(H-SAF) PROJECT PLAN - Version 2

H-SAF/CDR/Doc.2a 

31 October 2007 

revised 8 Feb 2008 (PP-2.1) 

revised 10 April 2008 (PP-2.2) 

Presented by Italy 

Satellite Application Facility on 

Support to Operational Hydrology and Water Management 

(H-SAF) 

PROJECT PLAN - Version 2 (PP-2.0) 

Submitted to the Critical Design Review, 17-18 December 2007 

This document is the update of the baseline Project Plan (PP-1.0) of the H-SAF 

Development Phase, dated 3 April 2006 and approved at the Requirements Review of 

26-27 April 2006 (RR). 

The purpose of the PP is to describe the work envisaged by the Development Proposal 

to the level necessary to monitor the development progress rate by anchoring activities 

to the project schedule as defined by the review meetings. The activities to implement 

the deliverable products are described with regard to the various product releases, and 

organisational aspects are deployed with as much detail as needed to identify 

responsibilities of each participant concurring to products generation. The 

Hydrological validation programme is structured so that each participant is responsible 

of a self-standing project described with due detail. 

This Version 2.0 incorporates recommendations put forward at the RR and registers 

changes occurred in the programme evolution since the last 1.5 years. In addition, it 

introduces a different structure: whilst PP-1.0 was structured by participating 

countries, PP-2.0 is structured by activities (or “Clusters”). This will facilitate the 

appreciation of work progress. 

In parallel with updating the Project Plan, the User Requirements Document is 

updated from Version 1.0 to URD-2.0. 

The document is split in two parts: PP-2.0-Main and PP-2.0-Appendix. The Appendix 

contains the Work Package Description sheets (WPD’s) and the list of Deliverables 

specifying the links among WP, deliverable and project document containing the 

deliverable. 

Recommended Actions by the Critical Design Review: 

1) To discuss the Project Plan Version PP-2.0 as appropriate. 

2) To recommend it for approval at the Steering Group meeting on 19 December 2007. 

Version PP-2.2 dated 10 April 2008

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Document change record Page 2 

DOCUMENT CHANGE RECORD OF THE PROJECT PLAN 

Version Date Description 

1.0 03 Apr 2006 Baseline submitted to the Requirements Review on 26-27 April 2006 

1.0-Add.1 16 Nov 2006 Implementation of recommendations from the RR Board 

Change 1 Pages 37-38 - Consequence of RID OBJ1_URD_Alarcon_019 

Change 2 Pages 154 and 160 - Consequence of RID OBJ3_PP_Alarcon_001 

Change 3 Page 34 - Consequence of RID OBJ3_PP_Alarcon_002 

Change 4 Page 50, Fig. 10 - Consequence of RID OBJ3_PP_Alarcon_007 

Change 5 Page 118 of the Main text, and WPD’s 091, 092, 093, 094, 095, 096 and 097 of 

the Appendix - Consequence of RID OBJ3_PP_Alarcon_008 

Change 6 Page 72 and Fig. 14 - Consequence of RID OBJ3_PP_Trigo_046 

Change 7 Pages 106-107 - Consequence of RID OBJ3_PP_Trigo_048 

Change 8 Several typo’s in several pages - Consequence of RID OBJ3_PP_Trigo_051 

2.0 31 Oct 2007 Submitted to the Critical Design Review (CDR, 17-18 December 2007) 

Change 1 Document placed under configuration control - Consequence of RID 

OBJ3_PP_Alarcon_006 

Change 2 Addition of mailing list 

Change 3 Addition of Applicable documents 

Change 4 Addition of Definitions, Acronyms, list of Tables, list of Figures, list of WBS’s 

Change 5 Re-structuring by Cluster instead of by Country 

Change 6 Page 23 - Table 2 updated - Consequence of RID OBJ3_PP_Trigo_043 

Change 7 Page 35 - WP-1240 added - Consequence of RID OBJ3_PP_Secretariat_021 

Change 8 Page 37 - Inter-SAF activity added - Consequence of RID OBJ3_PP_Trigo_042 

Change 9 CNR-IFAC soil moisture and snow products removed - Snow products for flat and 

mountainous areas now merged - RID OBJ3_PP_Trigo_045 accomplished 

Change 10 Addition of list of Deliverables in the Appendix - Consequence of RID 

OBJ3_PP_Alarcon_018 

Change 11 Page 35 - WP-1140 added to make explicit the tasks of planning and editing 

Change 12 Page 35 - WP-1330 added to make explicit the task of engineering documentation 

Change 13 Page 46 - WP-2110 results of merging acquisition and pre-processing tasks 

Change 14 Page 51 - MW from conical and cross-track scanners now two distinct products 

Change 15 Page 51 - Blended IR/MW by R.U. and Morphing now two distinct products 

Change 16 Page 53 - WP-2220 does not include experimental products any longer 

Change 17 Page 55 - WP-2300 only includes Validation. Calibration moved to WP-2400 

Change 18 Page 55 - Italian contribution to WP-2300 split over 3 WP’s (2310, 2350, 2360) 

Change 19 Page 57 - WP-2400 now includes all product developments (not only advanced) 

Change 20 Page 72 - Global and Regional surface soil moisture now two distinct products 



Change 23 Pages 92 (WP-4100) and 96 (WP-4200) - The new structure is by activity type 

(operationally-oriented) whereas in PP-1.0 was by product, including development 

Change 24 Page 95 - Snow status and snow cover now two distinct products 



Change 27 Pages 112-147 - General: relevant information from the “Hydrological validation 

plan” developed in the time span between PP-1.0 and PP-2.0 has been utilised 

Change 28 Page 113 - Replacements of test sites: WP-5500: Sieg, Sulzbach and Dill 

replaced by Rhine; WP-5700: Prosna replaced by Czarna; WP-5900: Sakaria and 

Manavgat replaced by Susurluk and West Black Sea 

Change 29 Page 123 - Specific section on Reporting added 

Change 30 Pages 124-146 - Test site description sheets updated 

continue ….

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Document change record Page 3 

continuation … 

Version Date Description 

2.1 8 Feb 2008 Incorporating remarks from CDR-1 (17-18 December 2007) 

Change 1 Pages 9-11 - In order to comply with RID OBJ1_ATDD_PART1_Bennartz_018, 

page numbers have been added to the lists of tables, figures and WBS’s 

Change 2 Because of RID OBJ2_REP_2_Secretariat_009, the terminology has been 

aligned to EUM/PPS/TEN/07/0036 issue 1 A. Previous terms such as “Version-1” 

and “Version-2” have been replaced through the whole text. Use is made of terms 

such as “demonstrational”, “pre-operational” and “operational” products 

Change 3 Page 29, Fig. 5 - Again because of RID OBJ2_REP_2_Secretariat_009 on 

standard terminology, several terms in the figure have been replaced 

Change 4 Page 35, Table 8: 

• CDR: 

- SRD-2.0 added due to the need to align with URD-2.0; 

• SIRR: 

- REP-3 added, as internal rolling document on product validation activities, 

to be run until the ORR 

- REP-4 added, as internal rolling document on hydrological validation 

activities, to be run until the ORR; 

• STRR: 

- URD-3.0 added due to the need to update the product performance 

requirements accounting for the results of validation 

- REP-5 was previously named REP-2.1 (REP-2.1 has been used for the 

REP-2.0 version adjusted after CDR-1); 

• WS-2: 

- previous “HYDRO” consists of the issue of REP-4 at the time of WS-2; 

• SVRR: 

- FR-0.5 (Draft Final Report) was previously named REP-2.5; 

• ORR: 

- FR-1.0 (Final Report) was previously named REP-3 

- in order to account for CDR-1 RID OBJ4_PP_Secretariat_017 the 

Proposal for the H-SAF Operational Phase (OP) is no longer included 

Change 5 Page 36 - The structure of the ORR documentation has been defined so as to 

comply with CDR-1 RID OBJ4_PP_Secretariat_017 

Change 6 Appendix A3 - Deliverables previously addressing documents that changed name 

as described in Change 4 have been re-addressed to the new names 

2.2 10 Apr 2008 Re-structured due to remarks from CDR-2 (3-4 March 2008) 

Change 1 In Table 8, page 35 document SVERF-0.6 has been added to the SIRR review 

and document SVALF-0.5 has been moved from SIRR to STRR 

Change 2 The definition of the product status has been further refined. Specifically, Fig. 1 

has been modified to achieve full consistency with doc. EUM/PPS/TEN/07/0036 

issue 1 A) 

Change 3 A new test for the Hydro-validation programme, the Kemijoki basin in Finland, 

has been introduced. Consequently, Fig. 2 and Fig. 27 have been updated; 

Section 7.3.3 and a new test site descriptive sheet has been added 

Change 4 The previous WP-5200, that was collecting the developments for the impact 

studies, repeating the tasks for each country (previously 7, now 8), has been 

spread under the WP’s of the various countries relative to the impact studies 

(i.e., previous WP’s 5210, 5220, 5230 …, have become 5210, 5310, 5410 …). 

WBS-18 of WP-5000 and all following ones consequently have been adjusted 

Change 5 The Appendix has been re-aligned to the new structure of WP’s in WP-5000

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Distribution list Page 4 

DISTRIBUTION LIST (general for H-SAF) (1 st sheet of 2) 

Country Institute Name E-mail 

Austria ZAMG Veronika Zwatz-Meise zwatz-meise@zamg.ac.at 

ZAMG Alexander Jann alexander.jann@zamg.ac.at 

TU-Wien / IPF Wolfgang Wagner ww@ipf.tuwien.ac.at 

TU-Wien / IPF Stefan Hasenauer sh@ipf.tuwien.ac.at 

Belgium IRM Emmanuel Roulin emmanuel.roulin@oma.be 

IRM Hans Van de Vijver hans.vandevijver@oma.be 

ECMWF Philippe Bougeault philippe.bougeault@ecmwf.int 

Matthias Drusch matthias.drusch@ecmwf.int 

Klaus Scipal 

klaus.scipal@ecmwf.int 

Finland FMI Pirkko Pylkko pirkko.pylkko@fmi.fi 

FMI Jarkko Koskinen jarkko.koskinen@fmi.fi 

FMI Jouni Pulliainen jouni.pulliainen@fmi.fi 

FMI Panu Lahtinen panu.lahtinen@fmi.fi 

TKK Juha-Petri Karna juha-petri.karna@tkk.fi 

SYKE Sari Metsämäki sari.metsamaki@ymparisto.fi 

France Météo France Jean-Christophe Calvet jean-christophe.calvet@meteo.fr 

Météo France Laurent Franchisteguy laurent.franchisteguy@meteo.fr 

CNRS-CETP Mehrez Zribi mehrez.zribi@cetp.ipsl.fr 

CNRS-CESBIO Patricia de Rosnay derosnay@cesbio.cnes.fr 

Germany BfG Thomas Maurer thomas.maurer@bafg.de 

BfG Peer Helmke helmke@bafg.de 

Hungary OMSZ Eszter Lábó labo.e@met.hu 

Italy USAM Massimo Capaldo m.capaldo@meteoam.it 

CNMCA Luigi De Leonibus l.deleonibus@meteoam.it 

CNMCA Costante De Simone c.desimone@meteoam.it 

CNMCA Francesco Zauli f.zauli@meteoam.it 

CNMCA Daniele Biron d.biron@meteoam.it 

CNMCA Davide Melfi d.melfi@meteoam.it 

CNMCA Attilio Di Diodato a.didiodato@meteoam.it 

CNMCA Lucio Torrisi l.torrisi@meteoam.it 

CNMCA Massimo Bonavita m.bonavita@meteoam.it 

CNMCA Adriano Raspanti a.raspanti@meteoam.it 

CNMCA Alessandro Galliani a.galliani@meteoam.it 

DPC Roberto Sorani hsaf.management@protezionecivile.it 

DPC Luca Rossi luca.rossi@protezionecivile.it 

DPC Silvia Puca silvia.puca@protezionecivile.it 

DPC William Nardin william.nardin@protezionecivile.it 

CNR-ISAC Franco Prodi f.prodi@isac.cnr.it 

CNR-ISAC Bizzarro Bizzarri bibizzar@tin.it 

CNR-ISAC Alberto Mugnai a.mugnai@isac.cnr.it 

CNR-ISAC Vincenzo Levizzani v.levizzani@isac.cnr.it 

CNR-ISAC Francesca Torricella f.torricella@isac.cnr.it 

CNR-ISAC Stefano Dietrich s.dietrich@isac.cnr.it 

CNR-ISAC Francesco Di Paola francesco.dipaola@artov.isac.cnr.it 

Ferrara University Federico Porcu' porcu@fe.infn.it 

Ferrara University Angelo Rinollo a.rinollo@isac.cnr.it 

DATAMAT Flavio Gattari flavio.gattari@datamat.it 

DATAMAT Emiliano Agosta emiliano.agosta@datamat.it

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Distribution list Page 5 

DISTRIBUTION LIST (general for H-SAF) (2 nd sheet of 2) 

Poland IMWM Piotr Struzik piotr.struzik@imgw.pl 

IMWM Bozena Lapeta bozena.lapeta@imgw.pl 

IMWM Jerzy Niedbala jerzy.niedbala@imgw.pl 

IMWM Jaga Niedbala jaga.niedbala@imgw.pl 

IMWM Monika Pajek monika.pajek@imgw.pl 

IMWM Jakub Walawender jakub.walawender@imgw.pl 

IMWM Jan Szturc jan.szturc@imgw.pl 

Romania NMA Andrei Diamandi diamandi@meteo.inmh.ro 

NMA Simona Oancea simona.oancea@meteo.inmh.ro 

Slovakia SHMÚ Ján Kaňák jan.kanak@shmu.sk 

SHMÚ Marián Jurašek marian.jurasek@shmu.sk 

SHMÚ Marcel Zvolenský marcel.zvolensky@shmu.sk 

SHMÚ Daniela Kyselová daniela.kyselova@shmu.sk 

Turkey TSMS Fatih Demýr fdemir@meteor.gov.tr 

TSMS Ali Umran Komuscu aukomuscu@meteor.gov.tr 

TSMS Ibrahim Sonmez isonmez@meteor.gov.tr 

TSMS Aydın Erturk agerturk@meteor.gov.tr 

TSMS Erdem Erdi eerdi@meteor.gov.tr 

METU Ali Unal Sorman sorman@metu.edu.tr 

METU Zuhal Akyurek zakyurek@metu.edu.tr 

METU Orhan Gokdemir orhan.gokdemir@gmail.com 

METU Ozgur Beser beser@metu.edu.tr 

ITU Zekai Şen zsen@itu.edu.tr 

ITU Ahmet Öztopal oztopal@itu.edu.tr 

Anadolu University Aynur Sensoy asensoy@anadolu.edu.tr 

Anadolu University Arda Sorman asorman@anadolu.edu.tr 

EUMETSAT Lorenzo Sarlo lorenzo.sarlo@eumetsat.int 

Frédéric Gasiglia frederic.gasiglia@eumetsat.int 

Dominique Faucher dominique.faucher@eumetsat.int 

Jochen Grandell jochen.grandell@eumetsat.int 

Lothar Schüller lothar.schueller@eumetsat.int 

Hans Bonekamp hans.bonekamp@eumetsat.int 

Zoltan Bartalis zoltan.bartalis@eumetsat.int

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Index and Lists Page 6 

INDEX 

Applicable documents 011 

Definitions and Acronyms 012 

1. Introduction - Purpose of the Project Plan 017 

2. Highlights from the Development Proposal 018 

2.1 The objectives of H-SAF 018 

2.2 The participants and their roles 018 

2.3 The envisaged products 024 

2.4 The Hydrological validation programme 025 

2.5 The general architectural concept 027 

2.6 The stepwise development approach 027 

2.7 The Work Breakdown Structure 030 

2.8 The management structure 033 

2.9 Programme schedule, Review meetings, documentation 034 

3. The Coordination task (WP-1000) 037 

3.1 Introduction 037 

3.2 The management task (WP-1100) 037 

3.3 The data service (WP-1200) 040 

3.4 The engineer task (WP-1300) 043 

3.5 Programme schedule of WP-1000 045 

4. The precipitation task (WP-2000) - Cluster-1 046 


4.2 Observation of precipitation (WP-2100) 048 

4.2.1 Generalities 048 

4.2.2 The data acquisition and pre-processing task (WP-2110) 051 

4.2.3 The products generation task (WP-2120) 053 

4.2.4 Quality control and distribution (WP-2130) 054 

4.3 Computed precipitation (WP-2200) 054 


4.3.2 Quantitative precipitation forecast (WP-2210) 055 

4.3.3 NWP model improvement (WP-2220) 056 

4.4 Precipitation products validation (WP-2300) 057 


4.4.2 Validation philosophy (WP-2310) 057 

4.4.3 Validation activity (WP’s 2320 to 2390) 058 

4.5 Developments (WP-2400) 059 


4.5.2 Precipitation by MW conical scanning radiometers (WP-2410) 060 

4.5.3 Precipitation by MW cross-track scanning radiometers (WP-2420) 060 

4.5.4 Precipitation by blending MW and IR observations (WP-2430) 061 

4.5.5 Accumulated precipitation (WP-2440) 062 

4.5.6 Complementary R&D work at ECMWF (WP-2450) 062 

4.6 Summary description of precipitation products 063 

4.7 Programme schedule of WP-2000 069


5. The soil moisture task (WP-3000) - Cluster-2 071 


5.2 Observation of surface soil moisture (WP-3100) 073 





5.3 Observation of volumetric soil moisture (WP-3200) 078 


5.3.2 Surface data assimilation system for ERS data (WP-3210) 079 

5.3.3 Surface data assimilation system for ASCAT data (WP-3220) 080 

5.4 Soil moisture products validation (WP-3300) 081 






5.5.2 Global surface soil moisture (WP-3410) 084 

5.5.3 Regional surface soil moisture (WP-3420) 084 

5.5.4 Volumetric soil moisture (WP-3430) 085 

5.5.5 Use of SMOS for soil moisture products development (WP-3440) 085 

5.6 Summary description of soil moisture products 086 


6. The snow observation task (WP-4000) - Cluster-3 092 


6.2 Observation of snow parameters in flat/forested areas (WP-4100) 093 





6.3 Observation of snow parameters in mountainous areas (WP-4200) 098 





6.4 Snow products validation (WP-4300) 101 






6.5.2 Snow recognition (WP-4410 and WP-4420) 104 

6.5.3 Complementary investigation on snow recognition (WP-4430) 105 

6.5.4 Snow status (WP-4440) 105 

6.5.5 Effective snow cover (WP-4450 and WP-4460) 106 

6.5.6 Snow water equivalent (WP-4470 and WP-4480) 106 

6.6 Summary description of snow products 107 

6.7 Programme schedule of WP-4000 112


7. The Hydrological validation programme (WP-5000) - Cluster-4 114 


7.2 The Education and Training programme (WP-5100) 115 

7.3 The impact study programme 117 


7.3.2 Impact studies in Belgium (WP-5200) 119 

7.3.3 Impact studies in Finland (WP-5300) 119 

7.3.4 Impact studies in France (WP-5400) 120 

7.3.5 Impact studies in Germany (WP-5500) 121 

7.3.6 Impact studies in Italy (WP-5600) 122 

7.3.7 Impact studies in Poland (WP-5700) 123 

7.3.8 Impact studies in Slovakia (WP-5800) 123 

7.3.9 Impact studies in Turkey (WP-5900) 124 

7.3.10 Typical activities implied by the impact studies 125 

7.4 Reporting 126 

7.5 Summary description of test sites 126 


8. Risk analysis and management 156 

8.1 General approach 156 

8.2 Specific risk analysis 156 

Reference to the Appendix 163 

Appendix - Work Package Description sheets (WPD) and Deliverables (separate doc. of 147 pages) 

A.1 List of Work Package Description sheets 

A.2 Work Package Description sheets 

A.3 List of Deliverables from WP’s and their location in H-SAF documentation 

List of Tables 

Table 01 Composition of the H-SAF Consortium 18 

Table 02 Required satellite-derived H-SAF products and satellite data sources 24 

Table 03 Backup products generated by a NWP model 25 

Table 04 List of undertakings of each Country split by WP up to the 3 rd level - Also list of 32 

WPD’s 

Table 05 Management components of H-SAF 33 

Table 06 Composition of the Steering Group as of end-2007 33 

Table 07 Events providing anchor points for the work schedule 34 

Table 08 List of deliverable documents for the Review meeting and the Workshops 35 

Table 09 Evolution of documents supporting meetings and Workshops 36 

Table 10 List of main hydrological models to be used for the Hydrological validation 

programme 

126 

List of Figures 

Fig. 01 Concept of the hydrological validation Cluster and its relation to Clusters 1 to 3 26 

Fig. 02 Countries involved in impact studies / validation of satellite products with use of 26 

hydrological models


Fig. 03 Sketch system architecture of H-SAF 27 

Fig. 04 Logic of the H-SAF Development Phase 28 

Fig. 05 Logic of the incremental development scheme 29 

Fig. 06 Top-level management structure of H-SAF 33 

Fig. 07 H-SAF central archive and distribution facilities 41 

Fig. 08 Conceptual architecture of the processing chain for precipitation products 49 

generation 

Fig. 09 Main components of the precipitation products generation sub-system 50 

Fig. 10 Main data flows to, within and from the precipitation products generation subsystem 

50 

Fig. 11 Relationships between satellite data and output products 51 

Fig. 12 One-orbit coverage from six operational meteorological satellites equipped with 52 

MW instruments in years 2008-2009. The figure assumes all satellites cross the 

ascending or descending equatorial node at 12 UTC. In red, conical scanning 

imagers (swath 1400 km); in blue cross-track scanning sounders (swath 2200 km) 

Fig. 13 Products generation chain for Quantitative Precipitation Forecasting 55 

Fig. 14 Conceptual architecture of the soil moisture production chain 72 

Fig. 15 Main components of the soil moisture product generation chain 73 

Fig. 16 Surface soil moisture products generation chain 74 

Fig. 17 Data flows within the soil moisture product generation chain of Austrian 75 

responsibility 

Fig. 18 ASCAT coverage in 24 h. The close-to-nadir 700-km gap in between the two 76 

500-km lateral swaths is not shown 

Fig. 19 Logic of the soil moisture extraction algorithm 77 

Fig. 20 Flow chart of the root zone soil moisture processing chain 79 

Fig. 21 Conceptual architecture of the snow product generation chain in Finland 94 

Fig. 22 Main subsystem components of the snow product generation chain in Finland 95 

Fig. 23 Relationships between satellite data and snow output products 95 

Fig. 24 Coverage from AVHRR (in 6 hours) and MODIS (in 9 hours) during the 96 

Development Phase 

Fig. 25 Conceptual architecture of the snow product generation chain in Turkey 99 

Fig. 26 Logic of the snow product generation chain in Turkey 99 

Fig. 27 Location and geo-morphological situation of test sites for the impact studies 118 

List of Work Breakdown Structures 

WBS-01 First two levels of the H-SAF WBS 030 

WBS-02 WBS of WP-1000: 1 st , 2 nd and 3 rd level WP’s. No 4 th level WP’s defined 037 

WBS-03 WBS of WP-2000: 1 st , 2 nd and 3 rd level WP’s. 4 th level WP’s defined in next sections 047 

WBS-04 WBS of WP-2100: 2 nd , 3 rd and 4 th level WP’s 048 






WBS-10 WBS of WP-3200: 2 nd , 3 rd and 4 th level WP’s 079


















WBS-27 WBS of WP-5900: 2 nd , 3 rd and 4 th level WP’s 125

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Applicable documents Page 11 

Applicable documents 

[Ref. 1] Summary Report of the SAF Hydrology Framework Working Group, Annex 1 to document 

EUM/STG/44/04/DOC/11 dated 2 April 2004. 

[Ref. 2] Proposal for the development of a “Satellite Application Facility” on “Support to Operational 

Hydrology and Water Management” (H-SAF), submitted by the “Servizio Meteorologico 

dell’Aeronautica”, Italy, on behalf of the H-SAF Consortium - Issue 2.1 dated 15 May 2005. 

[Ref. 3] H-SAF Project Plan, version 1.0 (PP-1.0), dated 3 April 2006. 

[Ref. 4] H-SAF User Requirements Document, version 1.0 (URD-1.0) dated 3 April 2006. 

[Ref. 5] Algorithm Theoretical Definition Document, version 0.5 (ATDD-0.5) dated 20 October 2006. 

[Ref. 1] and [Ref. 2] provide the scenario of available methodologies and algorithms, aiming at 

demonstrating the feasibility of fulfilling the objectives of H-SAF. [Ref. 1] exhibits the possible things 

to do, [Ref. 2] defines the selected options among those displayed in [Ref. 1] and displays the 

undertaking of the H-SAF Consortium vis-à-vis the EUMETSAT Council. 

[Ref. 3] and [Ref. 4] enter the details of what to do and how. 

[Ref. 5] is the preliminary version of ATDD. 

In parallel with updating PP-1.0 by this PP-2.0, ATDD-1.0 moving from ATDD-0.5 and URD-2.0 

moving from URD-1.0 also are being updated.

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Definitions and Acronyms Page 12 

Definitions 

Bands of the e.m. spectrum utilised in Remote sensing 

UV Ultra-Violet 0.01 - 0.38 µm 

VIS Visible 0.38 - 0.78 µm 

B Blue 435.8 nm 

G Green 546.1 nm 

R Red 700.0 nm 

NIR Near Infra-Red 0.78 - 1.30 µm 

SWIR Short-Wave Infra-Red 1.30 – 3.00 µm 

MWIR Medium-Wave Infra-Red 3.00 – 6.00 µm 

TIR Thermal Infra-Red 6.00 – 15.0 µm 

FIR Far Infra-Red 15 µm - 1 mm (= 300 GHz) 

Sub-mm Submillimetre wave (part of FIR) 3000 - 300 GHz (or 100 µm - 1 mm) 

Mm Millimetre wave (part of MW) 300 - 30 GHz (or 1-10 mm) 

MW Microwave 300 - 1 GHz (or 1 mm - 30 cm) 

SW Short Wave 0.2 - 4.0 µm 

LW Long Wave 4 - 100 µm 

IR Infra-Red (MWIR + TIR) 3 - 15 µm 

VNIR Visible and Near Infra-Red (VIS + NIR) 0.38 - 1.3 µm 

Radar bands according to the American Society for Photogrammetry and Remote Sensing (ASPRS) 

Band Frequency range Wavelength range 

P 220 - 390 MHz 77 -136 cm 

UHF 300 - 1000 MHz 30 -100 cm 

L 1 - 2 GHz 15 - 30 cm 

S 2 - 4 GHz 7.5 - 15 cm 

C 4 - 8 GHz 3.75 - 7.5 cm 

X 8 – 12.5 GHz 2.4 - 3.75 cm 

Ku 12.5 - 18 GHz 1.67 - 2.4 cm 

K 18 - 26.5 GHz 1.18 - 1.67 cm 

Ka 26.5 - 40 GHz 0.75 - 1.18 cm 

V 40 - 75 GHz 4.0 - 7.5 mm 

W 75 - 110 GHz 2.75 - 4.0 mm 

Qualification of products development status according to doc. EUM/PPS/TEN/07/0036 issue 1 A 

In development 

Demonstrational 

Pre-operational 

Operational 

Products or software packages that are in development and not yet available to users 

Products or software packages that are provided to users without any commitment on 

the quality or availability of the service and have been considered by the relevant 

Steering Group to be useful to be disseminated in order to enabling users to test the 

product and to provide feedback 

Products or software packages with documented limitations that are able to satisfy the 

majority of applicable requirements and/or have been considered by the relevant 

Steering Group suitable for distribution to users 

Products or software packages with documented non-relevant limitations that largely 

satisfy the requirements applicable and/or have been considered by the relevant 

Steering Group mature enough for distribution to users 

Acronyms 

A-HRPT 

AMI-SCAT 

AMSR-2 

AMSR-E 

AMSU 

Advanced High Resolution Picture Transmission (on MetOp) 

Active Microwave Instrument (AMI) operating as wind SCATterometer (on ERS-1/2) 

Advanced Microwave Scanning Radiometer - 2 (on GCOM-W) 

Advanced Microwave Scanning Radiometer for EOS (on EOS-Aqua) 

Advanced Microwave Sounding Unit (on NOAA and MetOp)


AMSU-A Advanced Microwave Sounding Unit - A (on NOAA, MetOp and EOS-Aqua) 

AMSU-B Advanced Microwave Sounding Unit - B (on NOAA up to NOAA-17) 

ASAR Advanced Synthetic Aperture Radar (on Envisat) 

ASCAT Advanced Scatterometer (on MetOp) 

ATDD Algorithms Theoretical Definition Document 

ATMS Advanced Technology Microwave Sounder (on NPP and NPOESS) 

AU 

Anadolu University (in Turkey) 

AVHRR Advanced Very High Resolution Radiometer (on NOAA and MetOp) 

AWOS Automatic Weather Observing Station 

BfG 

Bundesanstalt für Gewässerkunde 

BILTEN Information Technologies and Electronics Research Institute (in TUBITAK, Turkey) 

BLUE Best Linear Unbiased Estimate 

BUFR Binary Universal Form for the Representation of meteorological data 

CDA Command and Data Acquisition station 

CDD Component Design Document 

CDF Cumulative Distribution Function 

CDOP Continuous Development Operations Phase 

CDR Critical Design Review 

CESBIO Centre d'Etudes Spatiales de la BIOsphere (of CNRS) 

CETP Centre d’études des Environnements Terrestres et Planétaires (of CNRS) 

CGMS Coordination Group for Meteorological Satellites 

CHy Commission of Climatology (of WMO) 

CLI-SAF SAF on Climate Monitoring 

CMIS Conical-scanning Microwave Imager/Sounder (on NPOESS starting from NPOESS-2). 

CMP Configuration Management Plan 

CNMCA Centro Nazionale di Meteorologia e Climatologia Aeronautica (in Italy) 

CNR Consiglio Nazionale delle Ricerche (of Italy) 

CNRS Centre Nationale de la Recherche Scientifique (of France) 

CORINE Coordinated Information on the European Environment 

COSMO Consortium for Small-Scale Modelling 

CRD Cloud-Radiation Database 

CRD Component Requirement Document 

CrIS Cross-track Infrared Sounder (on NPP and NPOESS) 

CRM Convection Resolving Model or Cloud Resolving Model 

CVERF Component Verification File 

DEM Digital Elevation Model 

DMSP Defense Meteorological Satellite Program 

DOF Data Output Format 

DPC Dipartimento Protezione Civile (of Italy) 

DPR Dual-frequency Precipitation Radar (on the GPM “core” satellite) 

DRiFt Discharge River Forecast Rainfall Runoff model (hydrological model) 

DWD Deutscher Wetterdienst 

E&T Education and Training 

EARS EUMETSAT Advanced Retransmission Service 

ECMWF European Centre for Medium-range Weather Forecasts 

EKF Extended Kalman Filter 

EOS Earth Observing System (Terra, Aqua, Aura) 

ERS European Remote-sensing Satellite (1 and 2) 

FAC Frequently Asked Questions 

FAR False Alarm Rate 

FMI Finnish Meteorological Institute 

FTP 

File Transfer Protocol 

GCOM-W Global Change Observation Mission - Water 

GEO Geostationary Earth Orbit 

GIS 

Geographical Information System 

GM 

Global Monitoring mode (of ASAR on ENVISAT) 

GME Global Model - Europe 

GMES Global Monitoring for Environment and Security 

GMI GPM Microwave Imager (on the GPM “core” satellite)


GNSS Global Navigation Satellite System 

GPM Global Precipitation Measurement mission 

GPS Global Positioning System 

GRACE Gravity Recovery And Climate Experiment 

GRAS GNSS Receiver for Atmospheric Sounding (on MetOp) 

GRIB Gridded Binary 

GTS Global Telecommunication System 

HAS Hydrology Assimilation Suite 

HBV Hydrologiska Byrans Vattenbalansavdelning (hydrological model) 

HEC-HMS Hydrologic Engineering Center’s Hydrologic Modeling System 

HIRLAM High Resolution Limited Area Model 

HIRS High-resolution Infrared Radiation Sounder (on NOAA and MetOp 1/2) 

HMS Hungarian Meteorological Service 

HR 

Hit Rate 

Hron-NAM Hron and Nedbør-Afstrømmings Model (hydrological model) 

H-SAF SAF on Support to Operational Hydrology and Water Management 

HYDRO Preliminary results of Hydrological validation 

IASI Infrared Atmospheric Sounding Interferometer (on MetOp) 

ICD 

Interface Control Document 

IfIN 

Institute of Integrated Natural Resources (University of Koblenz, Germany) 

IFOV Instantaneous Field Of View 

IFS 

Integrated Forecast System 

ILR 

Institute for Landscape Ecology and Resources Management (Un. of Giessen, Germany) 

IMWM Institute of Meteorology and Water Management (of Poland) 

IPF 

Institut für Photogrammetrie und Fernerkundung (of TU-Wien) 

IR 

Infra Red 

IRM Institut Royal Météorologique 

ISAC Istituto di Scienze dell’Atmosfera e del Clima (of CNR) 

ITU 

İstanbul Technical University 

JPEG Joint Photographic Expert Group 

KOM Kick Off Meeting 

LEO Low Earth Orbit 

LIS 

Lightning Imaging Sensor (on TRMM) 

LM 

Local Model 

LSA-SAF SAF on Land Surface Analysis 

LST Laboratory of Space Technology (of SYKE, Finland) 

LST Local Solar Time (of a sunsynchronous orbit) 

MARF Meteorological Archive and Retrieval Facility (of EUMETSAT) 

MARS Meteorological Archive and Retrieval System (of ECMWF) 

MetOp Meteorological Operational satellite 

METU Middle East Technical University (in Turkey) 

MHS Microwave Humidity Sounder (on NOAA 18 and 19, and on MetOp) 

MIS Microwave Imager/Sounder (on NPOESS starting from NPOESS-2) (formerly CMIS) 

MIT Massachusetts Institute of Technology 

MMS Modular Modeling System 

MOBIDIC MOdello di Bilancio Idrologico DIstribuito e Continuo (hydrological model) 

MODIS Moderate-resolution Imaging Spectro-radiometer (on EOS Terra and Aqua) 

MP 

Modelling Platform of the IMWM (hydrological model) 

MPE Multi-sensor Precipitation Estimate 

MSG Meteosat Second Generation 

MVIRI Meteosat Visible and Infra Red Imager (on Meteosat up to 7) 

MW Micro Wave 

NASA National Aeronautical and Space Administration (in USA) 

NATO North Atlantic Treaty Organization 

NIMH National Institute for Meteorology and Hydrology (of Romania; now NMA) 

NMA National Meteorological Administration (of Romania; formerly NIMH) 

NMC National Meteorological Centre 

NOAA National Oceanic and Atmospheric Administration (Agency and satellite) 

NPOESS National Polar-orbiting Operational Environmental Satellite System


NPP 

NRT 

NWC-SAF 

NWP 

NWP-SAF 

OP 

ORR 

OSSE 

PDR 

Pixel 

POD 

POP 

PP 

PPF 

PPR 

PR 

PT 

QC 

QPF 

R&D 

R.U. 

REP 

RGB 

RID 

RR 

RTM 

s.s.p. 

SAF 

SAR 

SCHEME 

SDAS 

SDD 

SEVIRI 

SG 

SHMÚ 

SHW 

SIM 

SIRR 

SIVVP 

SMOS 

SRD 

SRM 

SSM/I 

SSMIS 

SSVD 

STRR 

SVALF 

SVERF 

SVRR 

SWE 

SWIR 

SYKE 

TBD 

TDR 

TIR 

TKK 

TMI 

TRMM 

TSMS 

NPOESS Preparatory Programme 

Near Real Time 

SAF in Support of Nowcasting and Very Short Range Forecasting 

Numerical Weather Prediction 

SAF on Numerical Weather Prediction 

Proposal for H-SAF Operational phase 

Operations Readiness Review 

Observing System Simulation Experiment 

Preliminary Design Review 

Picture element 

Probability Of Detection 

Precipitation Observation Production 

Project Plan 

Products Processing Facility (in EUMETSAT) 

Products Prototyping Reports 

Precipitation Radar (on TRMM) 

Project Team 

Quality Control 

Quantitative Precipitation Forecast 

Research and Development 

Rapid-Update 

Report 

Red-Green-Blue 

Review Item Discrepancy 

Requirements Review 

Radiative Transfer Model 

Sub-satellite-point 

Satellite Application Facility 

Synthetic Aperture Radar 

SCHEldt and MEuse (hydrological model) 

Surface Data Assimilation System 

System Design Document 

Spinning Enhanced Visible and Infra-Red Imager (on Meteosat from 8 onwards) 

Steering Group 

Slovenský Hydrometeorologický Ústav 

State Hydraulic Works (in Turkey) 

Safran-Isba-Modcou (hydro-meteorological model) 

System Integration Readiness Review 

System IV & V Plan 

Soil Moisture and Ocean Salinity 

System Requirements Document 

Snowmelt Runoff Model (hydrological model) 

Special Sensor Microwave / Imager (on DMSP up to F-15) 

Special Sensor Microwave Imager/Sounder (on DMSP starting with S-16) 

System/Software Version Description 

System Test Results Review 

System Validation File 

System Verification File 

System Validation Results Review 

Snow Water Equivalent 

Short-Wave IR 

Finnish Environment Institute 

To Be Defined 

Time Domain Reflectometers 

Thermal IR 

Helsinki University of Technology 

TRMM Microwave Imager (on TRMM) 

Tropical Rainfall Measuring Mission 

Turkish State Meteorological Service


TUBITAK Scientific and Technological Council of Turkey 

TU-Wien Technische Universität Wien 

UGM Ufficio Generale per la Meteorologia (of Italy; now USAM) 

UKMO United Kingdom Met Office 

UM 

User Manual 

U-MARF Unified Meteorological Archive and Retrieval Facility 

URD User Requirements Document 

USAM Ufficio Generale Spazio Aereo e Meteorologia (of Italy; formerly UGM) 

USGS United States Geological Survey 

UTC Coordinated Universal Time 

UVSQ University of Versailles-St Quentin (in France 

V1CP Version-1 Check Point 

VIIRS Visible/Infrared Imager Radiometer Suite (on NPP and NPOESS) 

VIS 

Visible 

WBS Work Breakdown Structure 

WMO World Meteorological Organisation 

WP 

Work Package 

WPD Work Package Description 

WS-1 1 st Workshop 

WS-2 2 nd Workshop 

ZAMG Zentral Anstalt für Meteorologie und Geodynamik

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 1 (Introduction) Page 17 

1. Introduction - Purpose of the Project Plan 

This Project Plan elaborates with higher detail the work programme outlined in the Development 

Proposal [Ref. 2]. 

In respect of the Development Proposal this Project Plan will: 

• streamline all parts originally included for highlighting principles and deploying possible options; 

• focus on the solutions finally adopted for implementation, providing further details if necessary; 

• expand all implementation details, including responsibilities and development steps. 

It follows that the original Development Proposal is not superseded at all by this Project Plan. On the 

contrary, the content and amplitude of the scientific discussions continue to be a reference. The 

activities to be actually performed during the Development Phase will instead be described to a fair 

degree of detail, particularly as regards the members of the Consortium that, not being Cluster leaders, 

did not have their activity enough well described because of volumetric limitations (the Development 

Proposal was 159 pages long, exceeding by far the EUMETSAT requirement for a compact document). 

The main objective of this Project Plan is to closely connect the activities to the envisaged development 

schedule, so as to have available a tool to monitor work progress across the 5-year Development Phase, 

specifically in the occasion of the Review meetings scheduled at approximately 6-month intervals. 

By developing the Project Plan as interlinked with the development schedule, it will be possible to 

identify the achievements visible to the Users at several points during the project, when successive 

versions of the various products will be released, after approximately 2 years and 3.5 years from start, 

and at the end of the Development Phase. Therefore, a major objective of this Project Plan is to identify 

the benchmark tests to be input in the User Requirements Document (URD), that constitutes the 

official statement for EUMETSAT to control the achievements of the H-SAF objectives. 

The structure of the first version of the Project Plan (PP-1.0) was designed so as to streamline the 

activity of monitoring work progress. Since there are 12 Participants to the Consortium, and four main 

activity streams, writing the detailed work programme and establishing all necessary links for 

programme control would have been extremely complex. To overcome the problem, PP-1.0 was 

structured by Country, each participating Country being responsible of a sort of sub-programme, as 

much as possible self-standing. With this PP-2.0, now that each Country is well aware of its 

commitment to the Project, the structure has been changed so as to provide the external observers with 

better appreciation of the data generation and assessment flow. PP-2.0 is structured by “Cluster”, i.e. 

the four thematic areas composing the Project (Precipitation, Soil moisture, Snow and Hydrology). On 

top of them, there is the Management area, encompassing activities common to the four thematic areas. 

The first version of the Project Plan, PP-1.0, submitted by Italy after consolidation by the Project Team, 

was discussed at the Requirements Review (RR) at approximately T 0 + 6 months (actual date: 26-27 

April 2006) and approved by the Steering Group (SG) at its 2 nd meeting (SG-2), on 28 April 2006. 

The updated version, PP-2.0, was due at approximately T 0 + 24 months and it is actually delivered on 

31 October 2007 to the Critical Design Review (CDR) scheduled for 17-18 December 2007, to be 

thereafter approved at SG-5 on 19 December 2007.

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 2 (From the Development Proposal) Page 18 

2. Highlights from the Development Proposal 

This Chapter reports the basic elements of the Development Proposal, that will be expanded in respect 

of details, responsibilities and scheduling in the follow-on chapters. 

2.1 The objectives of H-SAF 

The main objectives of H-SAF are: 

a. to provide new satellite-derived products from existing and future satellites with sufficient time and 

space resolution to satisfy the needs of operational hydrology; identified products: 

• precipitation (liquid, solid, rate, accumulated); 

• soil moisture (at large-scale, at local-scale, at surface, in the roots region); 

• snow parameters (detection, cover, melting conditions, water equivalent); 

b. to perform independent validation of the usefulness of the new products for fighting against 

floods, landslides, avalanches, and evaluating water resources; the activity includes: 

• downscaling/upscaling modelling from observed/predicted fields to basin level; 

• fusion of satellite-derived measurements with data from radar and raingauge networks; 

• assimilation of satellite-derived products in hydrological models; 

• assessment of the impact of the new satellite-derived products on hydrological applications. 

2.2 The participants and their roles 

The H-SAF participants and their roles in the Development Phase are recorded in Table 1. 

Table 1 - Composition of the H-SAF Consortium 

No. Country Units in the Country (responsible unit in bold) Role in the Project 

01 Austria 

- Zentral Anstalt für Meteorologie und Geodynamik 

- Technische Univ. Wien, Inst. Photogrammetrie & Fernerkundung 

Leader for soil moisture 

02 Belgium - Institut Royal Météorologique 

03 ECMWF - European Centre for Medium-range Weather Forecasts Contributor for “core” soil moisture 

04 Finland 

- Finnish Meteorological Institute 

- Helsinki Technical University, Laboratory of Space Technology Leader for snow parameters 

- Finnish Environment Institute 

05 France 

- Météo-France 

- CNRS Centre d'Etudes Spatiales de la BIOsphere 

- CNRS Centre d’études des Environnem. Terrestres et Planétaires 

06 Germany - Bundesanstalt für Gewässerkunde 

07 Hungary - Hungarian Meteorological Service 

08 Italy 

- Servizio Meteorologico dell’Aeronautica 

- Dipartimento Protezione Civile, Presidenza Consiglio Ministri 

- CNR Istituto di Scienze dell’Atmosfera e del Clima 

Host + Leader for precipitation 

- Ferrara University, Department of Physics 

09 Poland - Institute of Meteorology and Water Management Leader for Hydrology 

10 Romania - National Meteorological Administration 

11 Slovakia - Slovenský Hydrometeorologický Ústav 

12 Turkey 

- Turkish State Meteorological Service 

- Middle East Technical University, Civil Engineering Department 

- Istanbul Technical University, Meteorological Department 

- Anadolu University 

Contributor for “core” snow parameters 

Shortest descriptions of the operating Units and the Country undertaking follow. 

Austria 

The Zentralanstalt für Meteorologie und Geodynamik (ZAMG) (Central Institute for Meteorology and 

Geodynamics) is one of the Austrian National Meteorological Services. Within the H-SAF, its Vienna 

headquarters provide the coordination of the soil moisture theme (Cluster-2), the basic structure for the


technical activities with respect to the surface soil moisture sub-topic; and ultimately have the task of 

running the chain to generate the regional surface soil moisture product, as well as backing the chain 

generating the global soil mosture at the EUMETSAT Central Products Processing Facility (PPF). 

The Institut für Photogrammetrie und Fernerkundung (IPF) (Institute for Photogrammetry and 

Remote Sensing) of the Technische Universität Wien (TU-Wien) is responsible for the development of 

the surface soil moisture product and quality control criteria. As the scientific leaders of the surface soil 

moisture topic, they function as consultants to ZAMG's administrative tasks, where appropriate, and 

support ZAMG in the implementation of IPF software in quasi-operational processing chains. The 

Hydrological validation programme (Cluster-4) and the ECMWF (with respect to this institute's root soil 

moisture activities) also are supported by IPF/TU-Wien within the H-SAF Visiting Scientist framework. 

The Austrian activity in H-SAF covers: 

• coordination of Cluster-2 (soil moisture); 

• development of algorithms and software for surface soil moisture products; 

• generation of surface soil moisture products; 

• surface soil moisture products calibration and contribution to validation; 

• education and training on the use of satellite-derived soil moisture products in Hydrology. 

Belgium 

The Institut Royal Météorologique (IRM) of Belgium, specifically its Meteorological Research and 

Development Department, is responsible of the Belgium participation to H-SAF. IMR will also foster a 

dialogue with the local users such as the different Regional Authorities in charge of water management 

both in Belgium and in the neighbouring countries sharing the transboundary river basins of Yser, 

Scheldt, Meuse and Moselle. This link can result in specific projects funded externally. 

The Belgium activity in H-SAF covers: 

• contribution to validation of precipitation products; 

• contribution to validation of soil moisture products; 

• contribution to validation of snow products; 

• participation to the Hydrological validation programme. 

ECMWF 

The ECMWF activities are centred around the development of a root zone soil moisture product based 

on the forecast from the Numerical Weather Prediction model, satellite derived surface soil moisture, 

and an advanced data assimilation system. 

The ECMWF activity in H-SAF covers: 

• development of algorithms and software for the root zone soil moisture product; 

• generation of the root zone soil moisture product; 

• root zone soil moisture calibration, and contribution to validation; 

• contribution to development of precipitation products (by Visiting Scientist). 

Finland 

The Finnish Meteorological Institute (FMI) will provide the coordination of the snow products theme 

(Cluster-3). FMI will generate the Snow detection product on flat areas and forests, and provide data 

from satellites and synoptic weather stations to SYKE and TKK/LST for development and generation of 

the other snow products. 

The Finnish Environmental Institute (SYKE) will develop the Snow effective cover maps on flat areas 

and forests. SYKE has a similar product in operations in Finland. SYKE also carries out snow course 

measurements in Finland and runs a hydrological model for climatological and flood forecasting uses. 

The Laboratory of Space Technology at the Helsinki University of Technology (TKK/LST) is 

responsible of producing the Snow water equivalent and Snow status products for flat areas and forests.


TKK/LST has an important role in the international snow research community. The laboratory's 

research includes modelling of radiometer observations of snow covered terrain as well as development 

of applications including the retrieval of SWE and Snow Depth from radiometer and radar data. 

The Finish activity in H-SAF covers: 

• coordination of Cluster-3 (Snow parameters); 

• development of algorithms and software for snow products on flat areas and forests; 

• generation of snow products on flat areas and forests; 

• snow products calibration, and contribution to validation; 

• education and training on the use of satellite-derived snow products in Hydrology. 

France 

Météo France, specifically the Department of Operational Hydro-meteorology (DP/DCLIM/HYDRO). 

DP/DCLIM/HYDRO is in charge of operational hydro-meteorology at Météo-France, and represents 

France in the Commission for Hydrology of the World Meteorological Organization (WMO/CHy). It is 

responsible, i.a., of the national rainfall database. 

The Centre d’études des Environnements Terrestres et Planétaires (CETP), belonging to CNRS 

(Centre Nationale de la Recherche Scientifique), will participate in association with the University of 

Versailles-St Quentin (UVSQ). The CETP team has two main research activities: 

• the use of multi-frequency satellite remote sensing data to infer soil and vegetation parameters, 

• the assimilation of satellite remote sensed surface variables (surface temperature and/or soil 

moisture) in hydrological and surface models. 

The Centre d'Etudes Spatiales de la BIOsphere (CESBIO), also belongs to CNRS. CESBIO aims at 

developing knowledge on continental biosphere dynamics and functioning at various temporal and 

spatial scales. This includes its interactions with atmosphere and anthropic impact on water resources 

and land use. CESBIO leads the European space mission SMOS (Soil Moisture and Ocean Salinity). 

The French activity in H-SAF covers: 

• contribution of CETP to validation of soil moisture products; 

• contribution of CESBIO to the development of soil moisture products; 

• participation of Météo France to the Hydrological validation programme. 

Germany 

The Federal Institute of Hydrology (Bundesanstalt für Gewässerkunde, BfG), founded in 1948 but 

with precursors in Germany since 1851, has wide expertise in hydrological modelling, possible use of 

satellite products for that purpose and the usage of meteorological data and forecasts from the German 

Weather Service (Deutscher Wetterdienst, DWD). It has near-real time access to operational data of: 

• hydrological in-situ networks (hourly or shorter intervals); 

• weather forecasts of DWD (mainly precipitation and air temperature, hourly, 72 h ahead for the nonhydrostatic 

Local Model / LM and 3-hourly, 7 d ahead for the Global Model - Europe / GME); 

• in-situ and calibrated weather radar precipitation data (1 km², hourly, operational from 2005 on) 

provided by DWD; 

• snow parameters and forecasts of snow melt and precipitation from the SNOW2D model of DWD 

(1 km², hourly, operational from 2005 on, during periods of snow, currently for southern Germany, 

the prevailing area with snowfall); 

• Meteosat imagery. 

The following partners are envisaged to support BfG within the H-SAF Project: 

The University of Koblenz, Institute of Integrated Natural Resources (IfIN) did conduct research at 

two catchments providing hydrological modelling in support of Geographic Information System (GIS). 

A broad set of hydrological as well geo-referenced data will be made available for the H-SAF Project.


The University of Giessen, Institute for Landscape Ecology and Resources Management (ILR), has 

tested the Modular Modeling System (MMS), provided by the United States Geological Survey (USGS) 

on the Dill catchment, which is a sub-basin of the river Lahn. Therefore, it is intended to start 

cooperation with the relevant persons. 

The University of Bonn, Institute of Geography, has run several projects using MMS, thus cooperation 

with them is envisaged. 

The German activity in H-SAF covers: 




Hungary 

The Hungarian Meteorological Service (HMS) is responsible of the participation in H-SAF. In 

Hungary, about 90 automatic stations work, where 10-min precipitation is measured by tipping bucket 

rain gauges. There are three C-band dual polarized Doppler weather radars operated routinely by the 

HMS. The radars are corrected with rain gauge data. Accumulated rain is calculated for 12 h or more. 

At HMS the SAFNWC/MSG program package runs operationally. It derives cloud type product and 

precipitation products (convective rain rate and probability of precipitation) also. 

MSG composite images are created operationally. Mainly the night time or daytime microphysical RGB 

and the storm RGB are the most interesting for precipitation validation. They contain information on 

the cloud top microphysical parameters (particle size, optical depth, phase). 

The Hungarian activity in H-SAF covers: 

• contribution to validation of precipitation products. 

Italy 

The role of Italy in establishing H-SAF started with the formation of the “Working Group on a Potential 

SAF in Support to Operational Hydrology and Water Management” in December 2001, chaired by 

Giuseppina Monacelli of the Italian National Hydrological and Mareographic Service. That W.G. 

demonstrated the case of H-SAF in its report presented to the 51 st Session of the EUMETSAT Council 

in Autumn 2002. Thereafter, Italy played a very active role in the “SAF Hydrology Framework 

Working Group”, chaired by Anthony Hollingsworth (ECMWF), that analysed in full detail the 

objectives and the feasibility of H-SAF, to the extent of outlining a realistic work programme supported 

by a number of interested Countries. Following the presentation of the report to the 55 th Session of 

Council in Summer 2004, the Italian Meteorological Service coordinated the preparation of the 

Development Proposal, that was submitted it its final version on 15 May 2005 and approved by the 57 th 

Session of Council on 2-3 July 2005. In the occasion of Council-57 the Italian Meteorological Service 

was designated as Host Institute of H-SAF. 

The Italian Meteorological Service is represented in H-SAF by the Headquarters, Ufficio Generale 

Spazio Aereo e Meteorologia (USAM, formerly Ufficio Generale per la Meteorologia, UGM), and the 

National Meteorological Centre, Centro Nazionale di Meteorologia e Climatologia Aeronautica 

(CNMCA). The Headquarters provide H-SAF coordination, the National Meteorological Centre 

provides the basic structure for the technical activity, both in support of the Coordination function, and 

for running the task of generating precipitation products (Cluster-1). The use of the CNMCA facilities 

is not charged to the official H-SAF budget 

The Dipartimento Protezione Civile (DPC) of the Presidenza del Consiglio dei Ministri is associated to 

the Italian Meteorological Service in both management matters and technical activities. The DPC 

provides coverage of the 50 % cost to balance the 50 % EUMETSAT contribution. In addition, the 

DPC participates to the Hydrological validation programme (Cluster-4) outside the 50+50 % official H- 

SAF budget.


The Istituto di Scienze dell’Atmosfera e del Clima (ISAC) of the Consiglio Nazionale delle Ricerche 

(CNR) is responsible of the development backing precipitation product generation and quality control 

criteria under Cluster-1. It is supported by the Dipartimento di Fisica dell’Università di Ferrara for 

precipitation cal/val activities. 

The Italian activity in H-SAF covers: 

• the Coordination task and the associated centralised functions/facilities 

• coordination of Cluster-2 (precipitation); 

• development of algorithms and software for precipitation products; 

• generation of precipitation products; 

• precipitation products calibration and contribution to validation; 

• education and training on the use of satellite-derived precipitation products in Hydrology; 


Poland 

The Institute of Meteorology and Water Management (IMWM) is responsible for the coordination of 

the Hydrological validation programme (Cluster-4). IMWM has been performing meteorological and 

hydrological services as well as research and development activities in this field continuously for 85 

years. The hydrological and meteorological services are provided at the same institution in close 

cooperation. They use the same data, including satellite information. The IMWM tasks in this field are: 

• research and development in the fields of atmospheric physics and chemistry; climatology; 

agrometeorology; hydrology; oceanology; water chemistry and biology; water hydrodynamics; 

water resources management; water engineering and safety of water technical structures; economy, 

planning and forecasting in water management and engineering; analysis of processes and factors 

influencing water resources quality and sewage treatment; 

• performing the systematic meteorological and hydrological observations and measurements; 

• collection, archiving and processing of observations and measurements; 

• preparation and distribution of forecasts and warnings for protection of citizens, national economy 

and state safety. 

The Polish activity in H-SAF covers: 

• coordination of Cluster-4 (Hydrological validation programme); 




Romania 

The National Meteorological Administration (NMA), formerly National Institute for Meteorology and 

Hydrology (NIMH) will cooperate with the Cluster-3 leader, Finland for developmental activities in the 

field of snow products generation. Romania has a long-standing experience in snow remote sensing 

applications, software and algorithm development and validation and measurement campaigns. NMA 

will test and validate snow products on Romania’s mountain and flat land areas, perform validation 

campaigns for the development of algorithms and develop algorithms and software for the prototyping 

of snow products. 

The Rumanian activity in H-SAF covers: 

• contribution to development of snow products (in the Visiting Scientist framework). 

Slovakia 

The Slovenský Hydrometeorologický Ústav (SHMÚ) (Slovakia Hydro-Meteorological Institute) has 

broad experience in hydrological modelling. The operational hydrological and meteorological services 

are at the same institution, closely cooperating. The operationally used models are ready for assimilation


of data from different sources: conventional, radar, satellite. Methods used currently in operational 

hydrology of SHMÚ are: 

• antecedent precipitation index, empirical-regression model; 

• hydrodynamic model MIKE-11 being used in pre-operational testing mode; 

• HVB model and rainfall-runoff model of non-linear reservoir cascade being used for simulation. 

The Slovak rainfall-runoff model of the river Hron is currently in developing stage. Increasing of 

performance and precision of the model is expected by using satellite products of rainfall and snow as 

inputs. The MIKE-11 and HVB models are already adaptable for inputs of products like radar and 

satellite rainfall intensities and cumulative precipitation. An SHMÚ rainfall-runoff model is also being 

developed. 

The Slovakian activity in H-SAF covers: 



Turkey 

The Turkish State Meteorological Service (TSMS) is in charge of overall coordination and 

management of H-SAF activities. It provides the basic infrastructure for the technical activities, 

including satellite data acquisition and meteorological data, both for running the task of generating snow 

products (Cluster-3) in mountainous regions, and in support of the other undertakings of Turkey in H- 

SAF. The TSMS provides coverage of the 50 % cost to balance the 50 % EUMETSAT contribution. 

The Middle East Technical University (METU) is responsible for the developmental activities related 

to generating snow products in mountainous regions METU is also responsible of the Turkey 

participation to the Hydrological validation programme (Cluster-4), in cooperation with ITU and the 

Anadolu University. 

The Istanbul Technical University (ITU) is responsible for the contribution to the activity on 

precipitation (Cluster-1), and will take part in the Hydrological validation programme in cooperation 

with METU. 

The Anadolu University (AU) will perform impact studies in a number of test sites in the framework of 

the Hydrological validation programme, in cooperation with METU. 

The Scientific and Technological Council of Turkey - Information Technologies and Electronics 

Research Institute (TUBITAK-BILTEN) is a government institute that conducts contract researches 

with various organizations from business and the public sectors. They have experience on both passive 

and active microwave systems, electromagnetic boundary value problems, solving inverse problems 

related with the electromagnetic theory. 

The State Hydraulic Works (SHW) is the primary executive state agency of Turkey for overall water 

resources planning, operation, and management. Its main responsibilities include irrigation, 

hydroelectric power generation; domestic and industrial water supplies for large cities; recreation and 

research on water-related planning, design and construction materials. The SHW is also responsible for 

hydrometeorological measurements including snow course measurements and collects discharge data in 

large basins in Turkey. SHW also runs hydrological models for flood forecasting uses. SHW will 

provide users requirements in order to use the snow products in the hydrological models. 

The Turkish activity in H-SAF covers: 

• development of algorithms and software for snow products in mountainous areas; 

• generation of snow products in mountainous areas; 

• snow products calibration and contribution to validation; 


• participation to the Hydrological validation programme.


2.3 The envisaged products 

Table 2 lists the targeted satellite-derived H-SAF products. The Table lists the satellites to be used 

during the Development Phase and those to be available during the Operational Phase (> 2010). It is 

noted that the anticipated product quality will not be achieved during the Development Phase since 

NPOESS and GPM will only be available after 2010. The User Requirements Document (URD) will 

indicate the data quality expected at mid, three-quarter and end of the Development Phase. 

Table 2 - Required satellite-derived H-SAF products and satellite data sources 

Precipitation Anticipated product quality in the operational phase Satellites / Sensors 

products Resolution Accuracy Cycle Delay Development Operations 

Precipitation 

rate (by MW 

only) with flag 

for phase 

Precipitation 

rate (by MW + 

IR) with flag 

for phase 

Accumulated 

precipitation 

(by MW + IR) 

on 3, 6, 12, 24 h 

10 km (MIS) 

15 km (additional 

GPM satellites) 

10 km 

10 km 

10-20 % (> 10 mm/h) 

20-40 % (1-10 mm/h) 

40-80 % (< 1 mm/h) 

Ranging from that of 

MW to one degraded 

by an extent TBD 

Tentative: 

10 % over 24 h 

30 % over 3 h 

9 h (MIS only) 

3 h (full GPM) 

20 min 

15 min 10 min 

3 h 20 min 

Meteosat 

(MVIRI, SEVIRI) 

+ 

DMSP 

(SSM/I, SSMIS) 

+ 

NOAA + MetOp 

(AMSU-A, 

AMSU-B/MHS) 

+ 

EOS/Aqua 

(AMSR-E, 

AMSU-A, HSB) 

+ 

TRMM 

(TMI, PR, LIS) 

Meteosat 

(SEVIRI) 

+ 

NPP 

(ATMS) 

+ 

NPOESS 

(MIS, ATMS) 

+ 

Further satellites 

of the GPM 

(all equipped at 

least with a MW 

radiometer, one 

also with radar) 

+ 

GCOM-W 

(AMSR-2) 

Soil moisture Anticipated product quality in the operational phase Satellites / Sensors 


Soil moisture in 

the surface layer 

Soil moisture in 

the roots region 

25 km (from ASCAT) 

50 km (from MIS) 

25 km (from ASCAT) 

50 km (from MIS) 

0.05 m 3 m -3 

(depending 

on vegetation) 

To be assessed 

(model-dependent). 

Tentative: 0.05 m 3 m -3 

36 h (from ASCAT) 

9 h (from MIS) 

36 h (from ASCAT) 

9 h (from MIS) 

2 h 

2 h 

ERS 1 / 2 

(AMI-SCAT) 

+ 

MetOp 

(ASCAT) 

+ 

EOS/Aqua 

(AMSR-E) 

MetOp 

(ASCAT) 

+ 

NPOESS 

(MIS) 

+ 

GCOM-W 

(AMSR-2 

Snow Anticipated product quality in the operational phase Satellites / Sensors 


Snow detection 

by optical 

bands 

Effective cover 

by optical and 

MW bands, with 

flag for wet/dry 

Snow Water 

Equivalent by 

MW radiometer 

+ scatterometer 

2 km 

10 km (in MW) 

5 km (in 

VIS/SWIR/TIR) 

95 % probability of 

correct classification 

15 % (depending on 

basin size and complexity) 

10 km ~ 20 mm 

6 h (depending 

on latitude) 


on latitude) 


on latitude) 

2 h 

2 h 

2h 

NOAA 

(AVHRR) 

+ 

MetOp 

(AVHRR, ASCAT) 

+ 

Meteosat 

(SEVIRI) 

+ 

EOS-Terra/Aqua 

(MODIS) 

+ 

DMSP 

(SSM/I, SSMIS) 

+ 

EOS-Aqua 

(AMSR-E) 

+ 

QuickSCAT 

(SeaWinds) 

MetOp 

(AVHRR, ASCAT) 

+ 

Meteosat 

(SEVIRI) 

+ 

NPOESS 

(VIIRS, MIS) 

+ 

MW radiometers 

of the GPM 

constellation 

+ 

GCOM-W 

(AMSR-2 

It is noted that, in comparison with the Development Proposal and PP-1.0, the expected performances 

have been degraded in respect of the following aspects: 

• since the former CMIS has been somewhat descoped (now MIS), the cycle has been degraded from 

6 to 9 h (two satellites instead of 3) and the resolution degraded by 20 % (smaller antenna);


• the delay of precipitation products now includes 5 min for the transmission through EUMETCast 

(currently optimistic, but possibly realistic in the post-2010 timeframe). 

In addition to satellite-derived products, H-SAF will make available forecast products derived by a 

NWP limited-area model, so that end-users have available a back-up product at any time. The targeted 

forecast products are shown in Table 3. 

Table 3 - Backup products generated by a NWP model 

Forecast products Resolution Accuracy (long term > 2010) Cycle Delay 

Instantaneous 

precipitation rate 

at the ground 

Mid-project: 7 km, 

end-project: 2.5 km 

10-20 % (> 10 mm/h) 

20-40 % (1-10 mm/h) 

40-80 % (< 1 mm/h) 

Mid-project: 3-6 h, 

end-project: 1 h 

Fixed times 

of the day 

Accumulated precipitation 

10 % over 24 h, 30 % over 3 h 

Product generation is performed by groups of participants structured according to “Cluster-1” 

(precipitation), “Cluster-2” (soil moisture) and “Cluster-3” (snow). The Cluster leaders are Italy, 

Austria and Finland, respectively. ECMWF and Turkey have special roles in Cluster-2 and Cluster-3, 

respectively (see Table 1). 

Modelling and algorithm developed for product generation imply calibration and validation activity as 

an integral part, and routine generation includes a certain amount of on-line re-calibration/validation to 

monitor product quality stability and continuously improve error structure characterisation. 

2.4 The Hydrological validation programme 

It has already been demonstrated that high-quality satellite-derived hydrological parameters can be 

successfully used in operational applications, e.g. river run off predictions, flood forecasting, land 

surface model development. However, incompatible space-time scales, insufficient knowledge of 

orography and soil/subsoil/vegetation characteristics, insufficient communication/transport 

infrastructure, reliability and accuracy of general information including meteorological forecasts, may 

limit the benefits for certain applications. Therefore, there is a need to quantify the impact of the 

satellite based products for a variety of practical hydrological applications and to identify areas, for 

which the future operational H-SAF products are most beneficial. This condition is necessary to support 

the request for a possible follow-on Operational Phase. 

The Development Phase, in addition to including the activities for developing and generating new 

satellite-derived products, includes a Hydrology validation programme, performed by “Cluster-4”, lead 

by Poland (see Table 1). Cluster-4 is responsible of impact assessment independent of the activity of 

Clusters 1 to 3. Fig. 1 illustrates the logic of the Hydrology validation programme, that should not be 

confused with the “product” calibration/validation activities integral part of products development and 

routine generation. 

The figure shows that the main activities of Cluster-4 are: 

a. adaptation of the observed or forecast products from Clusters 1 to 3 to the local situation by 

downscaling/upscaling operations and area averaging; 

b. merging satellite-derived data with ground observations, punctual (raingauges) or remote-sensing 

(radar), possibly supported by GIS (Geographical Information System); 

c. development of algorithms and models to perform activities a. e b.; 

d. use of satellite data for campaigns over test sites intended to: 

- add to the product validation activity performed contextually with product development, 

- scientifically assess the impact of the new data on practical hydrological application; 

e. provide feedback to Cluster 1 to 3 for possibly improving data quality and, in so doing, also reassess 

user requirements for hydrology; 

f. establish user operational structures in Europe to optimally exploit H-SAF products.


Fig. 1 - Concept of the hydrological validation Cluster and its relation to Clusters 1 to 3. 

Several Countries and Units in Countries participate to the Hydrology validation programme. Fig. 2 

shows, in red colour, the coverage interested by test catchments. 

Fig. 2 - Countries involved in impact studies / validation of satellite products with use of hydrological models.


2.5 The general architectural concept 

The H-SAF architecture is based on: 

• data production centres (in Italy, Austria + ECMWF, Finland + Turkey), that: 

- acquire satellite data via direct reception or EUMETCast 

- generate the H-SAF products also with support from local databases, products from other SAF’s, 

locally available ancillary data, NWP products and climatology; 

• existing dedicated communication networks (regional branches of the Global Telecommunication 

System) for immediate dissemination of products versus operational end-users such as hydrometeorological 

services and Civil Protection units; and/or the alternative dissemination system based 

on connection with EUMETSAT for re-distribution via EUMETCast; 

• a structure for product dissemination to the H-SAF units in charge of the Hydrological validation 

programme and other scientific institutes, based on an H-SAF archive connected to the EUMETSAT 

U-MARF via a client. 

Fig. 3 shows the general concept of the H-SAF architecture. 

PROCESSING 

SCIENTIFIC 

USERS 

INPUT DATA 

Satellites by 

direct read-out 

Satellites via 

EUMETCast 

Local 

databases 

Products from 

other SAF’s 

Ancillary data 

locally available 

NWP products 

and climatology 

Various links 

Coordination 

ITALY as Host 

Precipitation 

products observed 

and forecast 

ITALY 

Soil moisture 

at surface layer 

AUSTRIA 

Soil moisture 

in roots region 

ECMWF 

Snow parameters 

in flat land, forests 

FINLAND 


in mountain areas 

TURKEY 

EUMETSAT area 

EUMETCast 

H-SAF 

Archive 

U-MARF Client 

U-MARF 

Dedicated links 

Institutes in 

charge of 

hydrological 

validation 

(led by POLAND) 

Other R&D 

Institutes 

OPERATIONAL 

END-USERS 

Operational 

hydro services 

Civil Protection 

operational units 

Meteorological 

services 

Fig. 3 - Sketch system architecture of H-SAF. 

2.6 The stepwise development approach 

Generally, the Development Phase of a SAF lasts five years, and the products are demonstrated at the 

end of the 5 years. In the case of H-SAF, the real demonstration of the usefulness of the products is 

executed by the Hydrological validation programme, that constitutes a long-lasting activity. It is 

therefore necessary to anticipate as much as possible the dissemination of certain products so as to 

activate the Hydrological validation programme early enough. Products for early dissemination will not 

have the quality that is expected to be possible at the end of the five years, but will be representative of 

operational characteristics.


Meanwhile, development will continue to gradually improve the quality of the products. The logic of 

the H-SAF Development Phase is shown in Fig. 4. The “green” boxes indicate activities that can be 

implemented in a relatively short time (nominally 2 years) based on available systems and consolidated 

methodologies, i.e. in a pre-operational fashion. The purpose of these activities is to provide as early as 

possible input data for the hydrological assessment programme (“red” box), so that within the follow-on 

3 years enough confidence is acquired about the value of satellite data for operational hydrology and 

water resource management. The “blue” boxes represent activities that are aimed at improving the 

quality of the retrieved data. They imply waiting for the availability of certain satellites or instrument 

(e.g., MetOp until end 2006), or developing the processing methods for instruments only recently 

become available (e.g., SSMIS and AMSR-E). 

Development 

work for improved 

precipitation data 

quality 

Development 


soil moisture data 

quality 

Development 


snow data quality 

Routine 

production of 

precipitation data 

for systematic 

value assessment 

Development 


data assimilation 

schemes 

Routine 

production of soil 

moisture data for 

systematic value 

assessment 

Routine 

production of 

snow data for 

systematic value 

assessment 

Quantitative 

Precipitation 

Forecast 

Measured 

precipitation 

Computed 

precipitation 

Measured soil 

moisture 

Measured snow 

parameters 

Assessment programme to evaluate the benefit of satellite-derived precipitation, soil moisture 

and snow information in European hydrology and water resource management 

Fig. 4 - Logic of the H-SAF Development Phase. 

The improvements will smoothly be transferred to the pre-operational chain. The final users will not 

have direct visibility of these internal developments, except that, hopefully, the data quality will 

gradually improve. 

The “yellow” box, with its associated “golden” development module, indicates the activity intended to 

provide users with “friendly” information. In fact, user (hydrological) models are generally designed to 

be initialised at specific times of the day by input fields represented by values in geographically fixed


grid points. Satellite data (except those from GEO) are spread in time (“a-synchronous”) and refer to 

scattered geographical locations. In addition, certain satellite-derived data may be more accurate if 

radiance data or brightness temperatures or backscatter coefficients are directly assimilated, without 

undergoing the (often ill-conditioned) retrieval process. 

The “red” box indicates the core activity of satellite data value assessment for hydrological applications. 

Fig. 4 shows that, in addition to the direct satellite measurements, the user will also have available the 

computed fields resulting from a NWP model. As a matter of fact, the computed fields will be anyway 

available, also in the absence of satellite measurements, therefore the users will be able to run their 

models with and without satellites. This will encourage users to run their models systematically, 

independently of the evolution of the satellite product generation chain. The value of satellites data will 

need to be assessed both as ingredients of the numerical assimilation process, and as direct 

measurements. The impact assessment programme will need to be carefully designed, so as to enable a 

genuine assessment of the added value of the new measurements to be generated by H-SAF. 

The initial part of the Development Phase will aim at providing as soon as possible a regular set of 

products enabling the Hydrological validation programme to start. This first set of products will be 

ready by the Critical Design Review (CDR) at approximately T 0 + 24 months. In parallel with the 

evaluation of the first set of products (“demonstrational”), a R&D programme will be run, enabling to 

extend the set of deliverable products, improve product quality, achieve a “pre-operational” status, and 

make progress until the delivery of the last “operational” release to be handed over to the Operational 

Phase at the end of the fifth year. Before releasing the set of demonstrational products at T 0 + 24, 

certain prototype products will be distributed, not on a regular basis, and not validated, for the purpose 

of the users get familiar at least with general product aspects, formats and coding. 

Fig. 5 shows the logic of the incremental development scheme. The figure emphasises that early release 

of demonstrational products enables End-users to provide feedback for products improvement. 

Initial 

databases 

Current 

instruments 

Augmented 

databases 

New 

instruments 

Baseline 

algorithms 

Cal/val 

programme 

Advanced 

algorithms 

Prototyping 

1 st release 2 nd release Final release 

Prototypes 

Special 

distribution 

Products 

in development 

Limited distribution 

(to beta users) 

Demonstrational 

products 

Progressively 

open distribution 

Pre-operational 

products 

Open 

distribution 

End-user 

feedback 

Operational 

products 

Open 

distribution 

Representative End-users and Hydrological validation programme 

Fig. 1 - Logic of the incremental development scheme.


The End-users (both the operational services and the scientific institutes in charge of the Hydrological 

validation programme) will not have direct visibility of the R&D activity, except that, with successive 

releases, the product quality will improve and/or new products could be introduced. As shown in Fig. 5, 

the elements of the R&D programme could be: 

• augmented database of the a-priori information supporting the retrieval algorithm; 

• the results of calibration/validation programme (continuous through the whole project); 

• introduction of advanced radiative transfer models or retrieval algorithms; 

• availability of new satellites or instruments (a number will come into service during 2005-2010); 

• feed back from End-users, particularly the Hydrological validation programme. 

2.7 The Work Breakdown Structure 

The first two levels of the Work Breakdown Structure (WBS) are shown in WBS-01. 

EUMETSAT Satellite Application Facility in Support to Operational Hydrology and Water Management (H-SAF) 

WP-1000 

Coordination 

Italy 

WP-1100 

Management 

WP-1200 

Data service 

WP-1300 

Engineering 

WP-2000 WP-3000 WP-4000 WP-5000 WP-5100 

Precipitation Soil moisture Snow parameters Hydro validation Products training 

Italy Austria Finland Poland Poland + Several 

WP-2100 WP-3100 WP-4100 WP-5200 WP-5300 

Observation Surface Flat lands, forests Impact study 1 Impact study 2 

Italy Austria Finland Belgium Finland 

WP-2200 WP-3200 WP-4200 WP-5400 WP-5500 

Computation Roots Mountains Impact study 3 Impact study 4 

Italy ECMWF Turkey France Germany 

WP-2300 WP-3300 WP-4300 WP-5600 WP- 5700 

Product validation Product validation Product validation Impact study 5 Impact study 6 

Italy + Several Austria + Several Finland + Several Italy Poland 

WP- 2400 WP- 3400 WP- 4400 WP- 5800 WP- 5900 

Developments Developments Developments Impact study 7 Impact study 8 

Italy + Several Austria + Several Finland + Several Slovakia Turkey 

WBS-01 - First two levels of the H-SAF WBS. 

The principles of the WBS are as follows: 

• the “core” tasks of generating new observational products are assigned to Italy for precipitation, 

Austria for soil moisture, and Finland for snow parameters (with support from Turkey); 

• the tasks of generating computed products are assigned to Italy and ECMWF; 

• the product validation tasks and the development tasks are spread among several countries in 

addition to those providing the pre-operational service; 

• the hydrological validation programme, though internally coordinated (by Poland), will in effect 

consist of a series of experiments performed in several countries according to local hydrological 

situations and needs;


• Austria, Finland and Italy support the hydrological validation programme by education and training. 

This WBS simplifies the management aspects in so far as most WP’s are assigned to a single 

responsible country. Only validation and developments are based on a collection of contributions. Of 

course, WBS-01 only represents a top-level WBS (only the first two levels, whereas each WP will in 

effect have a more detailed structure, to be deployed in the next Chapters of this Project Plan). 

In Table 4 the undertakings of each Country are listed with regard to WP’s up to the 3 rd level, not shown 

in WBS-01. The added information in respect of WBS-01, apart from the 3 rd level WP’s, regards the 

WP’s assigned to “Several”, that now are specified. They are those of the families: Products validation 

(WP’s 2300, 3300 and 4300), Products development (WP’s 2400, 3400 and 4400) and Education & 

Training (WP-5100). 

Table 4 should be used according to the following explanations: 

• 1 st level WP’s (1000, 2000, 3000, 4000, 5000) - coordination tasks of the project (WP-1000) or of a 

Cluster. An exhaustive description is provided in the Main text and a compact WPD (Work Package 

Description) is provided in Appendix; 

• 2 nd level WP’s (xy00) - supervision task of a set of technical activities. An exhaustive description is 

provided in the Main text and a compact WPD is provided in Appendix; 

• 3 rd level WP’s (xyz0) - “z” technical WP’s connected under xy00. An exhaustive description is 

provided in the Main text and a somewhat articulated WPD is provided in Appendix. 

4 th level WP’s (xyzw) are mentioned in the Main text, but dedicated WPD’s are not included in 

Appendix. The 4 th level WP’s are described as “tasks” in the body of the 3 rd level WPD’s (this is the 

reason why they are much more articulated than the WPD’s of 1 st and 2 nd level, basically frameworks. 

5 th level WP’s could be defined by individual partners for internal reasons, but will not be recorded in 

this Project Plan. 

The WPD’s will identify the name of the responsible person in the Institute, and closely associate work 

progress and deliverables to the envisaged verification events. In addition to the collection of WPD’s, 

the Appendix provides the list of deliverable and their relationship with the official documentation.


No. 

Table 4 - List of undertakings of each Country split by WP up to the 3 rd level - Also list of WPD’s 

Country 

WP-1000 WP-2000 WP-3000 WP-4000 WP-5000 

Lev 1 Lev 2 Lev 3 Lev 1 Lev 2 Lev 3 Lev 1 Lev 2 Lev 3 Lev 1 Lev 2 Lev 3 Lev 1 Lev 2 Lev 3 

3110 

3100 3120 

3130 

01 Austria 3000 

3300 3310 

3320 

3400 3410 

3420 

02 Belgium 2320 3330 4320 5200 

03 ECMWF 2450 

3200 3210 

3220 

3340 

3430 

04 Finland 4000 

4100 

4300 

4400 

4110 

4120 

4130 

4310 

4330 

4410 

4440 

4450 

4470 

5110 

5210 

5220 

5230 

5120 

5300 5310 

5320 

3350 

5410 

05 France 

5420 

3440 5400 5430 

5440 

06 Germany 2330 4340 5500 5510 

5520 

07 Hungary 2340 

08 Italy 

1100 

1200 

1300 

1110 

1120 

1130 

1140 

1210 

1220 

1230 

1240 

1310 

1320 

1330 

1340 

2110 

2100 2120 

2130 

2200 2210 

2220 

2310 

2300 2350 

2360 

2410 

2420 

2400 

2430 

2440 

09 Poland 2370 4350 5000 

10 Romania 4430 

11 Slovakia 2380 5800 

12 Turkey 2390 

4200 

4210 

4220 

4230 

4360 

4420 

4460 

4480 

5600 

5100 

5700 

5900 

5130 

5610 

5620 

5630 

5640 

5700 

5720 

5730 

5740 

5810 

5820 

5830 

5840 

5850 

5860 

5910 

5920 

5930 

5940 

5950 

5960


2.8 The management structure 

The management components involved by H-SAF are based on the general management rules given by 

EUMETSAT, summarised in Table 5. 

EUMETSAT level 

H-SAF level 

Table 5 - Management components of H-SAF 

SAF Project manager 

SAF network support team 

Designated members of EUMETSAT delegate bodies 

Steering Group 

Project Team 

Focal points nominated by the participating Countries 

The project top-level management scheme, descending from WBS-01, is shown in Fig. 6. 

Director of the Host Institute 

and Chairman of the Steering Group 

Massimo Capaldo 

Italian Meteorological Service 

Project manager 

and Chairman of the Project Team 

Roberto Sorani 

Italian Department of Civil Protection 

Project Scientist 

Luigi De Leonibus 

Italian Meteorological Service 

Coordinator of Cluster-1 

Precipitation 

Francesco Zauli 

Italy (CNMCA) 


Soil moisture 

Alexander Jann 

Austria (ZAMG) 



Jouni Pulliainen 

Finland (FMI) 


Hydrological validation 

Bozena Lapeta 

Poland (IMWM) 

Fig. 6 - Top-level management structure of H-SAF. 

The composition of the Steering Group is recorded in Table 6. It is noted that, for efficiency reasons, 

only the four Cluster responsibles, plus ECMWF and Turkey, that share the task of generating “core” 

products, are directly represented at meetings, whereas the other Countries are represented through the 

leader(s) of the Cluster(s) in which they take part. 

Table 6 - Composition of the Steering Group as of end-2007 

No. Country SG Member or contact Institute or role If Contact, represented by: 

01 Austria Veronica ZWATZ-MEISE ZAMG 

02 Belgium Contact: Emmanuel ROULIN IRM Italy or Poland 

03 ECMWF Philippe BOUGEAULT ECMWF 

04 Finland Jarkko KOSKINEN FMI 

05 France Contact: Jean-Christophe CALVET Météo France Austria or Poland 

06 Germany Contact: Thomas MAURER BfG Italy or Finland or Poland 

07 Hungary Contact: Eszter LABO HMS Italy 

08 Italy Massimo CAPALDO USAM 

09 Poland Piotr STRUZIK IMWM 

10 Romania Contact: Andrea DIAMANDI NMA Finland 

11 Slovakia Contact: Jan KANAK SHMU Italy or Poland 

12 Turkey Fath DEMIR TSMS 

EUMETSAT Lorenzo SARLO SAF Network Manager 

EUMETSAT Jochen GRANDEL Met Division 

EUMETSAT Stefan NILSSON STG-AFG Representative 

Italy Roberto SORANI DPC, Project Manager 

Italy Luigi DE LEONIBUS CNMCA, Project Scientist 

Italy Bizzarro BIZZARRI ISAC, Planning Officer 

Italy Flavio GATTARI Datamat, Head Engineer


The Steering Group supervises the progress of the SAF Development and provides guidelines to ensure 

that the SAF objectives are met, and that a proper coordination of technical, financial and 

scientific/meteorological/hydrological aspects is performed. 

The H-SAF Steering Group is the programmatic authority that may decide on changes of the project 

planning as well as the corresponding adjustment of the payment plan. 

The SAF Project Team is the executive body of the Steering Group. It is chaired by the Project 

Manager, who also serves as Executive Secretary of the Steering Group. The composition of the Project 

Team reflects that one of the Steering Group, i.e. the nominal members are from Italy, Austria, Finland, 

Poland, ECMWF and Turkey. However, attendance to Project Team meetings is open to supporting 

experts from both inside and outside the Consortium, as appropriate. 

The H-SAF Project Scientist coordinates the scientific aspects of the H-SAF activities, including 

management of the Visiting Scientist programme and possible inter-SAF collaborations. 

Possible conflicts that could arise in the course of the Development Phase will be solved, in priority 

level of attempt: 

• by the Cluster leader, if internal to one Cluster 

• by the Project Team if the conflict is across Clusters or it was not possible to solve it at Cluster level 

• by the Steering Group in case of lack of solution at lower level. 

2.9 Programme schedule, Review meetings, documentation 

As mentioned, this Project Plan is intended to provide forecast of which user requirement can be met at 

specific points in time during the project (thus to provide input to the User Requirements Document) 

and to constitute a tool for monitoring work progress. Therefore, the work programme must be solidly 

anchored to the verification points along the Development Phase. The verification points and their 

relevance are recorded in Table 7, and follow the Review meetings structure. 

Table 7 - Events providing anchor points for the work schedule 

EVENT 

Date 

KOM Kick Off Meeting T0 + 00 Start of the Project - Start of Phase 1 (Preparatory phase). 

RR Requirements Review T0 + 06 Version 1.0 of this Project Plan and of the URD approved. 

PDR Preliminary Design Review T0 + 12 

All problems relative to satellite data acquisition and availability of baseline 

processing methods should be cleared. Prototype products should be 

available for early evaluation. 

WS-1 1 st Workshop T0 + 18 

Consolidated products definition, including: 

- Precipitation products 

- Soil moisture products 

- Snow products 

- Calibration/validation plan 

- Hydrological validation plan. 

CDR Critical Design Review T0 + 24 

Phase 1 Report, including: 

- Status of the product generation chains 

- Status of preparation of demonstrational products 

- Status of valisation activities 

- Status of preparation of the Hydrological validation programme. 

Approval of PP-2.0, URD-2.0, ATDD-1.0. 

Authorisation to release demonstrational products. 

Start of Phase 2 (Demonstration phase). 

SIRR System Integration Readiness Review T0 + 36 

Evaluation of the results of the product validation activity. 

Evaluation of early results of the Hydrological validation programme. 

STRR System Test Results Review T0 + 42 Authorisation to release pre-operational products. 

WS-2 2 nd Workshop T0 + 48 

Preliminary results of the Hydrological validation programme. 

Release of recommendations for products tuning/improving. 

SVRR System Validation Results Review T0 + 54 

Consolidation and evaluation of results from impact studies. 

Consolidation of products and their characterisation from validation. 

Definition of the proposal for a possible Operational Phase. 

ORR Operations Readiness Review T0 + 60 

Demonstration of the final operational version of the products. 

End of the H-SAF Development Phase.


Associated to the Review meetings, programmatic, scientific and technical documentation must be 

submitted to the Review Boards. Table 8 lists the documents to be submitted to the Review meetings. 

Table 8 - List of deliverable documents for the Review meetings and the Workshops 

Event Time Document Status 

KOM Kick Off Meeting T0 + 00 N/A Start of Phase 1 (Preparatory phase) N/A 

RR 

PDR 

WS-1 

CDR 

SIRR 

Requirements Review 

Preliminary Design Review 

1 st Workshop 

Critical Design Review 

System Integration 

Readiness Review 

(internal) 

T0 + 06 

(actual: 

T0 + 07) 

T0 + 12 

(actual: 

T0 + 15) 

T0 + 18 

(actual: 

T0 + 25) 

T0 + 24 

(actual: 

T0 + 27 

for science. 

T0 + 29 for 

engineering) 

T0 + 36 

STRR System Test Results Review T0 + 42 

PP-1.0 Project Plan Baseline 

URD-1.0 User Requirements Document Baseline 

CMP-0.5 Configuration Management Plan Preliminary 

SRD-0.5 System Requirements Document Preliminary 

SDD-0.5 System Design Document (Concept Design) Preliminary 

ATDD-0.5 Algorithms Theoretical Definition Document Preliminary 

CMP-1.0 Configuration Management Plan Baseline 

SRD-1.0 System Requirements Document Baseline 

SDD-1.0 System Design Document Baseline 

SIVVP-0.5 System Integration, Verification & Validation Plan Preliminary 

CRD-0.5 Component Requirement Document Preliminary 

CDD-0.5 Component Design Document Preliminary 

CVERF-0.5 Component Verification File Preliminary 

ICD-0.5 Interface Control Document Preliminary 

REP-1.0 

Consolidated products definition, including: 

- Precipitation products 

- Soil moisture products 

- Snow products 

Preliminary results of products validation 

Hydrological validation plan 

Rolling (internal) 

from RR to WS-1 

PP-2.0 Project Plan Update 

URD-2.0 User Requirements Document Update 

ATDD-1.0 Algorithms Theoretical Definition Document Baseline 

REP-2.0 

Phase 1 Report, including: 

- Status of preparation of H-SAF products 

- Status of product validation activities 

Status report 

- Status of preparation of hydrological validation 

SRD-2.0 System Requirements Document Update 

SDD-2.0 System Design Document Update 

SIVVP-1.0 System Integration, Verification & Validation Plan Baseline 

SVERF-0.5 System Verification File Preliminary 

SSVD-0.5 System/Software Version Document Preliminary 

CRD-1.0 Component Requirement Document Baseline 

CDD-1.0 Component Design Document Baseline 

CVERF-1.0 Component Verification File Baseline 

ICD-1.0 Interface Control Document Baseline 

N/A Start of Phase 2 (Demonstration phase) N/A 

ATDD-2.0 Algorithms Theoretical Definition Document Update 

REP-3 Status of product validation activities Rolling (internal) 

REP-4 Status of hydrological validation activities from CDR to ORR 

SSVD-1.0 System/Software Version Document Baseline 

SVERF-0.6 System Verification File Preliminary 

CDD-2.0 Component Design Document Update 

CVERF-2.0 Component Verification File Update 

PPR-1.0 Products Prototyping Reports Baseline 

DOF-1.0 Data Output Format Baseline 

URD-3.0 User Requirements Document Update 

REP-5 Status of preparation of pre-operational products Status report 

SVALF-0.5 System Validation File Preliminary 

SVERF-1.0 System Verification File Baseline 

PPR-2.0 Products Prototyping Reports Update 

WS-2 2 nd Workshop T0 + 48 REP-4 Status of hydrological validation activities Rolling (internal) 

SVALF-1.0 System Validation File Baseline 

SVRR 

System Validation Results 

DOF-2.0 Data Output Format Update 

T0 + 54 

Review 

UM-0.5 User Manual Draft 

FR-0.5 Final Report Draft 

UM-1.0 User Manual Baseline 

ORR Operations Readiness Review T0 + 60 FR-1.0 Final Report Baseline 

N/A End of the H-SAF Development phase N/A


The official documents for the ORR (User Manual and Final Report) will include: 

• User Manual: 

- essential product descriptions (reasons for the product, sensing principle) 

- main sensor features controlling product geometry and accuracy 

- information for data access and handling (dissemination means, format, coding, schedule) 

- information on data quality (resolution, observing cycle, timeliness, accuracy / error structure) 

- description of user services (archive, web site, help desk); 

• Final Report: 

- description of the final system architecture and configuration 

- summary description of products basis, algorithm and development phases 

- summary report of products validation activities and results 

- summary report of hydrological validation results and benefit assessment. 

Bakground documents for the ORR will be: 

• the latest version of ATDD (presumably, ATDD-2.0 or some minor update); 

• the final issue of the rolling internal document REP-3 (H-SAF Products Validation Report); 

• the final issue of the rolling internal document REP-4 (H-SAF Hydrological Validation Report). 

A synoptic view of the evolution of the various documents is provided in Table 9. Minutes of meetings 

and Reviews, and progress reports in between meetings are not listed. 

Table 9 - Evolution of documents supporting meetings and Workshops 

No. Deliverable document RR PDR WS-1 CDR SIRR STRR WS-2 SVRR ORR 

D-01 PP Project Plan 1.0 2.0 

D-02 URD User Requirements Document 1.0 2.0 

D-03 ATDD Algorithms Theoretical Definition Document 0.5 1.0 2.0 

D-04 CMP Configuration Management Plan 0.5 1.0 

D-05 SRD System Requirements Document 0.5 1.0 2.0 

D-06 SDD System Design Document 0.5 1.0 2.0 

D-07 SIVVP System IV & V Plan 0.5 1.0 

D-08 SSVD System/Software Version Description 0.5 1.0 

D-09 SVERF System Verification File 0.5 0.6 1.0 

D-10 SVALF System Validation File 0.5 1.0 

D-11 CRD Component Requirement Document 0.5 1.0 

D-12 CDD Component Design Document 0.5 1.0 2.0 

D-13 CVERF Component Verification File 0.5 1.0 2.0 

D-14 ICD Interface Control Document 0.5 1.0 

D-15 PPR Products Prototyping Reports 1.0 2.0 

D-16 DOF Data Output Format 1.0 2.0 

D-17 REP-1 Report to the 1 st H-SAF Workshop (rolling) X 

D-18 REP-2 H-SAF Phase-1 Report X 

D-19 REP-3 H-SAF Products Validation Report (rolling) X X 

D-20 REP-4 H-SAF Hydrological Validation Report (rolling) X X X 

D-21 REP-5 Status of preparation of pre-operational products X 

D-22 UM User Manual 0.5 1.0 

D-23 FR Final Report 0.5 1.0 

The calendar of meetings/Reviews may be adapted to need. For instance, in preparation of the Critical 

Design Review (at T 0 + 24) due to authorise the release of demonstrational products, a “Version-1 

Check Point” (V1CP, not in Table 8) was organised 4 months in advance. Another variation to Table 8 

is that the CDR has been split in two sessions, a scientific-oriented one to analyse documents REP-2, 

PP-2.0, URD-2.0 and ATDD-1.0; and an engineering-oriented one for the remaining documents. 

Steering Group meetings take place at roughly 6-month intervals, generally following a Review 

meeting. Project Team meetings are generally organised some month before an SG meeting. 

Specialised meetings, for instance to coordinate product validation activities or hydrological validation 

activities, or for Education & Training, are organised at occasions.

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 3 (The coordination task) Page 37 

3. The Coordination task (WP-1000) 

3.1 Introduction 

The Coordination task implies the ordinary management activities and also the technical structure for 

monitoring data distribution and feedback from users, and for complying with engineering standards 

throughout the various components of H-SAF. Thus, there are three components, or “Level-2” WP’s: 

• WP-1100: Management 

• WP-1200: Data Service 

• WP-1300: Engineering. 

The Work Breakdown Structure of WP-1000 is deployed in WBS-02. The activity is based on three 2 nd 

level WP’s that will be described below. Work Package Description sheets (WPD’s) are provided in 

Appendix. It is noted that WBS-02 only extends to Level-3 (i.e. WP-1xy0). 

WP-1000 

Coordination 

Italy (USAM) 

WP-1100 

Management 

DPC 

WP-1110 

Technical management 

DPC 

WP-1120 

Science management 

CNMCA 

WP-1130 

Administration & finance 

USAM 

WP-1140 

Planning and editing 

ISAC 

WP-1200 

Data service 

CNMCA 

WP-1210 

H-SAF archive development 

CNMCA 

WP-1220 

Dissemination links 

CNMCA 

WP-1230 

Reports collection & analysis 

CNMCA 

WP-1240 

Web site and Help desk 

CNMCA 

WP-1300 

Engineering 

CNMCA / Datamat 

WP-1310 

Detailed system architecture 


WP-1320 

Engineering standards 


WP-1330 

Engineering documentation 

Datamat 

WP-1340 

Control functions & support to PT 

DPC / Datamat 

WBS-02 - WBS of WP-1000: 1 st , 2 nd and 3 rd level WP’s. No 4 th level WP’s defined. 

3.2 The management task (WP-1100) 

The responsibility of H-SAF Management is shared between USAM and DPC. The DPC provides the 

technical management, the USAM the science management and the administrative services. Support for 

planning and editing of the science-oriented documentation is provided by CNR-ISAC. 

WP-1110: Technical management 

WP-1110 provides the H-SAF Development Phase with the Project Manager, also responsible of the 

overall WP-1100. Major objectives: 

• to coordinate the H-SAF technical work through the Project Team; 

• to support the Steering Group; 

• to ensure implementation of the Project Plan; 

• to manage the User Requirements Document (URD).


The project management task is coordinated with WP-1120 (Science Management) and WP-1130 

(Administration & Finance), and supported by WP-1140 (Planning and editing); and reports to the top 

authority of the Host Institute (WP-1000). 

In order to ensure the implementation of the Project Plan, the Project Manager: 

• coordinates and chair the Project Team, that implies: 

- to entertain working relationships with the sectorial project teams of the individual Clusters; 

- to call meetings of the Project Team whenever needed to establish working agreements; 

- to prepare Review meetings and Steering Group meetings; 

• collects reports of WP-1200 (Data service) and processes the results by addressing the various cases 

to the appropriate unit, for technical actions (Project Team) or programmatic/policy issues (Steering 

Group); 

• cares that the output of WP-1300 (Engineering), e.g. about engineering standards, is applied in all 

appropriate environments (generally through agreements in the Project Team). 

In order to ensure management of the URD, the Project Manager shall: 

• monitor that, as the project evolves, the achieved results comply with the URD; 

• in case of discrepancies, the Project Manager, through the Project Team, adjusts the Project Plan 

(within limits) so as to bring the results to comply with the URD; 

• in the case that it is not possible to comply with the URD by small adaptations of the Project Plan, 

the Project Manager will submit proposal to the Steering Group for: 

- either modify the Project Plan, 

- or update the User Requirements Document. 

In support of the Steering Group, the Project Manager: 

• acts as Executive Secretary, that implies: 

- meetings organisation; 

- preparation of working papers to make meetings more effective; 

- reporting on behalf of the Project Team; 

- provision of secretarial services; 

- processing results and ensuring that decisions are implemented; 

• facilitates the Review meetings process by: 

- timely delivering of the official documents to the members of the Review Board; 

- ensuring that any deliberation of the Review Board is rapidly processed. 

With respect to EUMETSAT, the Project Manager: 

• acts as ordinary contact point for most H-SAF aspects, having regard to: 

- the responsibilities of the Project Scientist (see WP-1120), particularly in respect of processing 

methodology assessment, compliance of data quality with User Requirements and management 

of the Visiting Scientist programme; 

- the ultimate responsibility of the Director of the Host Institute (WP-1000) for programmatic or 

policy issues, and as Chairman of the H-SAF Steering Group. 

The Project Manager supports the Administration of the Host Institute (WP-1130) by providing input 

such as technical assessment of compliance of the work carried out by the Operating Units of H-SAF in 

respect of the Project Plan and the User Requirement Document. 

WP-1120: Science management 

The H-SAF work programme couples an activity finalised to generate products at established dates for 

hydrological evaluation activities, and a parallel continuous development for progressive product quality 

improvement. The objectives of WP-1120, that is led by the Project Scientist, are: 

• to monitor the scientific aspects of the H-SAF Development Phase; 

• to ensure that the quality of H-SAF products is consistent with the stated User Requirements.


The scientific management task is coordinated with WP-1110 (Project Management) in such a way that 

the scientific assessment processes (upstream and downstream of product generation) can be run 

somewhat decoupled from the intensive daily management of the activities run to implement the Project 

Plan. The Project Scientist cares that: 

• envisaged processing models, cal/val activities and implementation schemes are consistent with the 

claimed performances in terms of expected data quality (this is an upstream activity); 

• prototype products, cal/val reports and, later, hydrological validation exercises, are analysed vis-àvis 

the User Requirements Document (this is a downstream activity). 

The Project Scientist is responsible of the Visiting Scientist programme. In this respect: 

• prepares and supports Steering Group decisions on the Visiting Scientist programme 

implementation by preparing the plan and reporting on achievements; 

• monitors the results of the visiting scientists’ work through the concerned Cluster leaders and 

provides input to the H-SAF unit that provides administrative service to the Visiting Scientist 

programme (Austria-ZAMG). 

The Project Scientist has special responsibility in respect of: 

• identifying opportunities of collaboration with other SAF’s; a list of possibilities to be explored is: 

- with NWC-SAF: use of software packages for clouds and precipitation products in support of H- 

SAF retrieval of precipitation rate; 

- with LSA-SAF: use of soil moisture indexes from optical instruments in support of H-SAF soil 

moisture retrieval, and cross-use between products from MW and optical instruments; also 

synergy for snow cover retrieval and cal/val; 

- with CLI-SAF: synergy for long-term cal/val and climatic use of H-SAF products; 

- with NWP-SAF: assimilation of H-SAF precipitation data for improved Quantitative 

Precipitation Forecasting; also replacement of American modules by European ones in the 

precipitation retrieval software; 

• preparing smooth transition from the H-SAF Development Phase to a possible Operational Phase 

through the mechanism of the Continuous Development Operations Phase (CDOP); 

• collecting reports from H-SAF Operating Units on activities correlated with GMES (Global 

Monitoring for Environment and Security) and preparing syntheses for the Steering Group. 

The ordinary vehicle for the Project Scientist activity, both to acquire the information and to indicate 

potential problems, are the Project Manager and the Project Team (of which he is member). Direct 

reporting to the Steering Group occurs for the Visiting Scientist programme and for scientific aspects 

such as statements on data quality in respect to the User Requirements. 

Further participants to WP-1120 are: the DPC to cover validation and hydrological aspects, and CNR- 

ISAC to cover developments at large. 

WP-1130: Administration and finance 

WP-1130 is responsible of managing the EUMETSAT contribution. The work of the Administrative 

Officer is supported by WP-1110 and WP-1120 for technical endorsement. 

In respect of managing the EUMETSAT contribution to the technical activities: 

• invoices are collected by the Host Institute from the H-SAF Operating Units entitled to get the 

EUMETSAT contribution, and conveyed to EUMETSAT for direct payment; 

• the collected invoices are delivered to EUMETSAT after: 

- endorsement by the responsible Cluster leader; 

- endorsement by the Project Manager. 

In respect of the Visiting Scientist programme, the EUMETSAT contribution is deposited at yearly 

intervals (November each year) with Austria-ZAMG. Payments are performed by ZAMG after:


• the invoices are collected by the Host Institute from the H-SAF Operating Unit employing the 

Visiting Scientist; 

• the collected invoices are delivered to Austria after: 

- endorsement by the responsible Cluster leader; 

- endorsement by the Project Scientist. 

WP-1140: Planning and Editing 

This is a supporting task for the implementation and updating of basic programmatic/scientific 

documents such as (see Tables 8 or 9) (each document to imply several issues for different Reviews): 

• the Project Plan (PP); 

• the User requirements Document (URD) 

• the Algorithm Theoretical Definition Document (ATDD) 

• the series of Reports (REP) on specific items, and Workshop proceedings 

• the User Manual (UM) and the Final Report (FR). 

These documents, especially the URD, come upstream of the engineering documentation, produced 

under WP-1330. The Planning Officer, on the base of the Development Proposal [Ref. 2] and previous 

discussions and negotiations [Ref. 1], submits draft documents or document frames to the H-SAF 

Participants, collects the contributions and performs editing of the documents to be delivered to the 

Review meetings. For those documents, he coordinates, appealing to authors of the contributions if 

necessary, the management of the Review Item Discrepancy (RID) associated to Review meetings. 

The Planning Officer has special responsibility for: 

• inputting and maintaining updated the information on the evolution of the space programmes, 

bridging with the WMO Space Programme and the Coordination Group for Meteorological 

Satellites (CGMS); 

• keep record on international progress in the use of satellites for H-SAF purposes, particularly as 

concerns ultimate performances potentially achievable by current and future satellites and 

instruments. 

The Planning Officer supports the Project Manager and the Project Scientist in their function of project 

control under both the viewpoints of Project Plan implementation and consistency of the achieved data 

quality with User Requirements. He supports the Steering Group by focusing, at each meeting, on the 

short-term activity to follow according to the Project Plan. 

3.3 The data service (WP-1200) 

The purpose of WP-1200 is to ensure that the products from H-SAF reach the users, both operational 

and scientific, both in real- or near-real time, and from the archive. Fig. 7, a section of Fig. 3, indicates 

the area addressed by WP-1200. 

The data generated by the production centres (in Italy, Austria, ECMWF, Finland and Turkey) are 

addressed: 

• in real-time directly from the production centres to connected centres. It is noted that the links with 

operational end-users are generally existing in the framework of the operational GTS (Global 

Telecommunication System), either as regional branches or in front of bilateral agreements between 

National Meteorological Centres (NMC’s). The links between the NMC’s and the corresponding 

national units for Civil Protection and operational Hydrology are considered a matter internal to the 

Countries; 

• in near-real time, through CNMCA, to EUMETSAT for distribution by EUMETCast. It is noted 

that the EUMETCast system, though suitable for open distribution, enables selective addressing. 

This will be useful for restricted distribution of experimental products not yet sufficiently validated; 

• invariably to the Central archive operated in Italy by CNMCA; this will be accessible by the 

scientific community through the EUMETSAT U-MARF via a Client.



Archive 

U-MARF Client 


Products 

generation 

centres 

U-MARF 

EUMETSAT area 


Products 

users 

EUMETCast 

Dedicated links 

Fig. 7 - H-SAF central archive and distribution facilities. 

It is reminded that the timeliness performance quoted in Table 2 refers to the distribution through 

EUMETCast. 

The same system developed for data archiving and distribution also supports monitoring tasks, off-line 

data service and help desk. 

The monitoring task includes collection of reports from the addressed users, and the analysis of the 

reports to assess compliance with system performance requirements such timeliness and reliability, and 

to feedback the results of validation reports for products calibration and characterisation. 

WP-1210: H-SAF archive development 

The objective of WP-1210 is to implement the H-SAF archive as: 

• the vehicle to convey data to the scientific user community via the EUMETSAT U-MARF; 

• the tool enabling the Host Institute to monitor the flow of H-SAF products into and outside the 

system. 

The H-SAF central archive will be designed and implemented. This implies: 

• to define the functional and technical requirements of the central archive, specifically the degree of 

physical distribution of its components; 

• to actually implement the central H-SAF archive. 

The H-SAF central archive is the source of data provision to the scientific user community, via 

EUMETSAT. This implies: 

• installation of the U-MARF client to connect with U-MARF in Darmstadt; 

• to test the overall chain, from data production centres to scientific end-users. The participants to the 

H-SAF Hydrology validation programme will serve as benchmarks. 

The H-SAF central archive will have full visibility of all product outputs from H-SAF. In addition: 

• it will support WP-1230 for the collection and analysis of reports from end-users; 

• it will support WP-1240 for providing a help desk service.


WP-1220: Dissemination links 

The purpose of WP-1220 is to ensure that the communication links between H-SAF product sources and 

EUMETSAT Members and cooperating States can support timely and reliable dissemination. 

Whereas WP-1210 addresses scientific users to collect H-SAF products off-line, that implies developing 

a new facility (the H-SAF archive), WP-1220 addresses end-users that need H-SAF products for 

operational use, within the required time limits, ranging from 10 to 20 min and 2 h, depending on the 

product (see Table 2). These figures, valid for the Operational Phase, assume 5 min delay introduced by 

the EUMETCast system (probably more during the Development Phase). Shorter delays require the use 

of dedicated lines. The work implies: 

• estimates of date volumes, data rates and time distribution profiles associated to the various H-SAF 

products; 

• review of the existing connections between the H-SAF production centres and the NMC’s of 

EUMETSAT member and cooperating States, and assessment of their suitability; 

• definition and implementation of possible actions needed for problems solving. 

For prototype products distribution use will be made of the ftp servers of the production centres. 

WP-1230: Reports collection and analysis 

The purpose of WP-1230 is to support the H-SAF performance monitoring function by collecting and 

analysing performance reports from the addressed users, on-line and off-line. 

Two types of utilisations are foreseen: on-line system monitoring and support to products cal/val. 

On-line monitoring has the objective to assess whether what was output from H-SAF has actually been 

received, at which time, and whether the content was sound, so as to check that the system is working 

properly. The work implies: 

• to establish the mechanisms for automatic reporting and the content of the report (time of reception, 

format check, some quick test on message soundness, …); 

• building the database of reports in a specific area of the central archive (see WP-1210). 

• compilation of statistics of delivery times, reception times, dissemination success rates for the 

various production centres, reception success rates for the various addressed users, compliance with 

format and message content specifications, etc.; 

• critical analysis of failures and classification into occasional and structural; 

• study, definition and implementation of problem solutions. 

Specific reports regard the results of validation campaigns. These will be analysed for: 

• supporting on-line quality control before product distribution (for the next deliveries); 

• retrofitting validation results into algorithm and software for improved calibration; 

• characterisation of the error structure of the products. 

The reports collection and analysis function will supported by the central archiving facility (see WP- 

1210). For the initial activities (system build-up and preliminary validation campaigns) use will be 

made of the ftp servers of the participating Institutes. 

WP-1240: Web site and Help desk 

A project Web site will be implemented at the server of CNMCA. It will contain: 

• general public information on H-SAF 

• H-SAF products description 

• rolling information on the H-SAF implementation status 

• an area for collecting/updating information on the status of satellites and instruments used in H-SAF 

• an area to collect E&T material


• areas for “forums” (on algorithms, on validation campaigns, etc.) 

• indication of useful links (specifically with other SAF’s) 

• an area for “Frequently Asked Questions” (FAQ) to alleviate the load on the Help desk. 

The Help desk will complement the web site. First attempt will be to help by e-mail. If not sufficient, 

telephone contacts will be used. The Help desk will be managed by the Satellite Section of CNMCA, 

that could appeal to other Units of H-SAF if necessary. 

3.4 The engineering task (WP-1300) 

The purpose of WP-1300 is to introduce and maintain industrial standard across the whole H-SAF 

architecture. It applies to the whole chain for products generation and dissemination. Although the 

nature of H-SAF is based on providing a service rather than a transportable SW/HW system (thus the 

essential requirements refers to product quality standards), compliance with a number of basic standard 

requirements is necessary for providing EUMETSAT with evidence of system reliability and stability. 

In fact, to demonstrate the feasibility, the quality and the usefulness of the products is only the first 

(indispensable) step for proposing an Operational Phase. The next requirement is that the system can 

become operational without having to re-design it to comply with operational standards. It also should 

be considered that, in the course of the possible Operational Phase, H-SAF will have to periodically be 

updated, for instance when NPOESS and the Global Precipitation Measurement mission (GPM) starts 

operations. If design standards are not established and observed, any update could imply requalification 

of some sub-system 

WP-1310: Detailed system architecture 

The purpose of WP-1310 is to add details to the conceptual H-SAF architecture outlined in the 

Development Proposal to the extent of identifying interfaces, defining system and sub-system 

requirements and ensure smooth flow of all operations. 

WP-1310 will start from the point where the Development Proposal arrived on the issue of architectural 

design and will develop the details until final consolidation of the system concept. The work will imply: 

• critical analysis of the preliminary concept outlined in the Development Proposal; 

• definition of system requirements, deployment of the details, identification of criticalities, definition 

of solutions, risk analysis; 

• definition of a baseline system architecture; 

• iterations on specific problems on the base of actual experience; 

• consolidation of system design. 

WP-1310 will be carried out in close cooperation with the Project Team. 

WP-1320: Engineering standards 

The purpose of WP-1320 is to establish engineering standards to be complied-with across the whole H- 

SAF system so that system credibility can be assessed and risks from changes are minimised. 

Since H-SAF delivers services (products), not SW/HW systems, the centres responsible of products 

generation are not bound to stringent requirements as regards standards and codes, except that the output 

products must comply with agreed coding, formats and protocols. Nonetheless, a minimum of 

standardisation is required to ensure that: 

• programming languages and software environments are used, that: 

- enable EUMETSAT to assess the credibility of the system to perform correctly and to comply 

with stability and reliability requirements; 

- enable smooth replacement of modules without need for re-qualifying system/subsystems; 

- enable smooth transition to a possible Operational Phase without need for substantial redevelopment, 

except possible addition of redundancies to strengthen reliability.


As concerns products, WP-1320 will: 

• establish formats, coding, protocol, etc. in such a mode that: 

- EUMETSAT members and cooperating States can receive the products without the need for 

substantial local development; 

- the products or part of them, depending on the EUMETSAT data policy, can be made available 

on the Global Telecommunication System (GTS); 

- the data structure is possibly the same for all communication modes (dedicated lines, via U- 

MARF, via EUMETCast). 

WP-1320 will be carried out in close cooperation with the Project Team. 

WP-1330: Engineering documentation 

The H-SAF contract with EUMETSAT implies that a number of engineering documents are presented at 

the Review meetings (see Tables 8 and 9), in addition to the programmatic/scientific documents to be 

provided under WP-1140. The list (each document to imply several issues for different Reviews) is: 

• Configuration Management Plan (CMP) 

• System Requirements Document (SRD) 

• Component Requirement Document (CRD) 

• Component Design Document (CDD) 

• Component Verification File (CVERF) 

• Interface Control Document (ICD) 

• System Design Document (SDD) 

• Products Prototyping Reports (PPR) 

• System IV & V Plan (SIVVP) 

• System/Software Version Description (SSVD) 

• System Verification File (SVERF) 

• System Validation File (SVALF) 

• Data Output Format (DOF). 

These documents come downstream of the programmatic/scientific documents produced under WP- 

1140, especially the URD. The Head Engineer submits draft documents or document frames to the H- 

SAF Participants, collects the contributions and performs editing of the documents to be delivered to the 

Review meetings. For those documents, he coordinates, appealing to authors of the contributions if 

necessary, the management of the Review Item Discrepancy (RID) associated to Review meetings. 

WP-1340: Control functions and Support to Project Team 

The purpose of WP-1340 is to support the Project Manager for ensuring configuration control, schedule 

control and documentation control. 

WP-1340 provides the Project Manager with industrial support for: 

• compilation and maintenance of the Configuration Management Plan; 

• configuration management control, that is: 

- configuration item identification in the general H-SAF architecture and its components, defined 

and developed under WP-1310, among which algorithms, models, processing chains, archives, 

telecommunication means (after availability of their description); 

- definition of procedures and guidelines for configuration control of software development, like 

adopted programming languages, coding, standards, protocol, etc. as stated under WP-1320; 

- assessment and supervision of the Configuration Management Control Function delegated to 

each Cluster leader; 

• schedule control of the activities envisaged under this Project Plan, locked to the project milestones; 

• configuration control of all deliverable documents listed under WP-1330 and possible others of 

special impact or prone to provoke updating of one or more official documents.


3.5 Programme schedule of WP-1000 

The diagram below deploys the programme schedule of WP-1000. The scheme, that will be re-used for 

the WP’s relative to the four Clusters, includes mention of 4 th level WP’s that are not present in WP- 

1000. 

LEGENDA 1 st level WP 2 nd level WP 3 rd level WP 4 th level WP 

→ start of 4 th level WP (or 3 rd if 4 th absent) →← end or important milestone of 4 th level WP (or 3 rd if 4 th absent) 

Work programme schedule and project events 

2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

1000 Italy 

1100 Italy 

1110 Italy → → ← 

1120 Italy → → ← 

1130 Italy → → ← 

1140 Italy → → ← 

1200 Italy 

1210 Italy → → ← → ← →← 

1220 Italy → → ← → ← →← 

1230 Italy → → ← → ← 

1240 Italy → → ← 

1300 Italy 

1310 Italy → → ← → ← →← 

1320 Italy → →← → ← → ← 

1330 Italy → → ← 

1340 Italy → → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 4 (The precipitation task) Page 46 

4. The precipitation task (WP-2000) - Cluster-1 


One major challenge of H-SAF is to generate precipitation measurements with unprecedented quality, 

thanks to the operational availability of microwave radiometers such as SSM/I on DMSP, in progress of 

being replaced by SSMIS. In addition to these instruments, specifically designed to measure 

precipitation rate, MW temperature and humidity sounders (AMSU-A and AMSU-B or MHS) on 

NOAA and MetOp satellites also have proven capability of providing information on precipitation, 

specifically useful over land thanks to the utilisation of absorption bands relatively insensitive to surface 

emission that strongly affects SSM/I window channels. The new SSMIS sensor couples window and 

absorption channels for optimal synergy, and is the precursor of the instruments of the future generation 

of meteorological satellites (NPOESS with the advanced MIS microwave radiometer). 

In addition to these operational instruments, others being flown on R&D satellites also are available. 

TRMM is still operating, with its Precipitation Radar (PR) that constitutes the currently unsurpassed 

tool for precipitation modelling and for ‘physical’ calibration of MW radiometers (one, TMI, is coflying 

on the same satellite, that also embarks a Lightning Imaging Sensor, LIS, specifically designed to 

identify convective cloud systems). The AMSR-E onboard EOS-Aqua has unprecedented high 

resolution, and is specifically useful because it measures precipitation at the scale of convective cells 

(up to 5 km), also being a precursor of NPOESS/MIS. In H-SAF, however, these instruments will only 

be used for development and validation of processing schemes, since they might not be available 

through the whole Development Phase (an AMSR-2 instrument could be flown on the Japanese GCOM- 

W series of satellites currently been planned, but not yet fully approved). 

Currently and for a long time to come, MW instruments are only possible to be flown on low orbits. 

Therefore, the observing cycle will in no way be shorter than, say, the 3 h foreseen for the Global 

Precipitation Measurement mission (GPM), that requires 8 satellites in properly de-phased orbits. Subhourly 

cycles as requested for nowcasting and hydrology therefore require help from geostationary 

satellites. For Europe, this is Meteosat that, in the current 2 nd generation (MSG), is equipped with 

SEVIRI that provides VIS/IR images at 15-min intervals. The correlation of optical imagery with 

precipitation is limited to convective clouds and, anyway, qualitative. However, by combining frequent 

IR images from GEO and infrequent MW images from LEO interesting results are achievable. MW 

precipitation measurements can be used to “calibrate” IR radiances in terms of precipitation; or IR 

images can be used to interpolate in between MW measurements (and to extrapolate to a certain extent). 

For nowcasting, this practice is rather satisfactory in so far as a meteorological forecaster (a 

“synoptician”) is used to manage with pattern information of uncertain and discontinue quality. For 

hydrology, interpolation to short time intervals is necessary for the purpose of computing cumulated 

precipitation. In H-SAF it is assumed that, by strongly improving the quality of the basic measurements 

derived from MW imagery, also the quality of merged IR/MW frequent observation will improve. 

Satellite determination of precipitation data is a rather complex exercise. In fact, with the single 

exception of heavy convective precipitation over the ocean, that can be directly measured by lowfrequency 

MW (say, ∼ 10 GHz), precipitation reaching the ground, particularly over land, is a rather 

indirect observation. The main problem is that the vertical structure of the precipitating cloud cannot be 

observed (except by using radar), thus it must be input through some model. Since it is not feasible, 

nowadays, to assimilate in real time satellite data as dense as MW images into Cloud Resolving Models 

(CRM), the only ones capable of providing sufficiently detailed cloud microphysical description as to 

constrain the strongly ill-conditioned retrieval problem, the vertical profiles of cloud microphysical 

structures are pre-computed by a CRM, converted into a radiative pattern by means of a Radiative 

Transfer Model (RTM) and stored in a Cloud-Radiation Database (CRD). The retrieval process 

identifies the most likely profiles in the CRD to constrain the solution by a Bayesian method. The 

effectiveness of this method, that is currently the most advanced in the world, depends on the 

representativeness of the CRD, that will be augmented by collaboration of the partners in Cluster-1.


This procedure applies to conical-scanning radiometers (SSM/I, SSMIS, AMSR-E, MIS) that ensure 

constant incidence angle. For data from cross-track scanners used for temperature/humidity sounding 

(AMSU-A, AMSU-B, MHS), with changing incidence angle across the image, the physical retrieval is 

more complex. Neural network methods are currently used. 

For blending MW data from LEO and IR data from GEO there are two different approaches: either to 

use GEO IR images as primary data, and “calibrate” the equivalent blackbody temperatures into mm/h 

through lookup tables generated by using the most recent LEO MW precipitation measurements; or to 

baseline as primary the (infrequent) LEO MW precipitation measurements and interpolate in between 

them by using the cloud dynamics as shown in the GEO IR image sequences. 

Moving from frequent measurements of precipitation rate from blended IR and MW data, and making 

fusion with ground-based measurements from rain gauges and NWP model output, accumulated 

precipitation is computed. 

In addition to satellite-derived observed data, WP-2000 will also generate computed data. As a matter 

of fact, currently, hydrologists are more used to utilise precipitation fields generated from a NWP model 

than actual data, due to their irregular structure. Satellite data come at times and places associated to the 

occurrence of the orbital passes. To support users by providing a regular input, H-SAF will provide a 

background field generated by a NWP model. The Quantitative Precipitation Forecasting (QPF) module 

will provide precipitation rate and accumulated precipitation at the nominal T 0 time (analysis) and at 

several times ahead. 

WBS-03 displays the structure of WP-2000 up to the 3 rd level WP’s. In this Chapter the work plan will 

be described up to 4 th level. In the Appendix WPD’s are provided for 1 st , 2 nd and 3 rd level WP’s. 

WP-2000 

Precipitation 

Italy (CNMCA) 

WP-2100 

Observed precipitation 

Italy (CNMCA) 

WP-2200 

Computed precipitation 

Italy (CNMCA) 

WP-2300 

Products validation 

Italy + Several 

WP-2400 

Products development 

Italy + Several 

WP-2110 

Acquis. & pre-processing 

CNMCA 

WP-2210 

Q.P.F. 

CNMCA 

WP-2310 

Validation philosophy 

DPC 

WP-2410 

MW conical scanners 

ISAC 

WP-2120 

Products generation 

CNMCA 

WP-2220 

NWP model improvement 

CNMCA 

WP-2320 

Validation in Belgium 

IRM 

WP-2420 

MW cross-track scanners 

ISAC 

WP-2130 

Q.C. & distribution 

CNMCA 

WP-2330 

Validation in Germany 

BfG 

WP-2430 

IR / MW blending 

ISAC 

WP-2340 

Validation in Hungary 

HMS 

WP-2350 

Validation in Italy 

University of Ferrara 

WP-2440 


CNMCA 

WP-2360 

Validation in Italy 

DPC 

WP-2370 

Validation in Poland 

IMWM 

WP-2450 

Complementary research 

ECMWF 

WP-2380 

Validation in Slovakia 

SHMÚ 

WP-2390 

Validation in Turkey 

ITU 

WBS-03 - WBS of WP-2000: 1 st , 2 nd and 3 rd level WP’s. 4 th level WP’s defined in next sections.


The WBS shows that a set of H-SAF participant will run a coordinated programme of products 

validation (WP-2300). Validation of precipitation is not an easy task. All ground systems have know 

biases and, in this sense, for precipitation rate the ground truth does not exist. Under these conditions, 

validation is actually a system, that involves comparisons with several sources, both instruments (rain 

gauges, radar) and numerical models. The results change with geographical/climatic areas, thus the H- 

SAF products validation programme involves several participant across Europe. 

The WBS reserves WP-2400 for all developmental work. Baseline methods will be used for Version-1 

of the products, to be delivered at approximately T 0 + 24. A parallel continuous development activity 

will be conducted. Development could regard augmentation of the cloud-radiation database, improved 

calibration as feedback of the validation activity, new processing methods, newly available instruments, 

and reactions to feedback from users, specifically from the Hydrological validation programme (Cluster- 

4), but also from operational end-users. 

4.2 Observation of precipitation (WP-2100) 

4.2.1 Generalities 

WP-2100 is due to generate the basic precipitation products from H-SAF. WBS-04 displays the 

structure of the WP down to the 4 th level WP’s. The task is led by several Italian units, as follows. 

• CNMCA will lead the WP. It will provide the basic structures for meteorological satellite 

acquisition, pre-processing, processing and distribution; integrate the application software, with 

support from CNR-ISAC and Industry; operate the facilities through the Development Phase. 

CNMCA has available plenty of auxiliary and ancillary data supporting processing and quality 

control, including raingauge, radar and lightning networks, satellite images and meteorological maps. 

• CNR-ISAC is responsible of developing and providing databases and algorithms for a number of 

products (see WP-2400), and also will assist CNMCA for software integration and provision of 

criteria for quality control. 

• The DPC provides auxiliary and ancillary data (raingauge and radar networks) either directly 

managed or controlled in the framework of the Italian Civil Defence organisation. It will also 

provide fast-reacting user feedback useful for quality control. 

WP-2100 

Observed precipitation 

Italy (CNMCA) 

WP-2110 

Data acquisition & pre-processing 

CNMCA 

WP-2111 

Meteorological satellites 

CNMCA 

WP-2112 

Ancillary data from Met Service 

CNMCA 

WP-2113 

Ancillary data from outside Met Serv. 

DPC 

WP-2114 

Data from R&D satellites 

ISAC 

WP-2120 


CNMCA 

WP-2121 

Input files formation & control 

CNMCA 

WP-2122 

Support to S/W integration 

ISAC 

WP-2123 

S/W integration & testing 

CNMCA + Industry 

WP-2124 

Operations 

CNMCA 

WP-2130 

Quality Control & distribution 

CNMCA 

WP-2131 

Development of QC procedures 

ISAC 

WP-2132 

User feedback 

DPC 

WP-2133 

On-line Quality Control 

CNMCA 

WP-2134 

Products delivery 

CNMCA 

WBS-04 - WBS of WP-2100: 2 nd , 3 rd and 4 th level WP’s.


The conceptual architecture of WP-2100 is shown in Fig. 8, that is the subject of separate documents: 

the “System requirements document” (SRD) and the “System design document” (SDD). 

DMSP 

DoD / NOAA 

Data from 

lightning networks 

VIS/IR/MW 

images 

Meteorological 

maps 

Data from 

raingauge 

networks 

NOAA 

MetOp 

Meteosat 

UKMO 

PRE- 

PROCESSED 

DATA 

REAL-TIME 

PRE- 

PROCESSING 

SSM/I 

SSMIS 

AMSU-A 

AMSU-B 

MHS 

SEVIRI 

PRODUCT 

GENERATION 

QUALITY 

CONTROL 

EUMETSAT 

MEMBERS AND 

COOPERATING 

STATES 

EOS/Aqua 

Database of 

precipitating cloud 

models 

Tools for product 

validation and 

improvement 

Radar 

images 

Feedback from 

National Civil 

Protection 

TRMM 

NASA 

Datasets of AMSR-E + AMSU-A + HSB 

Datasets of TMI + PR + LIS 

Fig. 8 - Conceptual architecture of the processing chain for precipitation products generation. 

A main feature of H-SAF is to provide hydrologists with data complying with very tight timeliness 

requirements (according to Table 2, 20 min for MW, 10 min for IR/MW). Therefore, precipitation 

products generation will be essentially based on satellites that provide real-time access. This is 

obviously the case for Meteosat data, as well as for MetOp and NOAA. DMSP data could be received 

in deferred time through NOAA or ECMWF or the UK Met Office (UKMO) but, for the purpose of H- 

SAF, the product timeliness requirement could not be fulfilled, thus it will be necessary to acquire them 

through a NATO station [Note: it is anticipated that, at least through most of the Development Phase, 

this will not be possible, and the primary source will be UKMO, whilst a solution via EUMETCast is 

being pursued]. In the operational phase NPOESS will provide real-time access. For the other satellites 

of the GPM constellation the data circulation concept has not yet been developed, but it is foreseen that 

there will be a structure enabling near-real-time data availability. The EUMETCast dissemination 

system is rapidly becoming more and more efficient: in the course of the Development Phase directread-out 

and EUMETCast will be used for mutual redundancy. 

Reserving the term “System” for the H-SAF overall product generation facility shown in Fig. 3 of 

Chapter 2, and “Sub-system” to the facility shown in Fig. 8 above, Fig. 9 anticipates, from the System 

requirements and design documents, the main components of the precipitation sub-system. In addition, 

Fig. 10 anticipates the main data flows to, within and from the precipitation sub-system. 

Fig. 11 shows the relationships between satellite data and output products.


Front End Satellite 

Satellite data 

DATA PROCESSOR 

LEGENDA 

Archive of Precipitation 

Cluster 

0 External 

Parameters 

Front End 

Auxiliary Data 

Calibration and 

Validation 

Development 

Quantitative 

Precipitation 

Forecasts and 

derived products 

Tuning, Study and 

Development 

Operative 

chain 

Data 

acquisition 

Control 

Storage 0 

End Users 

Monitoring of output 

and off line requests 

Fig. 9 - Main components of the precipitation products generation sub-system. 

Front End Satellite 

Satellite data: 

level 0, 1 a-c 

DATA 

PROCESSOR 

External 

Parameters 0 

of POP 

Precipitation 

Observation Production 

Quantitative 

Precipitation 

Forecasts 

External 

Parameters 0 

of QPF 

Development and 

Tuning of POP 

Calibration and 

Validation of POP 

Archive of Precipitation 

Cluster 

Precipitation Production Distribution 

Monitoring and recovery 

Development and Tuning of QPF 

Calibration and Validation 

of QPF 

Front End Auxiliary Data 

LEGENDA 

Study and Development 

Operative chain 

Data 

acquisition 

Control 

Off line requests 

End Users 

Storage 

Fig. 10 - Main data flows to, within and from the precipitation products generation sub-system.


DMSP ≤ F15 

DMSP ≥ F16 

NOAA, 

MetOp 

NOAA ≤ 17 

NOAA ≥ 18, 

MetOp 

Meteosat ≥ 8 

SSM/I 

SSMIS 

AMSU-A 

AMSU-B 

MHS 

SEVIRI 

Processor 

Processor 

Processor 

Processor 

Processor 

Processor 

SSM/I – SSMIS processing chain AMSU – MHS processing chain LEO/MW + GEO/IR 

processing chain 

PR-OBS-1 – Precipitation rate 

from conical scanners 

PR-OBS-2 – Precipitation rate 

from cross-track scanners 

PR-OBS-3&4– Precipitation rate 

from blended LEO/MW and GEO/IR 



PR-OBS-5 – Accumulated precipitation 

from blended LEO/MW and GEO/IR 

Quality control Quality control Quality control Quality control 

End-users and H-SAF central archive 

Fig. 11 - Relationships between satellite data and output products. 

It is observed in the [yellow] boxes that there are four processing chains, as follows: 

• precipitation rate from conical scanning SSM/I and SSMIS; 

• precipitation rate from cross-track scanning AMSU and MHS; 

• precipitation rate by blending MW from LEO and IR from GEO; 

• accumulated precipitation from blended LEO/MW and GEO/IR. 

4.2.2 The data acquisition and pre-processing task (WP-2110) 

The objective of WP-2110 is to acquire satellite data either by EUMETCast or by direct read-out, as 

well as ancillary and auxiliary data necessary to generate precipitation products. These data are 

acquired at CNMCA. Data from R&D satellites are acquired by ISAC, generally from NASA via ftp. 

As shown in Fig. 11, satellite data acquisition is followed by signal processing for extracting the data 

from the addressed instrument, arranging the appropriate raw data stream (“Level-0” data), and 

performing on-line calibration and geolocation (“Level-1” data). These operations are performed by an 

instrument processor. In this PP-2.0 we consider data acquisition and pre-processing as a single task. 

The acquisition of Meteosat occurs all time, since the satellite is geostationary. Sun-synchronous 

satellite, instead, are acquired at intervals. 

Fig. 12 shows the orbital positions and earth’s coverage of six sunsynchronous satellites presumably to 

be used for Version-1 products generation in years 2008-2009 (NOAA-17, NOAA-18, MetOp, DMSP 

F-13, DMSP S-16 and DMSP S-17).


NOAA-18 

AMSU-A + MHS 

13:40 a 

DMSP S-17 

SSMIS 

5:30 d 

DMSP F-13 

SSM/I 

6:30 d 

DMSP S-16 

SSMIS 

8:10 d 

MetOp-1 

AMSU-A + MHS 

9:30 d 

NOAA-17 

AMSU-A + AMSU-B 

10:20 d 

Fig. 12 - One-orbit coverage from six operational meteorological satellites equipped with MW instruments in years 

2008-2009. The figure assumes all satellites cross the ascending or descending equatorial node at 12 UTC. 

In red, conical scanning imagers (swath 1400 km); in blue cross-track scanning sounders (swath 2200 km). 

In may be seen that there is a rather regular sequence of satellite passes in the range of Local Solar 

Times (LST) 05-14 and 17-02 whereas there is a gap of time coverage in intervals 02-05 and 14-17 LST. 

This is unfortunate, since there is no observation in the range of hours (mid-afternoon) when convection 

is more frequent over continental areas. Fortunately, observation from IR imagery in GEO (Meteosat) is 

more sensitive to convective precipitation. 

WP-2110 includes the following activities: 

WP-2111: Meteorological satellites 

The activity addresses the operational meteorological satellites mentioned in Figures 10, 11 and 12, to 

be acquired either by direct readout in real-time, or in near-real-time by EUMETCast. NOAA, MetOp 

and Meteosat data will be acquired both by direct readout and via EUMETCast, for redundancy. Data 

from the DMSP satellites could in principle be acquired in real-time, but actually, for most of the H- 

SAF Development Phase, they will be acquired from UKMO via ftp, waiting for a more timely solution 

(e.g., inclusion of SSM/I-SSMIS in the EUMETCast broadcasting programme). 

WP-2112: Ancillary data available internally to the Italian Meteorological Service 

Satellite data processing will require, to some extent, ancillary data and information, sometimes to help 

products retrieval, always for on-line quality control. The Italian Meteorological Service has available 

the data from the national network managed by the Service itself, and the data circulating over the GTS, 

both Main Trunk and some Regional networks. Special files for H-SAF purpose will be built.


WP-2113: Ancillary data not internal to the Italian Meteorological Service 

In addition to those managed by the Italian Meteorological Service, other data from raingauge and radar 

networks belonging to or controlled by the DPC in the framework of the Italian Civil Defence 

organisation, will be collected and utilised. Some of these data will be made available timely enough as 

to be used for on-line quality control, most will be available for supporting the environment for followon 

production cycles. 

WP-2114: Data from R&D satellites 

High-quality datasets from TRMM (PR, TMI, LIS) and EOS-Aqua (AMSR-E) will be collected by 

CNR-ISAC to be used for improving processing models and for calibration of products from operational 

(less performing) instruments. The structure implemented by NASA for distribution of these data (via 

ftp) will be used. 

4.2.3 The products generation task (WP-2120) 

The objective of WP-2120 is to generate the following precipitation products (see Fig. 11): 

• PR-OBS-1 - Precipitation rate at ground by MW conical scanners (with indication of phase 

• PR-OBS-2 - Precipitation rate at ground by MW cross-track scanners (with indication of phase) 

• PR-OBS-3 - Precipitation rate at ground by GEO/IR supported by LEO/MW 

• PR-OBS-4 - Precipitation rate at ground by LEO/MW supported by GEO/IR (with flag for phase) 

• PR-OBS-5 - Accumulated precipitation at ground by blended MW and IR. 

The products will be generated starting from algorithms selected or developed by CNR-ISAC (first 4 

products) or internally to CNMCA (fifth product). The developmental activities are described under 

Section 4.5 (WP-2400). The software is implemented at CNMCA, with support from ISAC as concerns 

the first 4 products. 

WP-2121: Input file formation and control 

This WP regards the activities necessary to interface the acquisition and pre-processing chains of the 

various instruments with the products generation chain. It implies: 

• the implementation of files optimally formatted to fasten access and save CPU time and disk space; 

• monitoring input data (for completeness, for quality, …); 

• emergency management (turn-around manoeuvres for missing data, data recovering, etc.). 

Some industrial support is foreseen. 

WP-2122: Support to S/W integration 

CNR-ISAC, responsible of development and testing of most algorithms backing precipitation products 

generation (see WP-2400), will provide the necessary databases and assist CNMCA for the integration 

of software originally developed in a research environment, on the operational facilities in use at 

CNMCA; and will participate to software validation activities. 

WP-2123: S/W integration and testing 

CNMCA, in cascade from the acquisition and pre-processing systems (see WP-2110), will (with CNR- 

ISAC support; see WP-2122) install the databases, algorithms and codes provided by CNR-ISAC or 

developed at CNMCA on the available processing facilities, implement the software and perform testing 

and validation. Some industrial support is foreseen. 

WP-2124: Operations 

CNMCA will operationally run the precipitation products generation chain on the available facilities, 

keep in-line and update/upgrade the facilities whenever necessary, maintain data quality (by exploiting 

the validation activity under WP-2300) and distribute the products after quality control (see WP-2130).


4.2.4 Quality control and distribution (WP-2130) 

The objective of WP-2130 is to generate a real time and off line data distribution flow of data of 

controlled quality. 

WP-2131: Development of QC procedures 

This WP defines rules, procedures and protocols backing the online and offline quality control activity, 

taking into consideration the product error structures, the applicability of the processing algorithm in 

respect of the type of precipitation, the status of cal/val, the availability of auxiliary data for quality 

control, etc.. The appropriate quality control procedures are developed by the Units responsible of the 

product development activity. 

WP-2132: User feedback 

This WP provides structured reporting on data quality as assessed by operational end-users (for instance, 

in the functional centres of the DPC). Emphasis will be placed on operational features of the service 

(regularity, timeliness, soundness, formal assets, etc.) leaving to the Hydrological validation programme 

the scientific assessment of data impact on applications. The WP is implemented in connection with 

WP-1230. 

WP-2133: On-line Quality Control 

This WP collects the auxiliary data to be used for on-line quality control (lightning, rain gauge, satellite 

images, radar maps, meteorological maps, …; see Fig. 8) and implements the procedures generated by 

WP 2131 on each product generated in WP-2100 before its distribution. 

WP-2134: Products delivery 

This WP refers to the operational chain to disseminate the Precipitation Products and Q.C. information 

in real-time (by dedicated links) or near-real-time (by EUMETCast) or off-line (from the central 

archive). A semi-automatic control is applied to monitor the broadcasting status. A semi-automatic 

system is applied to recover from service interruptions and provide delivery in differed time. 

4.3 Computed precipitation (WP-2200) 


MW-derived precipitation products will be distributed soon after the time of satellite pass, in a 

projection similar to the natural one of the image (except for panoramic distortion). This means that 

data from more passes will not be synchronous, nor at a time coincident with a desired one, and the 

earth location of the data will change all times. Data from merged MW-IR, provided in the Meteosat 

projection, could approximately be synchronous with any pre-fixed time but their position will be 

irregular on the earth surface. It is realised that current hydrological models largely prefer to be 

initialised by means of forecast fields represented over regularly-distributed grid points synchronous 

with a defined time. These user-friendly characteristics might represent a so great practical advantage 

that the effect of (in principle) higher accuracy of the observation might be biased. For this reason, in 

addition to the original observations at the proper times and locations, a space-time continuised field 

will also be provided by using a NWP model. This also will serve as a backup for the user against 

occasional gaps in the satellite processing cycle, and as one tool for quality control. 

Currently, it is envisaged to use the COSMO-ME model of the Italian Meteorological Service. It is a 

non-hydrostatic model with 40 vertical levels and 7 km grid spacing. The current operational version of 

COSMO-ME does not assimilate precipitation data, but there is the technical capability to do this. At 

present MW satellite radiances from the temperature sounding channels are assimilated. 

It is to be noted that the development of the NWP model to better serve the purpose of Hydrology will 

be pursued in connection with H-SAF, but as a “best-effort” item, i.e. not budgeted under H-SAF. In


other words, forecast precipitation fields will be provided during the H-SAF Development Phase from 

the output of the model in current operational use. 

WBS-05 displays the structure of WP-2200, that is entirely performed by CNMCA. The conceptual 

architecture is shown in Fig. 13. 

WP-2200 

Computed precipitation 

Italy (CNMCA) 

WP-2210 

Quantitative Precipitation Forecasts 

WP-2211 

Tuning of COSMO-ME to H-SAF requirements 

WP-2212 

Operational precipitation products 

WP-2220 

NWP model improvement 

WP-2221 

Improved physics representation 

WP-2222 

Improved data assimilation 

WP-2213 

Quality control and distribution 

WBS-05 - WBS of WP-2200: 2 nd , 3 rd and 4 th level WP’s. 

Satellite observations 

Assimilation & initialisation 

Ground-based observations 

High resolution model Integration 

Precipitation rate 

PR-ASS-1 



Fig. 13 - Products generation chain for Quantitative Precipitation Forecasting. 

4.3.2 Quantitative precipitation forecast (WP-2210) 

WP-2200 is to generate the following precipitation products: 

• PR-ASS-1 - Instantaneous and accumulated precipitation at ground computed by a NWP model. 

WP-2210 is implemented as a special effort for H-SAF, embedded in the current NWP operational chain 

at CNMCA. The objective of WP-2210 is to improve high resolution NWP precipitation forecasts and 

itsr timely delivery. 

WP-2211: Tuning of COSMO-ME to H-SAF requirements 

COSMO-ME is the high resolution NWP model in use at CNMCA for QPF. As it is configured now, 

COSMO-ME does not meet H-SAF requirements. The following improvements need to be 

implemented: 

• extension of the area coverage, that implies: 

- retrieval and quality control of physiographic parameters (soil type, vegetation parameters, etc.); 

- reconfiguration of boundary conditions files; 

- geographical parameters reconfiguration;


- reconfiguration of operational scripts; 

- testing of the new operational configuration; 

• increased number of vertical layers; 

• increased number of runs per day. 

Implementation of all these improvements would require much more computing power with respect to 

what is currently available. Improvements will gradually be introduced based on the availability of the 

necessary computing resources over the Development Phase period. 

WP-2212: Operational precipitation products 

The generation of precipitation products for H-SAF (instantaneous precipitation and accumulated 

precipitation) are already part of the operational NWP chain at CNMCA. The only change will consist 

of the modifications due to WP-2211 and the extraction of the specific output files for H-SAF. 

WP-2213: Quality control and distribution 

All products from the NWP chain in CNMCA use to be quality-controlled before dissemination. 

However, additional Q.C. will be applied to the special case of precipitation. The verification of 

COSMO-ME quantitative precipitation forecasts will be made with respect to high resolution surface 

observations. This will involve the set-up of a database of regular observations (e.g., 1-hour cumulated 

precipitation) from reports of different sampling times. Due to differing observing practices, the data 

will have to be carefully screened and quality controlled. Data representativeness and downscalingupscaling 

issues will also be tackled. 

4.3.3 NWP model improvement (WP-2220) 

Whilst WP-2210 addresses the specific requirements of H-SAF framing them into the current 

operational NWP activity, WP-2220 does not specifically address H-SAF, but only takes advantage of 

improvements of the NWP model at large that will provide indirect benefit to H-SAF products among 

other ones. 

WP-2221: Improved physics representation 

New microphysics and turbulence parameterisation schemes will be tested and implemented in the 

COSMO-ME model to improve the precipitation forecast skill (more types of hydrometeors and 

dimensions/shapes, better representation of boundary layer processes, etc.). 

WP-2222: Improved data assimilation 

The COSMO-ME model already assimilates a certain amount of satellite data. When new types and 

sources of satellite data will be available on the GTS they will be included in the analysis step.


4.4 Precipitation products validation (WP-2300) 


Validation is obviously a hard work in the case of precipitation, both because the sensing principle from 

space is very much indirect, and because of the natural space-time variability of the precipitation field 

(fractal or close-to-fractal), that places severe sampling problems. In addition, because of known biases 

of ground systems (essentially raingauge and radar), a reliable ground truth does not exist. Comparison 

with results of numerical models obviously suffer of the incompatible scales between the natural 

phenomenon and the model (for hydrostatic NWP models) or the limits of atmospheric predictability 

when entering the scale of convection (for Cloud Resolving Models). A mixture of all this techniques is 

generally used, and the results change with the climatic situation and the type of precipitation. It is 

therefore necessary a European cooperation for this programme. 

The objective of WP-2300 is to support precipitation products quality by: 

• supporting algorithms and models tuning (i.e., calibration) during their development process; 

• characterise the products error structure whose knowledge is needed for correct utilisation; 

• collecting routine reporting from end-users and special reporting from experimental activities; 

• continuing calibration/validation activities during the pre-operational phase. 

WBS-06 shows that eight H-SAF participants cooperate to the validation programme, under the 

leadership of Italy (DPC). 

WP-2300 

Validation 

Italy (DPC) 

WP-2310 

Philosophy 

DPC 

WP-2320 

in Belgium 

IRM 

WP-2330 

in Germany 

BfG 

WP-2340 

in Hungary 

HMS 

WP-2350 

in Italy 

UniFerrara 

WP-2360 

in Italy 

DPC 

WP-2370 

in Poland 

IMWM 

WP-2380 

in Slovakia 

SHMÚ 

WP-2390 

in Turkey 

ITU 

WP-2311 

Validation 

methods 

WP-2321 

Tools & 

structures 

WP-2331 

Tools & 

structures 

WP-2341 

Tools & 

structures 

WP-2351 

Tools & 

structures 

WP-2361 

Tools & 

structures 

WP-2371 

Tools & 

structures 

WP-2381 

Tools & 

structures 

WP-2391 

Tools & 

structures 

WP-2312 

Reporting 

& analysis 

WP-2322 

Support to 

calibration 

WP-2332 

Support to 

calibration 

WP-2342 

Support to 

calibration 

WP-2352 

Support to 

calibration 

WP-2362 

Support to 

calibration 

WP-2372 

Support to 

calibration 

WP-2382 

Support to 

calibration 

WP-2392 

Support to 

calibration 

WP-2323 

Characterisation 

WP-2333 


WP-2343 


WP-2353 


WP-2363 


WP-2373 


WP-2383 


WP-2393 



4.4.2 Validation philosophy (WP-2310) 

The objective of WP-2310 is to establish common principles for all validation exercises, i.e.: 

• which methods and tools have to be utilised; 

• how to report the results of the validation activities and how to analyse them. 

WP-2311: Validation methods 

Since the nature of remote-sensed precipitation observation differs substantially from that one of ground 

based systems (rain gauge and radar), comparison of the two measurements requires a number of 

preventive operations to bring them to consistency (upscaling, downscaling, etc.). This WP defines 

which ground tools have to be used and how to make the comparison, including consideration of both 

mechanical comparisons suitable to build statistics (performance indexes) essential for product


characterisation, and focused exercises (supervised) intended to understand the reasons of differences, 

particularly useful for calibration. 

WP-2312: Reporting and analysis 

The description of validation activities will often be a kind of scientific work, to be assembled in a 

special (bulky) report. For practical purposes, reports in standardised formats will be provided, aiming 

at easy extraction of the essential message, and focused analysis. Reports could have different shapes, 

depending on their purpose: 

• reasonably articulated when to be used as feedback to the Units in charge of development (WP- 

2400) for improving calibration; 

• closely structured and standardised when to be used for products characterisation; 

• concise and essential when to be used for on-line monitoring of data quality (see WP-1230 for 

monitoring and WP-2130 for quality control). 

4.4.3 Validation activity (WP’s 2320 to 2390) 

Eight Units will participate to the validation activities, in seven Countries (there will be two Units in 

Italy). They have taken active role in defining the validation philosophy (WP-2310) and operate in 

close coordination both among themselves and with the Units in charge of products development (WP- 

2400). In each Country or Unit the work programme may be slightly different in respect of both the 

available tool and the adopted methodology. However, for the sake of simplicity, only three type of 

WP’s are described below. 

WP’s 2321, 2331, 2341, 2351, 2361, 2371, 2381 and 2391: Tools and structures 

Tools (rain gauges, radar, generic meteorological stations, model outputs, …) and structures (existing 

networks, special test sites, …) will be either made available or tuned or modified or installed onpurpose 

to support validating H-SAF precipitation products. 

WP’s 2322, 2332, 2342, 2352, 2362, 2372, 2382 and 2392: Support to calibration 

The most urgent task of the validation activity is to support tuning processing algorithms and software 

by enabling improved calibration. This first phase will be performed in close contact with WP-2400, 

by using tools and methods as available in the early phase of the Development Project, even if not yet 

available on a routine basis (tools) or fully consolidated (methods). Supervised methods, special 

campaigns and, sometimes, special tools (e.g., research radar) will be utilised. 

WP’s 2323, 2333, 2343, 2353, 2363, 2373, 2383 and 2393: Characterisation 

Ultimately, all products distributed by H-SAF will be associated with information on their error 

structure. This is essential for a correct utilisation of the data, especially in numerical models 

(hydrological and meteorological). Due to the large variability of the geographic/climatic/seasonal 

situations and the different response of remote sensing tools to different types of precipitation, 

characterisation will take a long time, presumably till the end of the H-SAF Development Project. Only 

limited characterisation will be available at the time of demonstrational products release, substantially 

more at the time of the second release (pre-operational products). Validation will be run routinely, 

therefore mostly basing on operational tools. Methods will be based on categorisation. Data 

performances will be analysed for selected intensity classes and geographic/climatic/seasonal situations 

by essentially automatic methods, to provide standard quality indexes. 

The characterisation work will provide the participating Units with opportunity to contribute to the 

development of the precipitation products. [Note: in PP-1.0, contributions to development from 

Belgium, ECMWF, Poland and Turkey were foreseen under WP-2400. Now these contributions are 

considered as stemming from the validation activity, except for ECMWF that does not participate to 

WP-2300 thus is kept under WP-2400].


4.5 Developments (WP-2400) 


As indicated in Chapter 2, development will be a continuous process during the H-SAF Development 

Phase (see Fig.s 4 and 5). During the first two years, baseline processing methods will be implemented, 

so as to generate “demonstrational products”, i.e. representative data to activate the Hydrological 

validation programme (Cluster-4); then development will continue so as to progressively improve data 

quality and release “pre-operational products” at about 3.5 years, and a final release of “operational 

products” at the end of the Development Phase. 

[Note 1 - In PP-1.0 the developmental activity for generating demonstrational products was included in 

the product generation WP’s, i.e. WP’s 2100 and 2200, whereas WP-2400 was reserved for further 

developments, i.e. for pre-operational and final operational releases. In this PP-2.0 this distinction is no 

longer kept: demonstrational products are just based on a snapshot of the development as occurred up to 

the time of delivering pre-operational and operational products]. 

[Note 2 - The titles of the WP’s are now closely associated to the products to be delivered]. 

[Note 3 - In PP-1.0 there were more countries involved in developments for precipitation. Now these 

contributions are practically provided through the validation activity, i.e. WP-2300, and all except one 

developments occur in Italy]. 

WBS-07 deploys the structure of WP-2400, lead by the CNR Istituto di Scienze dell’Atmosfera e del 

Clima (ISAC), the scientific partner of the Italian Meteorological Service for H-SAF purposes. 

WP-2400 

Developments 

Italy (CNR-ISAC) 

WP-2410 

MW conical scanners 

ISAC 

WP-2420 

MW cross-track scann. 

ISAC 

WP-2430 

IR / MW blending 

ISAC 

WP-2440 

Accumulated precip. 

CNMCA 

WP-2450 

Complementary R&D 

ECMWF 

WP-2411 

Algorithm selection 

& improvement 

WP-2421 


& improvement 

WP-2431 


& improvement 

WP-2441 


& improvement 

WP-2451 

SSMIS data 

pre-processing 

WP-2412 

Cloud-radiation 

database 

WP-2422 

Image sharpening 

& pre-processing 

WP-2432 

Rapid-Update 

implementation 

WP-2442 

Time integration of 

precipitation rate 

WP-2452 

Building surface 

emissivity maps 

WP-2413 

Precipitation retrieval 

& calibration 

WP-2423 

Precipitation retrieval 

& calibration 

WP-2433 

Morphing 

implementation 

WP-2442 

Bias 

corrections 


It is noted that, in general, the work performed in WP-2400 is described to a fair level of detail in the 

Algorithm Theoretical Definition Document (ATDD). The version of ATDD aligned to this PP-2.0 is 

ATDD-1.0, delivered to the CDR at the same time. 

[Note 1 - The developmental activity for product PR-ASS-1 from WP-2200 (Computed precipitation) is 

not included in WP-2400 since the activity is internal to WP-2200. However, ATDD-1.0 includes 

information on the adopted NWP model and the personalisation for H-SAF purposes]. 

[Note 2 - WP-2450, that is implemented by a Visiting Scientist at ECMWF, is recorded in this PP-2.0 

but not in ATDD-1.0 since there is a dedicated document for it: the Report of the Visiting Scientist].


4.5.2 Precipitation by MW conical scanning radiometers (WP-2410) 

This is the WP intended to develop product PR-OBS-1. The MW scanning radiometers provide 

observation with constant zenith angle, thus constant resolution at a given frequency and easier handling 

of the polarisation information; and in “window” channels at relatively low frequencies, thus capable of 

somewhat “direct” observation of precipitating particles. Therefore, in principle, instruments such as 

SSM/I should be able to provide the most accurate precipitation measurements. The successor SSMIS 

adds channels in absorption bands, bringing auxiliary information on the vertical structure of 

atmospheric temperature and water vapour. 

WP-2411: Algorithm selection and improvement 

The selected algorithm is thought to be the most powerful currently available, derived by the experience 

performed with TRMM data, being progressively improved in view of the future Global Precipitation 

Measurement mission (GPM). WP-2411 includes a number of developments intended to make the 

algorithm working in an operational environment rather than in a research environment. 

WP-2412: Implementation of a cloud-radiation database 

Although observations in window channels are somewhat direct in respect of detecting precipitation, the 

retrieval problem is awfully ill-conditioned (too many solutions consistent with too few measurements 

in too few channels). It is necessary to input external information on the expected atmospheric structure 

(cloud microphysics). Since, nowadays, the available computing power is not sufficient to simulate the 

atmospheric situation on-line with the incoming observation, a-priory possible atmospheric profiles of 

hydrometeors are computed by means of a Cloud-Resolving Model (CRM) followed by a Radiative 

Transfer Model (RTM) to simulate the possible sets of brightness temperatures. The resulting profiles 

are stored in a Cloud-Radiation Database (CRD). WP-2412 provides building the CRD and 

progressively augmenting its representativeness. [Note: this work is being done in collaboration with 

the University of Wisconsin, specifically Greg Tripoli]. 

WP-2413: Precipitation retrieval and calibration 

A physical method is used for precipitation retrieval from SSM/I and SSMIS measurements. When 

observations arrive, a search is performed in the CRD for the maximum likelihood profiles, by means of 

a Bayesian technique. Information on the error structure (Jacobians) is necessary for this purpose. The 

method, however, has the capability to update the Jacobians with time. A patient work of tuning is 

necessary to deal with typical problems of the method (surface emissivity, coastlines, …) and discover 

possible new ones. Progress might also be necessary on basic modules (e.g., RTM for better 

representation of ice scattering). The validation activity (WP-2300) will provide input for calibration. 

4.5.3 Precipitation by MW cross-track scanning radiometers (WP-2420) 

This is the WP intended to develop product PR-OBS-2. Although conical scanning radiometers should 

in principle provide data of superior quality, cross-track scanning radiometers primarily designed for 

temperature and humidity profiling (AMSU-A and AMSU-B or MHS) also need to be used for 

achieving more frequent coverage (see Fig. 12). These instruments operate in absorption bands, that 

have the privilege of less sensitivity to the disturb of surface (emissivity), and benefit of built-in 

information on the atmospheric temperature and humidity structure, that is favourable for detecting 

precipitation from stratiform clouds and snowfall. 


AMSU-B (or MHS) and, to a minor extent, AMSU-A, are now rather extensively utilised for 

precipitation retrieval. The methods adopted are generally very simple, in most cases only using 

AMSU-B / MHS or even only their two window channels (89 and 150 or 157 GHz). For H-SAF, the 

most advanced method has been adopted, originally developed in MIT (Dave Staelin). WP-2421 

includes a number of developments intended to make the algorithm working in an operational 

environment rather than in a research environment.


WP-2422: Image sharpening and pre-processing 

In current practise AMSU-A is not used because of its relative coarse resolution (~ 50 km at the s.s.p. 

degrading across-track to some 100 km at the edge of the image). On the other hand, the temperature 

profile is more significant of the atmospheric structure (water vapour in precipitating areas tends to 

saturation), and AMSU-A has much more dense spectral information than AMSU-B / MHS (15 

channels v/s 5 channels). WP-2422 performs resolution enhancement of AMSU-A by importing highspatial-frequency 

information from AMSU-B / MHS. In addition, corrections need to be applied for the 

increasing atmospheric thickness when moving from the sub-track to the image edge (limb darkening). 

WP-2423: Precipitation retrieval and calibration 

Measurements of precipitation in absorption bands are much more indirect than in window channels. 

Physical retrieval would in principle be more effective thanks to the built-in information on the 

atmospheric vertical structure, but the variable incidence angle and resolution would make the CRD 

extremely wide and laborious. Leaving this possibility to a later stage, a neural network algorithm is 

currently baselined. In a first phase, the neural network is trained by means of a selected set of 

meteorological radar of the NEXRAD network. In a second phase, the training is performed against 

hydrometeor profiles simulated by a Cloud Resolving Model (MM5). This has the advantage of 

extending the database everywhere, including Europe. A patient work of tuning is necessary to deal 

with typical problems of the method (frozen surfaces, too dry atmosphere, …) and discover possible 

new ones. The validation activity (WP-2300) will provide input for calibration. 

4.5.4 Precipitation by blending MW and IR observations (WP-2430) 

This is the WP intended to develop products PR-OBS-3 and PR-OBS-4. At most, low-orbiting 

satellites (LEO) could provide some six MW coverages per day (see Fig. 12), i.e. measurements at 4- 

hourly (irregular) intervals, to become 3 hours with the GPM. For nowcasting and hydrology this is not 

enough. In particular, it is not enough for computing accurate accumulated precipitation. Observation 

from MW in geostationary orbit would be ideal, but the technology is not yet there, and current plans 

look at this possibility to materialise not before 2015-2020. It is therefore necessary to complement 

accurate/infrequent MW measurements from LEO with frequent/inaccurate IR observations from GEO. 


Several techniques are available and are being developed for blending GEO/IR and LEO/MW data. The 

most consolidated way is to make use of frequent IR images and “calibrate” them in terms of 

precipitation by using MW determinations. The opposite approach is based on using the MW 

determinations and interpolate in between them by importing dynamical information from IR images. 

Both methods will be used for H-SAF, but the first one is currently much more consolidated. 

WP-2432: Rapid-Update implementation 

The first method to be implemented (“Rapid-Update”) makes use of SEVIRI IR radiances (equivalent 

black-body temperatures) available at 15-min intervals and convert them into mm/h by means of lookup 

tables built by space-time co-located MW measurements, updated at any new SSM/I-SSMIS or AMSU- 

MHS pass. In respect of other practices currently operational (e.g., in EUMETSAT with the Multisensor 

Precipitation Estimate, MPE), the product for H-SAF should presumably be more accurate 

because of more frequent, more timely and possibly more accurate MW measurements. The validation 

activity (WP-2300) will provide input for product improvement through better calibration. 

WP-2433: Morphing implementation 

The Rapid-Update method suffers of the disputable relationship between IR radiances and precipitation, 

valid essentially for convective precipitation. The second method to be implemented (“Morphing”) 

makes use of SEVIRI IR radiances only to interpolate in between infrequent MW measurements (i.e. the 

retrieval is from MW, not from IR). The method is more complicated because it is necessary to wait for 

a new MW observation, and move back and forward (“morphing”) in between the last two. It is not sure


that the operational constraints will enable the product to be timely enough. However, for the purpose 

of computing accumulated precipitation, that is a major requirement from Hydrology, Morphing should 

be much more accurate than Rapid-Update (that, however, meets timeliness requirements from 

Nowcasting). Both products, by Rapid-Update and Morphing, will co-exist. It is noted that the 

Morphing product (PR-OBS-4) is targeted for the second set of products release (at ~ T 0 + 42). 

4.5.5 Accumulated precipitation (WP-2440) 

This is the WP intended to develop product PR-OBS-5. The basis for time integration are initially 

product PR-OBS-3 (Rapid-Update) and, later, PR-OBS-4 (Morphing). The problem is that, particularly 

with PR-OBS-3, the original precipitation rate measurement is not accurate enough, and specifically is 

biased towards convective precipitation (more closely associated to IR radiances). Therefore, 

contextual auxiliary information is necessary. 


The method adopted performs blending of satellite-derived measurements and external information, 

both observed (from rain gauges) and forecast (from the operational NWP model). With PR-OBS-3 the 

relative impact of the auxiliary information would be major, with PR-OBS-4 should be less. 

WP-2442: Time integration of precipitation rate 

According to the user requirements, precipitation rate data are integrated over time intervals of 3, 6, 12 

and 24 hours. The measurements will be weighed to account for their error structure (information 

initially scarcely available, to be augmented as the validation programme makes progress). 

WP-2443: Bias corrections 

Actual precipitation data from rain gauge networks will be used for building the first guess field due to 

constrain the noisy observed precipitation pattern. A number of corrections will have to be applied to 

rain gauge measurements before being used for this purpose. Another auxiliary information to be used 

is the field forecast by the operational NWP model in use at CNMCA. A patient work of tuning is 

necessary to deal with typical problems of the method (scale consistency between satellite and ground 

measurement, and NWP-derived fields, …) and discover possible new ones. The validation activity 

(WP-2300) will provide input for calibration. 

4.5.6 Complementary R&D work at ECMWF (WP-2450) 

The ECMWF contributes to precipitation products development through the Visiting Scientist 

programme. This activity has already been conducted in the first phase of the H-SAF Development 

Project. The Report is available on the web site with the title “Assimilation of precipitation-affected 

SSMIS radiances over land in the ECMWF data assimilation system”. It addressed one of the major 

difficulties in using MW observation over land, i.e. the strongly impacting, poorly known and largely 

variable surface emissivity. 

WP-2451: SSMIS data pre-processing 

SSMIS on DMSP S-16 and onwards includes all window channels of SSM/I, sensitive to surface 

emissivity, and adds absorption bands less sensitive or insensitive to surface. WP-2451 deals with 

extraction and pre-processing of the data of this relatively new sensor, and inputting into the 

assimilation scheme. 

WP-2452: Building surface emissivity maps 

After assimilation in the ECMWF operational NWP model, the impact of surface emissivity is assessed 

and characterised. The work provided indications on the way forward. Possible utilisation of this work 

for improving H-SAF products, particularly PR-OBS-1, will be investigated. 

4.6 Summary description of precipitation products 

Descriptive sheets of precipitation products generated under WP-2000 follow.


PR-OBS-1 

Precipitation rate at ground by MW conical scanners (with indication of phase) 

Product description 

Instantaneous precipitation maps generated from MW images taken by conical scanners on operational satellites in sunsynchronous 

orbits processed soon after each satellite pass. The retrieval algorithm is based on physical retrieval supported by a 

pre-computed cloud-radiation database built from meteorological situations simulated by a cloud resolving model followed by a 

radiative transfer model 

Coverage Strips of ~ 1400 km swath crossing the H-SAF area [25-75°N lat, 25°W-45°E long] in direction approx. S-N or N-S 

Cycle Up to six passes/day at approximately 05:30, 08:00, 09:15, 17:30, 20:00 and 21:15 LST 

Resolution Average: 30 km (computed at 37 GHz) - Best case: 15 km (computed at 90 GHz) 

Accuracy 

Timeliness 

10-20 % (> 10 mm/h), 20-40 % (1-10 mm/h), 50-100 % (< 1 mm/h) - Depending on liquid or solid and land or sea 

Development Phase: within 90 min from the observing time 

Operational Phase: within 15 min from the end of reception if in the acquisition range of Rome; otherwise 90 min 

Dissemination By dedicated lines to centres connected by GTS - By EUMETCast to most other users, especially scientific 

Formats Primary: values in grid points of specified coordinates in the orbital projection - Also JPEG or similar for quick-look 

Satellites and instruments to be used pre-operationally during the Development Phase 

SSM/I on DMSP up to 15 

4 frequencies, 7 channels, resolution 30 km @ 37 GHz, 15 km @ 90 GHz 

SSMIS on DMSP from 16 onward 21 frequencies, 24 channels, resolution 30 km @ 37 GHz, 15 km @ 90 GHz 

Satellites and instruments to be used experimentally during the Development Phase 

TMI on TRMM (South Mediterranean) 5 frequencies, 9 channels, resolution 13 km @ 37 GHz, 6 km @ 90 GHz 

PR on TRMM (South Mediterranean) rain-radar, frequency 13.8 GHz, resolution 4.3 km 

LIS on TRMM (South Mediterranean) lightning mapper, channel at 777.4 nm, resolution 5 km 

AMSR-E on EOS-Aqua 


AMSR-2 on GCOM-W 


Satellites and instruments to be used during the Operational Phase (> 2010) 

SSMIS on DMSP from 16 onward 21 frequencies, 24 channels, resolution 30 km @ 37 GHz, 15 km @ 90 GHz 



CMIS on NPOESS (being re-designed) 66 frequencies, 77 channels, resolution 8 km @ 37 GHz, 4 km @ 90 GHz 

DPR on the “core” GPM satellite rain-radar, frequencies 13.6 and 35.5 GHz, resolution 5 km 

MW radiometers of the GPM (up to 8) 5-7 frequencies, 9-13 channels, resolution 15-30 km @ 37 GHz, 8-15 km @ 90 GHz 

Non-satellite supporting information (ancillary/auxiliary for processing, or used for verification) 

Maps of soil emissivity in MW (in absence, climatology is used) 

Digital Elevation Model 

Data from ground-based lightning networks 

Data from raingauges 

Images from meteorological radar 

Output from NWP models 

Short description of the basic principles for product generation 

Measurements in “atmospheric windows” (SSM/I, TMI, AMSR-E, AMSR-2) - The relationship that links the brightness 

temperature to precipitation has a variable degree of complexity (from minimum at the lower frequencies over the sea to maximum at 

higher frequencies over land), and in addition invariably refers to columnar contents of liquid or ice water. The vertical structure 

necessary for the retrieval is input through the utilisation of a database of radiative cloud/precipitation models previously built by 

means of simulations carried out over real events. The accuracy of the product depends on the representativeness of the database. 

Measurements in both “window” and “absorption” bands (SSMIS, CMIS, some MW radiometers of the GPM constellation) - 

Information on the atmospheric vertical structure is observed by the absorption channels of the instrument itself, thus data quality is 

less dependent on the cloud-radiation database. Also, the observation is more applicable over land because absorption channels 

are less sensitive to surface emissivity. Sensitivity to light rain and snowfall is improved. 

Location of more information 

For the basic algorithms: ATDD-1.0 Part 2 (Precipitation), Chapter 2 (provided by CNR-ISAC) 

For instrument descriptive tablets of SSM/I, SSMIS, AMSR-E / AMSR-2, TMI, PR, LIS, CMIS (before descoping), DPR and one 

advanced GPM radiometer (GMI): Appendix to ATDD-1.0 Part-1


PR-OBS-2 

Precipitation rate at ground by MW cross-track scanners (with indication of phase) 


Instantaneous precipitation maps generated from MW images taken by cross-track scanners on operational satellites in sunsynchronous 

orbits processed soon after each satellite pass. Before undertaking retrieval the AMSU-A resolution is enhanced by 

blending with AMSU-B/MHS. The retrieval algorithm is based on a neural network trained by means of a pre-computed cloudradiation 

database built from meteorological situations simulated by a cloud resolving model followed by a radiative transfer model 

Coverage Strips of ~ 2250 km swath crossing the H-SAF area [25-75°N lat, 25°W-45°E long] in direction approx. S-N or N-S 

Cycle Up to six passes/day at approximately 01:40, 09:30, 10:20, 13:40, 21:30 and 22:20 LST 

Resolution Average along the swath: 40 km - Best case (close to the s.s.p.): 20 km 

Accuracy 20-40 % (> 10 mm/h), 30-60 % (1-10 mm/h), 40-80 % (< 1 mm/h) - Depending on type (convective or stratiform) 

Timeliness 15 min from the end of reception if within the acquisition range of Rome; otherwise 30 min 


Formats Primary: values in grid points of specified coordinates in the orbital projection - Also JPEG or similar for quick-look 


AMSU-A on NOAA and MetOp 15 channels, band 54 GHz, resolution 48 km s.s.p. (~ 16 km after blending with AMSU-B/MHS) 

AMSU-B on NOAA up to 17 5 channels, band 183 GHz, resolution 16 km s.s.p. 

MHS on MetOp and NOAA 18/19 5 channels, band 183 GHz, resolution 16 km s.s.p. 


ATMS on NPP 

22 channels, resolution 32 km @ 54 GHz, 16 km @ 183 GHz 


AMSU-A on NOAA and MetOp 15 channels, band 54 GHz, resolution 48 km s.s.p. (~ 16 km after blending with AMSU-B/MHS) 

MHS on MetOp and NOAA 18/19 5 channels, band 183 GHz, resolution 16 km s.s.p. 

ATMS on NPP and NPOESS 22 channels, resolution 32 km @ 54 GHz, 16 km @ 183 GHz 


Maps of soil emissivity in MW (in absence, climatology is used) 


Data from ground-based lightning networks 

Data from raingauges 

Images from meteorological radar 

Output from NWP models 


MW sensing in “atmospheric windows” (typical instruments: SSM/I, TMI, AMSR-E, AMSR-2 and, with complementary channels in 

absorption bands, SSMIS, CMIS and some MW radiometers of the GPM constellation), attempts to directly observe precipitating 

particles. Surface emissivity represents a strong limitation over land, and the fact that “windows” only observe vertically integrated 

quantities implies that strong support from external sources (e.g., a cloud-radiation database) is needed to provide information on the 

vertical structure of cloud microphysical parameters. In absorption bands exploited for temperature sounding (the 54 GHz band of 

AMSU-A) or for water vapour sounding (the 183 GHz band of AMSU-B and MHS) the effect of surface emissivity is minimised. 

Precipitation that, per sé, represents a “disturb” for these instruments that are designed for all-weather temperature/humidity 

sounding, is retrieved by exploiting the differential effect of liquid drops or ice particles at different frequencies associated to 

weighting functions peaking in different atmospheric layers. It is a highly indirect principle that implies that only part of the retrieval 

process is physically-based, whereas substantial part of the retrieval is currently relying on the use of neural networks. In 

comparison to PR-OBS-01, PR-OBS-02 is expected to perform worse over sea and for intense precipitation, better over land and for 

light precipitation and snowfall. 


For the basic algorithms: ATDD-1.0 Part 2 (Precipitation), Chapter 3 (provided by CNR-ISAC) 

For instrument descriptive tablets of AMSU-A, AMSU-B, MHS and ATMS: Appendix to ATDD-1.0 Part-1


PR-OBS-3 

Precipitation rate at ground by GEO/IR supported by LEO/MW 


Instantaneous precipitation maps generated by IR images from operational geostationary satellites “calibrated” by precipitation 

measurements from MW images in sun-synchronous orbits, processed soon after each acquisition of a new image from GEO 

(“Rapid Update”). The calibrating lookup tables are updated after each new pass of a MW-equipped satellite 

Coverage The rectangular area of the Meteosat field of view that includes the H-SAF area limited to 60° N [i.e. 25-60°N lat 

instead of 25-75°N lat, 25°W-45°E long] 

Cycle 15 min 

Resolution Average over Europe: 8 km (controlled by the IR pixel size) 

Accuracy 40-80 % (> 10 mm/h), 80-160 % (1-10 mm/h), not applicable for low rate (more suitable for convective precipitation) 

Timeliness Within 5 min from the end of (real time) acquisition 


Formats Primary: values in fixed grid points of the Meteosat projection - Also animations of image-like files 


MW, same as for PR-OBS-1 and PR-OBS-2 SSM/I, SSMIS, AMSU-A, AMSU-B, MHS 

Note: product PR-OBS-3 does not perform precipitation retrieval from MW instruments. It uses products PR-OBS-1 and PR-OBS-2 

SEVIRI on Meteosat-8 and follow-on 12 VIS/IR channels, resolution over central Europe 5 km (IR) 

MVIRI on Meteosat up to 7 (initial testing) 3 VIS/IR channels, resolution over central Europe 8 km (IR) 


Same as for PR-OBS-1 and PR-OBS-2 TRMM PR, TMI, LIS; EOS-Aqua AMSR-E, GCOM-W AMSR-2; NPP ATMR 



MW, same as for PR-OBS-1 and PR-OBS-2 SSMIS, GPM MW radiometers, AMSR-2, CMIS, AMSU-A, MHS, ATMS, DPR 




Same as for PR-OBS-1 and PR-OBS-2 (land emissivity, DEM, lightning networks, raingauge networks, images from meteorological 

radar, output from NWP models, ...) 


The relationship linking IR brightness temperature and precipitation is very much indirect, since IR is only sensitive to the cloud top 

structure. Measurements are qualitative and mostly applicable to convective precipitation. After an initial start-up phase of 

NHOURS (NHOURS is a tunable parameter set to 24 h), needed to build meaningful statistical relationships over the entire study 

area), every time that a MW overpass is available, the corresponding IR image is “calibrated” against the precipitation measurement 

from MW. The “calibration” is thereafter propagated to follow-on IR images, till the next MW image is available. Any sort of MW 

image (SSMIS, AMSU, ...) are useful for this purpose and, in effect, any precipitation measurement from any source could be used. 

The “Rapid-update” method is being used operationally in NOAA and experimentally in Europe. It is useful for nowcasting but, for 

hydrological purposes (computation of accumulated precipitation), the quality may be insufficient because of the bias towards 

convective precipitation. 


For the basic algorithms: ATDD-1.0 Part 2 (Precipitation), Chapter 4, Section 4.3.1 (provided by CNR-ISAC) 

For instrument descriptive tablets of SSM/I, SSMIS, AMSR-E / AMSR-2, TMI, PR, LIS, CMIS (before descoping), DPR, one 

advanced GPM radiometer (GMI), AMSU-A, AMSU-B, MHS, ATMS, MVIRI and SEVIRI: Appendix to ATDD-1.0 Part-1


PR-OBS-4 

Precipitation rate at ground by LEO/MW supported by GEO/IR (with flag for phase) 


Instantaneous precipitation maps generated by MW images from operational satellites in sun-synchronous orbits, time-interpolated 

by exploiting the dynamical information observed on IR images from GEO. The algorithm performs the interpolation soon after the 

acquisition of a new image from LEO. This method (“Morphing”) is particularly suited for computing accumulated precipitation of use 

in hydrology. It is also possible to extrapolate the precipitation field for a few steps ahead, with reduced accuracy but improved value 

for nowcasting 

Coverage The rectangular area of the Meteosat field of view that includes the H-SAF area limited to 60° N [i.e. 25-60°N lat 

instead of 25-75°N lat, 25°W-45°E long] 

Cycle Up to 12 times per day, following the availability of fresh MW-derived precipitation retrievals 

Resolution Average over Europe: 8 km intended as sampling, ~ 30 km effective (controlled by the resolution of MW data) 

Accuracy 30-60 % (> 10 mm/h), 50-100 % (1-10 mm/h), 80-160 % (< 1 mm/h) - Depending on type (convective or stratiform) 

Timeliness 20 min after acquisition of a new MW image (5 min after availability of new MW retrievals requiring 15 miin process) 


Formats Primary: values in fixed grid points of the stereographic projection - Also animations of image-like files 





MVIRI on Meteosat up to 7 (initial testing) 3 VIS/IR channels, resolution over central Europe 8 km (IR) 





MW, same as for PR-OBS-1 and PR-OBS-2 SSMIS, GPM MW radiometers, AMSR-2, CMIS, AMSU-A, MHS, ATMS, DPR 




Same as for PR-OBS-1 and PR-OBS-2 (land emissivity, DEM, lightning networks, raingauge networks, images from meteorological 

radar, output from NWP models, ...) 


Frequent IR images from GEO are used to simulate MW images in between actual MW images from LEO. The IR images are used 

as tracers of the precipitation patterns, that are extrapolated forward from the first MW image and backward from the second MW 

image. The simulated MW image is obtained by weighed average of the two. Precipitation is anyway retrieved from the MW image, 

actual or simulated, thus avoiding the (disputable) IR “calibration” process. This method is potentially more suitable for the 

computation of accumulated precipitation. It is still in an experimental stage 


For the basic algorithms: ATDD-1.0 Part 2 (Precipitation), Chapter 4, Section 4.3.2 (provided by CNR-ISAC) 




PR-OBS-5 

Accumulated precipitation at ground by blended MW and IR 


Derived from precipitation maps generated by merging MW images from operational sun-synchronous satellites and IR images from 

geostationary satellites (i.e., products PR-OBS-3 and, in future, PR-OBS-4). Integration is performed over 3, 6, 12 and 24 h. In 

order to reduce biases, the satellite-derived field is forced to match raingauge observations and, in future, the accumulated 

precipitation field outputted from a NWP model 

Coverage The rectangular area of the stereographic projection that includes the H-SAF area [25-75°N lat, 25°W-45°E long] 

Cycle Each 3 hours: MW+IR integrated over the previous 3, 6, 12 and 24 

Resolution Average over Europe: 8 km intended as sampling, ~ 30 km effective (controlled by the resolution of MW data) 

Accuracy From PR-OBS-3 or PR-OBS-4: 40 % (lower bias from PR-OBS-4). More accurate for 24-h than for 3-h integration 

Timeliness At fixed times of the day, within 15 min after synoptic hours (00, 03, 06, 09, 12, 15, 18 and 21 UTC) 


Formats GRIB - Also JPEG or similar for quick-look 



IR, same as for PR-OBS-3 and PR-OBS-4 SEVIRI, MVIRI (initial tests only) 

Note: product PR-OBS-5 does not perform precipitation retrieval. It uses products PR-OBS-3 or PR-OBS-4 





MW, same as for PR-OBS-1 and PR-OBS-2 SSMIS, GMP MW radiometers, AMSR-2, CMIS, AMSU-A, MHS, ATMS, DPR 

IR, same as for PR-OBS-3 and PR-OBS-4 SEVIRI 



Raingauges data from GTS used directly by algorithm, and from others networks used for validation; meteorological radar data 

assimilated by NWP model; QPF output from NWP model 


Product derived by time integration of product PR-OBS-3 and PR-OBS-4 (96 samples/day at 15-min intervals) over 3, 6, 12 and 24 

hours. The product from PR-OBS-4 (i.e. by “Morphing”) should be better (lower bias) than that one from PR-OBS-3, but the latter is 

more prompt since does not have to wait for a fresh MW determination. PR-OBS-4 is considered for use in Version-2. 

Computing accumulated precipitation is not only a simple integration of precipitation intensities but involves some information 

sources like rain gauges data and QPF coming from NWP in order to minimize bias and random errors and to take into account 

orography. The error structure of the precipitation rate measurements is accounted for. Rain gauge data are corrected for surface 

wind effect. Climatological thresholds are applied on the final products to avoid some outliers. 


For the basic algorithms: ATDD-1.0 Part 2 (Precipitation), Chapter 5 (provided by CNMCA) 




PR-ASS-1 

Instantaneous and accumulated precipitation at ground computed by a NWP model 


Fields of precipitation rate and accumulated precipitation generated by a non-hydrostatic operational NWP model (COSMO-ME) to 

provide spatial-temporal continuity to the observed fields otherwise affected by temporal and spatial gaps due to insufficient and 

inhomogeneous satellite cover. The accumulated precipitation is integrated over 3, 6, 12 and 24 h 

Coverage Mid of Development Phase: COSMO-ME [approx. 30-55°N lat., 5°W-35°E lon.] Domain; Last part of Development 

Phase: H-SAF area [25-75°N lat, 25°W-45°E long] 

Cycle Development Phase (Version-1): 12 h – Last part of Development Phase (Version-2): 6 h 

Resolution Grid mesh: 7 km 

Accuracy For 3-h forecast: precipitation rate 50 %, accumulated: 100 %. 

Timeliness At fixed times of the day, 4 h after nominal time of analysis (00, 12)and, in Version-2, 06, 18 UTC) 


Formats Binary output (GRIB) in rotated regular lat-lon grid. - Also standard graphic format for quick-look 

Satellite data to be assimilated pre-operationally during the Development Phase 

Brightness temperatures from AMSU-A and AMSU-B/MHS (on NOAA and MetOp) 

Retrieved winds from ASCAT on MetOp and SeaWinds on QuikSCAT 

Level-2 products (geophysical parameters) from other satellites 

Satellite data to be assimilated experimentally during the Development Phase 

Retrieved temperature profiles from GPS radio-occultation sounders (GRAS on MetOp) 

Level-2 products from IASI sounder on METOP 

Satellite data to be assimilated during the Operational Phase 

Brightness temperatures from AMSU-A and MHS (on NOAA and MetOp), CMIS and ATMS (on NPOESS) 

Retrieved winds from ASCAT on MetOp 

Level-2 products (geophysical parameters) from other satellites 


Large-scale atmospheric conditions from ECMWF 

Observational data from the ground-based component of the Global Observing System including radar 



Assimilation – Synoptic and satellite data from geostationary and sun-synchronous satellites are collected over the NWP model 

integration domain. Through the assimilation process this information is blended in a statistically “optimal” way with the current model 

representation of the atmosphere, thus obtaining an analysed state which gives the best possible estimate of the current atmospheric 

state on the regular grid. 

Forecast - The result of the assimilation process is not a deliverable per-sé, but is only used to initialise the NWP model which is the 

only source of precipitation rain rates and accumulations The product time T0 will be at the two main nominal forecast times (00, 12) 

(six hourly products will be available later on, at the last development stage). Precipitation forecast fields will be provided up to T0+ 

24 h. 

Models - A mesoscale non-hydrostatic model (COSMO-ME) with a resolution of 7 km and full physics parametrizations will be used 

(with 5 category prognostic water condensate). 


For the basic algorithms: ATDD-1.0 Part 2 (Precipitation), Chapter 6, Section 6.3.1 (provided by CNMCA) 

For instrument descriptive tablets of SSM/I, SSMIS, CMIS (before descoping), one advanced GPM radiometer (GMI), AMSU-A, 

AMSU-B, MHS, ATMS, ASCAT, SeaWinds, HIRS, IASI and CrIS: Appendix to ATDD-1.0 Part-1



The diagram below deploys the programme schedule of WP-2000. 




2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

2000 Italy 

2100 Italy 

2110 Italy 

2111 Italy → → ← 

2112 Italy → → ← 

2113 Italy → → ← 

2114 Italy → → ← 

2120 Italy 

2121 Italy → →← →← →← 

2122 Italy → →← →← →← 

2123 Italy → →← → ← → ← 

2124 Italy → → ← → ← 

2130 Italy 

2131 Italy → →← → ← 

2132 Italy → →← → ← →← 

2133 Italy → → ← → ← 

2134 Italy → → ← → ← 

2200 Italy 

2210 Italy 

2211 Italy → →← → ← 

2212 Italy → → ← 

2213 Italy → → ← 

2220 Italy 

2221 Italy → →← → ← 

2222 Italy → →← → ← 

2300 Italy 

2310 Italy 

2311 Italy → →← 

2312 Italy → → ← → ← 

2320 Belgium ← 

2321 Belgium → →← 

2322 Belgium → → ← → ← 

2323 Belgium → → ← 

2330 Germany ← 

2331 Germany → →← 

2332 Germany → → ← → ← 

2333 Germany → → ← 

2340 Hungary ← 

2341 Hungary → →← 

2342 Hungary → → ← → ← 

2343 Hungary → → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

(continue) 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR




Work programme schedule and project events (continuation) 

2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

2350 Italy UniFe ← 

2351 Italy UniFe → →← 

2352 Italy UniFe → → ← → ← 

2353 Italy UniFe → → ← 

2360 Italy DPC ← 

2361 Italy DPC → →← 

2362 Italy DPC → → ← → ← 

2363 Italy DPC → → ← 

2370 Poland ← 

2371 Poland → →← 

2372 Poland → → ← → ← 

2373 Poland → → ← 

2380 Slovakia ← 

2381 Slovakia → →← 

2382 Slovakia → → ← → ← 

2383 Slovakia → → ← 

2390 Turkey ← 

2391 Turkey → →← 

2392 Turkey → → ← → ← 

2393 Turkey → → ← 

2400 Italy 

2410 Italy 

2411 Italy → →← 

2412 Italy → → ← → ← 

2413 Italy → → ← → ← →← → ← 

2420 Italy 

2421 Italy → →← 

2422 Italy → → ← → ← 

2423 Italy → → ← → ← →← → ← 

2430 Italy 

2431 Italy → →← 

2432 Italy → → ← → ← → ← 

2433 Italy → → ← →← → ← 

2440 Italy 

2441 Italy → →← 

2442 Italy → → ← → ← → ← 

2443 Italy → → ← → ← →← → ← 

2450 ECMWF 

2451 ECMWF → →← 

2452 ECMWF → →← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 5 (The soil moisture task) Page 71 

5. The soil moisture task (WP-3000) - Cluster-2 


Remote sensing of soil moisture has been conducted in the thermal and in the microwave domain of the 

electromagnetic spectrum. The thermal approach relies on the coupling of the energy and water fluxes 

at the Earth’s surface and normally uses remotely sensed surface skin temperature to estimate soil 

moisture in a data assimilation approach. This method has been adapted e.g. by the Land-SAF which 

will produce evapotranspiration and soil moisture products at a spatial resolution of 5 km tailored to the 

needs of NWP. For operational hydrology, the thermal approach is not well-suited since cloud cover 

will often impede the observation of the land surface in the infrared domain during flood events. Also, 

hydrologists would like to obtain direct measurements of soil moisture, a condition which is much better 

fulfilled by microwave techniques. 

Scatterometers are active microwave sensors (radar) designed to retrieve wind speed and direction over 

the oceans. However, it is increasingly acknowledged that the unique technical characteristics of the 

sensors are also beneficial for monitoring highly dynamic geophysical processes over land. The ERS 

scatterometers and the MetOp ASCAT are radar operated in C-band. The fundamental reason why any 

microwave technique, and in particular the ERS and MetOp scatterometers, offer the opportunity to 

measure soil moisture in a relatively direct manner is the high sensitivity of microwaves to the water 

content in the soil surface layer due to the pronounced increase in the soil dielectric constant with 

increasing water content. This is specifically the case in the low frequency region (1-10 GHz). The 

benefit of using the ERS and MetOp scatterometers for soil moisture retrieval is their unique sensor 

design, which enables direct accounting for the confounding effects of surface roughness, vegetation 

and dielectric properties. Outstanding sensor characteristics: 1) the multi-incidence angle viewing 

capability which allows separating vegetation and soil moisture effects which both influence the 

measured backscatter coefficient, 2) the high temporal sampling rate which allows monitoring of highly 

dynamic processes such as the soil moisture process, and 3) the excellent radiometric accuracy which 

results in a low noise level and allows analysing multi annual time series. 

WBS-08 displays the structure of WP-3000 up to the 3 rd level WP’s. In this Chapter the work plan will 

be described up to 4 th level. In the Appendix WPD’s are provided for 1 st , 2 nd and 3 rd level WP’s. 

WP-3000 

Soil moisture 


WP-3100 

Surface soil moisture 


WP-3200 

Volumetric soil moisture 

ECMWF 

WP-3300 


Austria + Several 

WP-3400 

Product development 

Austria + Several 

WP-3110 


ZAMG + EUMETSAT 

WP-3210 

Assimilation system 

for ERS 

WP-3310 


Tu-Wien 

WP-3410 

Global product 

Tu-Wien 

WP-3120 



WP-3220 

Assimilation system 

for ASCAT 

WP-3320 

Validation in Austria 

Tu-Wien 

WP-3420 

Regional product 

Tu-Wien 

WP-3130 

Q. C. and distribution 


WP-3330 


IRM 

WP-3430 


ECMWF 

WP-3340 

Validation in ECMWF 

ECMWF 

WP-3350 

Validation in France 

CETP 

WP-3440 

Synergy with SMOS 

CESBIO 

WBS-08 - WBS of WP-3000: 1 st , 2 nd and 3 rd level WP’s. 4 th level WP’s defined in next sections.


The three soil moisture products are generated by a structure that involves four components: 

• the Institut für Photogrammetrie und Fernerkundung (IPF) of the Technische Universität Wien (TU- 

Wien) for development of all surface soil moisture products (SM-OBS-1 and SM-OBS-2); 

• the EUMETSAT central Product Processing Facility (PPF) for the routine generation of the global 

product SM-OBS-1; 

• the Zentral Anstalt für Meteorologie und Geodynamik (ZAMG) for the routine generation of the 

regional (disaggregated) product SM-OBS-2; and as (partial) backup of the PPF for generating SM- 

OBS-1; 

• the European Centre for Medium-range Weather Forecasts (ECMWF) for development and routine 

generation of the volumetric soil moisture product SM-ASS-1. 

Fig. 14 shows the logical connections among the various components. During the routine phase, the 

MetOp ASCAT data are acquired in EUMETSAT and processed to generate the Global product that is 

disseminated via EUMETCast. This option has been adopted in view of the expressed interest of 

several EUMETSAT member countries to have the large-scale product extended to the whole globe 

instead of to the H-SAF area only. However, ZAMG retains the capability of generating the large-scale 

product over the limited H-SAF area in case of need. In addition, the EUMETSAT product will benefit 

of developments and validation results stemming from the H-SAF activity. 

MetOp 

EUMETCast 

Level-1 

Level-0 

Level-2 

Level-1 

Level-2 

Level-2 

CDA & EARS EUMETCast EUMETCast 

Level-2 nominal 

Level-1 backup 

EUMETSAT 


SM-OBS-1 (Level-2) 

generated and 

distributed in 

Near-Real-Time 

ZAMG 


SM-OBS-2 generated 

from Global product 

(also SM-OBS-1 backup 

limited to Europe) 

Level-2 

(backup) 

EUMETCast 

ECMWF 

SM-ASS-1 

generated by 

assimilation of 

SM-OBS-1 

Provision of software and 

database for the Global product 

Development and improvement 

of the disaggregated product 

Quality control 

TO 

USERS 

TU-Wien 

Land cover, 

DEM 

Precipitation, 

snow, 

temperature 

Fig. 14 - Conceptual architecture of the soil moisture production chain.


Fig. 15 highlights the main components of the soil moisture generation chain. 

Fig. 15 - Main components of the soil moisture product generation chain. 

5.2 Observation of surface soil moisture (WP-3100) 


There will be two types of surface soil moisture products: 

• SM-OBS-1: Global surface soil moisture by radar scatterometer 

• SM-OBS-2: Regional surface soil moisture by radar scatterometer. 

As mentioned earlier, SM-OBS-1, in normal conditions, will be generated at the EUMETSAT 

Headquarters, with ZAMG only acting as backup for the limited H-SAF area, whereas SM-OBS-2 will 

be generated at ZAMG with assistance from TU-Wien for software implementation and maintenance of 

the auxiliary files. 

WBS-09 displays the structure of WP-3100. Although the Global product is actually generated in 

EUMETSAT, mention is kept in the WBS and, when appropriate, in the follow-on text for convenience.


WP-3100 



WP-3110 

Acquisition and pre-processing 

ZAMG 

WP-3111 

Global product from EUMETSAT 

ZAMG 

WP-3112 

Level-1 ASCAT data (backup) 

ZAMG 

WP-3113 

Acquisition of auxiliary data 

Tu-Wien 

WP-3120 

Product generation 

ZAMG 

WP-3121 

Global product generation (backup) 

ZAMG 

WP-3122 

Support for regional product 

TU-Wien 

WP-3123 

Regional product generation 

ZAMG 

WP-3130 


ZAMG 

WP-3131 


TU-Wien 

WP-3132 


ZAMG 

WP-3133 


ZAMG 


The two products are implemented sequentially, as shown in Fig. 16. 

MetOp 

ASCAT 

Global parameter 

database 

ASCAT Processing 

Chain 

European 

parameter 

database 

SM-OBS-1 – Global surface soil 

moisture by radar scatterometer 

Disaggregation 

process 

Additional 

datasets 


SM-OBS-2 – Regional surface soil moisture 

by radar scatterometer 


Fig. 16 - Surface soil moisture products generation chain. 

The TU-Wien method for retrieving soil moisture from ERS scatterometer data is, from its conception, a 

change detection method. Instantaneous backscatter measurements are extrapolated to a reference 

incidence angle (taken at 40°) and are compared to dry and wet backscatter references. 

The influence of vegetation is determined by exploiting the multi-incidence angle viewing capabilities 

of the ERS scatterometer sensors. As a result, time series of the topsoil moisture content m s (< 5 cm)


are obtained in relative units ranging between 0 (dry) and 1 (saturated). Compared to ERS, data from 

ASCAT will provide improved resolution (25 km instead of 50 km) and twice frequent coverage (two 

500-km swaths on the left-hand and right-hand sides of the sub-satellite track instead of one 500-km 

swath of ERS). 

The soil moisture information as recorded by the ERS and MetOp scatterometers does not come equally 

from all areas within the sensor footprint. Some areas, such as bare soil surfaces, grassland or 

agricultural fields, exhibit a very high sensitivity of the measured backscattering coefficient to soil 

moisture, while other, such as dense forest or rocks, none. As a result the relevant soil moisture 

information in the 25/50 km surface soil moisture products only comes from soil moisture-sensitive 

areas within these pixels. Since hydrologists normally run their models on a much finer spatial scale 

they need to be informed about where the soil moisture information can be applied, and where not. 

Therefore it is foreseen to disaggregate the 25/50 km scatterometer products to 1 km products, taking 

topography and land cover data into account. The disaggregated 25 km ASCAT surface soil moisture 

product is thus a product sampled at 1 km intervals, where soil moisture information is only supplied 

over soil moisture-sensitive land cover types. This product is corrected for topography and projected to 

user-defined coordinate systems. 

Fig. 17 shows the main data flow feature in the surface soil moisture processing chain. 

Fig. 17 - Data flows within the soil moisture product generation chain of Austrian responsibility. 


The MetOp ASCAT data for the soil moisture generation purpose should be available in real-time via 

the A-HRPT system, or in real-real-time through EARS (exploiting A-HRPT) and EUMETCast. 

Unfortunately, the A-HRPT transmitter on MetOp-1 failed, thus until MetOp-2 is launched, ASCAT 

data will be acquired at the EUMETSAT Command and Data Acquisition station (CDA) at Svalbard 

and re-transmitted via EUMETCast. The ASCAT coverage obtained in 24 hours is shown in Fig. 18. 

It is noted that full coverage of the European latitudes is achieved each 36 hours.


Fig. 18 - ASCAT coverage in 24 h. The close-to-nadir 700-km gap 

in between the two 500-km lateral swaths is not shown. 

WP-3111: Global product from EUMETSAT 

In the nominal scheme, the Global surface soil moisture product (SM-OBS-1) is generated at the 

EUMETSAT PPF and disseminated by EUMETCast. ZAMG will acquire this Level-2 product and 

form the files for the generation of the Regional surface soil moisture product (SM-OBS-2). 

WP-3112: Level-1 ASCAT data (backup) 

ZAMG will retain the capability of acquire Level-1 ASCAT data by EUMETCast for backing the 

EUMETSAT chain in case of delay of the EUMETSAT product to be ready for Version-1 release or, 

later, in case the EUMETSAT product fails to meet some user requirement (e.g., for timeliness). 

WP-3113: Acquisition of auxiliary data 

For the purpose of generating SM-OBS-2, due to the sensitivity of backscatter measurements to 

different surface conditions, auxiliary data such as land cover data and digital terrain models will have 

to be acquired to serve as important supplementary information (e.g. to obtain the specific scattering 

characteristics of the land surface). These data need to be procured, quality-checked and updated (where 

necessary). 


The objective of WP-3120 is to generate the following soil moisture products (see Fig. 16): 

• SM-OBS-1: Global surface soil moisture by radar scatterometer 

• SM-OBS-2: Regional surface soil moisture by radar scatterometer. 

Fig. 19 shows a rough outline of the algorithmic steps that are necessary to generate the H-SAF surface 

soil moisture products (Global and Regional/disaggregated).


Fig. 19 - Logic of the soil moisture extraction algorithm. 

WP-3121: Global product generation (backup) 

The Global surface soil moisture product (SM-OBS-1) will be generated at the EUMETSAT PPF on the 

base of algorithms developed and tested by TU-Wien in past years to process AMI-SCAT data from 

ERS-1 and ERS-2, now adapted to ASCAT. Software integration will take place at EUMETSAT, with 

some support from TU-Wien. Exactly the same software will be possible to run at the ZAMG premises. 

The purpose of this backup activity may be either limited to the initial phases, in case the EUMETSAT 

product is late (i.e., to meet the demonstrational product release deadline), or extended to the preoperational 

phase in case the EUMETSAT fails to meet some H-SAF user requirement (e.g., timeliness). 

The backup activity is limited to the coverage of the H-SAF area. 

WP-3122: Support for regional product 

The Regional (or “disaggregated”) product (SM-OBS-2) is being developed specifically for the H-SAF 

hydrological community. The development (at TU-Wien) will be a long-standing activity, and 

transportation to ZAMG for implementation in an operational environment will be assisted by TU-Wien. 

Even after, assistance will be necessary to keep updated the necessary auxiliary files.


WP-3123: Regional product generation 

ZAMG will operationally run the Regional (or disaggregated) product (SM-OBS-2) generation chain on 

the available facilities, keep in-line and update/upgrade the facilities whenever necessary, maintain data 

quality (by exploiting the validation activity under WP-3300) and distribute the products after quality 

control (see WP-3130). 


The best strategy against errors in the input data has to be elaborated (e.g. how far the input data can 

deviate from nominal quality before the surface soil moisture product generation is suspended). Also 

under the heading of "Quality Control" is the derivation of appropriate quality flags, in case the 

validation activities using external data sets indicate problems in the soil moisture retrieval due to e.g. 

snow, freezing, topography, inundation and wetland dynamics. 

WP-3131: Development of Quality Control procedures 

Soil moisture output generated offline is to be monitored. It is of particular interest to study the 

behaviour of the product where input data is known to be non-conformal (according to MetOp 

operations bulletins). Quality Control software routines to deal with identified problems will be 

programmed. This WP defines rules, procedures and protocols backing the online and offline quality 

control activity, taking into consideration the product error structures, the applicability of the processing 

algorithm in respect of the type of soil, the status of cal/val, the availability of auxiliary data for quality 

control, etc.. The appropriate quality control procedures are developed by the Unit responsible of the 

product development activity. 


This WP collects the auxiliary data to be used for on-line quality control (precipitation, snow, 

temperature, …; see Fig. 19) and implements the procedures generated by WP 3131 on each product 

generated in WP-3100 before its distribution. 


This WP refers to the operational chain to disseminate the Soil Moisture Products and Q.C. information 

in real-time (by dedicated links) or near-real-time (by EUMETCast through CNMCA and EUMETSAT) 

or off-line (from the central archive). A semi-automatic control is applied to monitor the broadcasting 

status. A semi-automatic system is applied to recover from service interruptions and provide delivery in 

differed time. 

5.3 Observation of volumetric soil moisture (WP-3200) 


Root zone soil moisture is not directly observable on large spatial scales, which necessitates the 

development of an indirect approach: satellite-derived surface soil moisture, 2-m temperature and 

relative humidity, and information from a physical land surface model will be combined to analyse the 

soil water content of the top 100-cm soil layer. A simplified extended Kalman filter (EKF) will be used 

to obtain statistically optimal estimates based on the error characteristics of the observations and the 

model. The analysed soil moisture fields will be available on a regular grid for three layers (0-7 cm, 7- 

21 cm, and 21-100 cm depths). 

The prototype of the surface data assimilation system will be developed using ERS-derived surface soil 

moisture. When the product derived from ASCAT becomes available in near-real-time (PR-OBS-1 

generated by EUMETSAT) the system will be adapted to the new data and tested. 

WBS-10 shows the Work Breakdown Structure of WP-3200. The flow chart of the processing chain is 

shown in Fig. 20.


WP-3200 


ECMWF 

WP-3210 

Assimilation system for ERS 

WP-3211 

Observation operators 

WP-3212 

Modification of the data assimilation system 

WP-3213 

Computation of ERS based soil moisture profiles 

WP-3220 

Assimilation system for ASCAT 

WP-3221 

Operational (passive) monitoring 

WP-3222 

Computation of ASCAT soil moisture based profiles 

WP-3223 

Operational implementation 

WP-3214 

Initial product validation 


OFF-LINE ERS-1/2 

REAL-TIME ASCAT 

Pre-processing 

chain 


index 

Operational 



index 

Static bias correction 

CDF matching 

Daily surface soil 

moisture fields (grib) 

Adaptive bias correction 

(CDF based) 

BUFR 

Observation file 

Corrected soil 

moisture fields 

Observation 

errors 

Daily modelled soil 

moisture fields (grib) 

Feedback 

files 

Corrected soil 

moisture fields 

Modelled first guess 

(‘internal’ data) 

Off-line 

SDAS / EKF 

Root zone 

soil moisture 

Operational IFS 

SDAS / EKF 

Root zone 

soil moisture 

Fig. 20 - Flow chart of the root zone soil moisture processing chain. 

5.3.2 Assimilation system for ERS (WP-3210) 

ERS derived surface soil moisture has already been available for an extended period. The global data set 

is quite ideal to develop and implement the production chain for the H-SAF root zone soil moisture. 

First results will be available in time for the H-SAF Hydrological validation programme (WP-5000).


WP 3211: Observation operators 

For applications in BLUE (Best Linear Unbiased Estimate) analysis systems (e.g. Kalman filtering, 

4DVar), systematic differences between the modelled first guess and the observation have to be 

corrected. Cumulative distribution function (CDF) matching is one potential method to correct for the 

bias and differences in the higher moments in the soil moisture distributions obtained from the model 

and the scatterometer data. 

The exact form of the observation operators derived through CDF matching will strongly depend on the 

results obtained from the data comparison (see WP-3340). It can be assumed that different regions 

require different observation operators. In addition, it may well be that the form of the observation 

operators depends on time (i.e. seasonal variability). It has to be noticed that the observation operators 

depend on the spatial resolution of the individual data sets and the number of data available. 

Observation operators derived for the analysis of ERS / re-analysis data can not necessarily be used for 

the analysis of ASCAT / operational IFS data. However, once a set of observation operators is defined 

the global swath data will be adjusted for assimilation applications and archived in BUFR format. 

WP 3212: Modification of the data assimilation system 

The H-SAF root zone soil moisture demonstration product will be based on ERS derived surface soil 

moisture and the Integrated Forecast System at ECMWF. For the ‘historic’ (i.e. not near real time) ERS 

data the data assimilation system will be run offline. Full assimilation experiments using the 

atmospheric 4DVar analysis are too time consuming and computationally expensive to be run for 

extended time periods. A ‘hydrology assimilation suite’ (HAS) tailored to the H-SAF applications will 

be developed. The ‘hydrology assimilation suite’ will run 24-hour forecast experiments to obtain the 

first guess. To initialize the forecast, atmospheric analysis fields from the archive will be used. Only 

volumetric soil moisture fields will be used from the previous days HAS analyses to allow the system to 

propagate information on the state of the land surface. 10-day forecasts will be performed once a day 

based on atmospheric fields from the archive and analysed soil moisture. 

The building of this suite comprises three main tasks: 

• The ‘hydrology assimilation suite’ will be set up using ECMWF’s Supervisor Monitor Scheduler. 

• The ‘swath’ based observations from the adjusted BUFR data files will be matched with the 

corresponding model fields. The collocation software will be developed and implemented. It is 

envisaged to interpolate observations to the reduced Gaussian model grid. 

• Including a new observation type for the extended Kalman filter (EKF) requires significant technical 

changes to the operational software. Basically, new fields for the observed variables will be 

introduced in the IFS and the rank of vectors and matrices involved in the EKF computations will be 

adjusted. 

WP 3213: Computation of ERS based soil moisture profiles 

The hydrology assimilation suite will be run for an extended period covering at least 2 months during 

northern hemispheric spring / summer. Soil moisture profiles will be archived and distributed for further 

validation and impact studies. 

WP 3214: Initial product validation 

The soil moisture profiles generated in WP-3213 are compared against the profiles from the operational 

forecasts and independent in-situ observations from the Global Soil Moisture Data Base. It is planned to 

focus on regional networks operating a number of stations (e.g. the Oklahoma Mesonet, Ukraine, the 

Illinois network, or the future French SMOSMANIA network). Average values for these regions match 

the spatial scale of the numerical model. 

5.3.3 Assimilation system for ASCAT (WP-3220) 

From early 2008 onwards, ASCAT derived surface soil moisture will be available in near real time 

(NRT). The work covered through WP-3220 will comprise the operational monitoring of the NRT


satellite data and modifications of the ERS prototype data assimilation system. ASCAT based root zone 

soil moisture will be produced with the Integrated Forecast System. If the impact of the ASCAT data on 

the forecast is positive the operational surface analysis will be introduced in operations. 

WP 3221: Operational (passive) monitoring 

Near real time (NRT) soil moisture derived from ASCAT will be available at the beginning of 2008. A 

processing chain for the BUFR data will be established for operational monitoring of the soil moisture 

fields. The collocation software developed for the ‘hydrology assimilation suite’ is implemented in the 

operational forecast system. The modelled soil moisture values are compared against the ASCAT 

derived soil moisture in NRT. Departure statistics will be derived on a regular basis. It will be checked 

if the observation operators derived for ERS / re-analysis data are transferable to ASCAT / IFS. Based 

on the monitoring results new observation operators will be derived if necessary. 

WP 3222: Computation of ASCAT soil moisture based profiles 

Once a reliable set of observation operators is established, the Integrated Forecast System will be run for 

an extended period covering at least 2 months during northern hemispheric spring / summer. Soil 

moisture profiles will be archived and distributed for further validation and impact studies. The impact 

of the ASCAT data on the weather forecast will be analysed and standardized skill scores will be 

compared against the ones obtained from the operational forecast. 

WP 3223: Operational implementation 

If the evaluation of the forecast experiments (WP 3222) is positive, i.e. ASCAT derived surface soil 

moisture data improve the soil moisture analysis and results in a neutral to positive impact on the 

forecast quality, the NRT data will be used operationally. 

5.4 Soil moisture products validation (WP-3300) 


Validation is a hard work in the case of soil moisture, the main problem being the large difference 

between the scales of satellite-derived data and ground observation systems. The H-SAF user 

requirements in terms of frequency of coverage (and friendly data access, not to be forgotten) have led 

to select instruments such as ASCAT only providing resolution of some 25 km (though the 

“disaggregated” Regional product is sampled at 1-km intervals). Ground-based observations (e.g. by 

Time Domain Reflectometers, TDR) are very punctual, and very sparse (generally on special test sites). 

Comparison with results of numerical models obviously suffer of the limited skill of NWP in predicting 

soil moisture (a very downstream product that passes through quantitative precipitation forecast, that 

certainly is not the most accurate product of NWP). A mixture of several techniques is generally used, 

and the results change with the climatic situation and the status of soil. 

For the validation of global soil moisture products generated by H-SAF, no specific ground truth data is 

available and no distinct validation datasets exist. Therefore, the only way to perform validation of 

products is the comparison of various datasets. 

The objective of WP-3300 is to support soil moisture products quality by: 





WBS-11 shows that four H-SAF participants cooperate to the validation programme, under the 

leadership of Austria (TU-Wien).


WP-3300 


Austria (TU-Wien) 

WP-3310 


Tu-Wien 

WP-3320 

Validation in Austria 

Tu-Wien 

WP-3330 


IRM 

WP-3340 

Validation in ECMWF 

ECMWF 

WP-3350 

Validation in France 

CETP 

WP-3311 

Validation 

methods 

WP-3321 

Tools & 

structures 

WP-3331 

Tools & 

structures 

WP-3341 

Tools & 

structures 

WP-3351 

Tools & 

structures 

WP-3312 

Reporting 

& analysis 

WP-3322 

Support to 

calibration 

WP-3332 

Support to 

calibration 

WP-3342 

Support to 

calibration 

WP-3352 

Support to 

calibration 

WP-3323 


WP-3333 


WP-3343 


WP-3353 








Since the nature of remote-sensed precipitation observation differs substantially from that one of ground 

based systems (e.g., TDR), comparison of the two measurements requires a number of preventive 

operations to bring them to consistency (upscaling, downscaling, etc.). This WP defines which ground 

tools have to be used and how to make the comparison, including consideration of both mechanical 

comparisons suitable to build statistics (performance indexes) essential for product characterisation, and 

focused exercises (supervised) intended to understand the reasons of differences, particularly useful for 

calibration. 







3400) for improving calibration; 



monitoring and WP-3130 for quality control). 


Four Units will participate to the validation activities, in three Countries plus ECMWF. They have 

taken active role in defining the validation philosophy (WP-3310) and operate in close coordination 

both among themselves and with the Units in charge of products development (WP-3400). In each 

Country or Unit the work programme may be slightly different in respect of both the available tool and


the adopted methodology. However, for the sake of simplicity, only three type of WP’s are described 

below. 

WP 3321, 3331, 3341 and 3351: Tools and structures 

Tools (soil moisture station networks, Global Soil Moisture Data Bank, Time Domain Reflectometers, 

model outputs, …) and structures (existing networks, special test sites, …) will be either made available 

or tuned or modified or installed on-purpose to support validating H-SAF soil moisture products. 

WP 3322, 3332, 3342 and 3352: Support to calibration 





campaigns and, sometimes, special tools, will be utilised. 

WP 3323, 3333, 3343 and 3353: Characterisation 




situations and the different response of remote sensing tools to different types of soil, characterisation 

will take a long time, presumably till the end of the H-SAF Development Project. Only limited 

characterisation will be available at the time of demonstrational products release, substantially more at 

the time of the second release (pre-operational products). Validation will be run routinely, therefore 

mostly basing on operational tools. Methods will be based on categorisation. Data performances will 

be analysed for selected classes and geographic/climatic/seasonal situations by essentially automatic 

methods, to provide standard quality indexes. 





so as to generate “demonstrational products”, i.e. representative data to activate the Hydrological 

validation programme (Cluster-4); then development will continue so as to progressively improve data 

quality and release “pre-operational products” at about 3.5 years, and a final release of “operational 

products” at the end of the Development Phase. 






[Note 2 - The titles of the WP’s are now closely associated to the products to be delivered]. 

[Note 3 - In PP-1.0 there was a voluntary contribution from Italy, concerning experimental products 

from AMSR-E and several types of SAR. This contribution, not budgeted under H-SAF, has been 

withdrawn though, if interesting results come out, H-SAF members will be duly informed]. 

WBS-12 deploys the structure of WP-3400, lead by the TU-Wien Institut für Photogrammetrie und 

Fernerkundung (IPF), the scientific partner of ZAMG for H-SAF purposes.


WP-3400 

Product development 


WP-3410 


Tu-Wien 

WP-3420 


Tu-Wien 

WP-3430 


ECMWF 

WP-3440 

Synergy with SMOS 

CESBIO 

WP-3411 

Updating off-line 

global parameters 

WP-3421 


& improvement 

WP-3431 

Surface data assimilation 

system development 

WP-3441 

SMOS data acquisition 

and analysis 

WP-3412 

Improving 

retrieval & calibration 

WP-3422 

Off-line generation of 

regional parameters 

WP-3432 

Surface data assimilation 

system updating 

WP-3442 

Comparison of SMOS 

and H-SAF products 

WP-3423 

Regional soil moisture 

retrieval & calibration 



Algorithm Theoretical Definition Document (ATDD). Exception is WP-3440, that is not intended to 

generate a deliverable product. The version of ATDD aligned to this PP-2.0 is ATDD-1.0, delivered to 

the CDR at the same time. 

5.5.2 Global surface soil moisture (WP-3410) 

The Global surface soil moisture product (SM-OBS-1) will be actually generated at the EUMETSAT 

PPF. The algorithm was originally developed and tested by TU-Wien, and will continue to be possibly 

improved in connection with the H-SAF activity, as feedback from the hydrological validation activity 

over Europe (WP-5000) and possibly from the development of the Regional product (SM-OBS-2). 

WP-3411: Updating off-line global parameters 

With the increasing quantity of available ASCAT data, statistics will continuously augment and the 

database of global parameters supporting the soil moisture retrieval algorithm will progressively grow. 

Also, the H-SAF Hydrological validation programme will be instrumental to extend the database of 

global parameters. 

WP-3412: Improving retrieval & calibration 

As a consequence of the development of the Regional product (SM-OBS-2) TU-Wien will improve their 

local prototype software generating ASCAT surface soil moisture. It is expected that this will indicate 

areas of the Global product retrieval chain that can be improved, and provide indication for revising or 

re-calibrating the algorithm. 

5.5.3 Regional surface soil moisture (WP-3420) 

The Regional surface soil moisture product (SM-OBS-2) is a new H-SAF development. 

[Note: in PP-1.0 products SM-OBS-1 and SM-OBS-2 were reported as a single product in two versions. 

Now we use different names to follow a recommendation of the PDR Board]. 

The development implies an intensive off-line preparation of auxiliary data necessary for the 

disaggregation process, and thereafter a product generation chain to run in an operational environment. 

It is noted that the Regional soil moisture product (SM-OBS-2) is targeted for the second products 

release timeframe (at T 0 + 42).



The product is derived by disaggregating the global product (SM-OBS-1) generated at the EUMETSAT 

PPF and disseminated via EUMETCast. The disaggregation process makes use of a fine-mesh layer 

pre-computed and stored in a database. The fine-mesh information includes ground-based 

measurements and SAR imagery from Envisat ASAR operating in the ScanSAR Global-monitoring 

Mode (GM). The disaggregated product, sampled at km-scale, enables better fitting of local information 

to better suite hydrological requirements. 

WP-3422: Off-line generation of regional parameters 

The disaggregation method could, e.g., be based upon the CORINE land cover or other European land 

cover data sets. The disaggregated products may be validated with C-band backscatter data acquired 

with the Global-monitoring Mode of the Envisat Advanced Synthetic Aperture Radar (ASAR), where 

recent research findings indicate that a useful downscaling layer can be computed. However, currently 

not enough ASAR GM data are available over Europe, which means that this validation approach 

depends on the future acquisition schedule of Envisat. 

WP-3423: Regional soil moisture retrieval & calibration 

Main steps of the Regional surface soil moisture retrieval process are: 

• Step 1: Restoring the European parameter database; 

• Step 2: Reading of the global soil moisture product; 

• Step 3: Disaggregation by correlation with 1-km scale information from the European database; 

• Step 4: Resampling to European projection; 

• Step 5: Product data type constitution; 

• Step 6: Quality flag generation from auxiliary datasets. 

5.5.4 Volumetric soil moisture (WP-3430) 

Currently, the ECMWF’s Integrated Forecast System is being updated up to four times a year. These 

updates comprise changes of the physical model, the numerical scheme, the data assimilation system, 

and the implementation of new observations. Whenever the surface data assimilation system, which 

computes the root zone soil moisture analysis, is affected through these regular updates the quality of 

the H-SAF product will be checked. It is noted that the Volumetric soil moisture product (SM-ASS-1) 

is targeted for the second products release timeframe (at T 0 + 42). 

WP 3431: Surface data assimilation system development 

Direct changes to the assimilation system will be necessary whenever new observations (e.g. SMOS 

brightness temperatures or GRACE derived soil water content) are introduced in the analysis or the 

analysis system itself changes (e.g. the surface analysis may be integrated in the atmospheric 4DVar 

analysis). It will be ensured that the ASCAT data can be used in any new version of the forecast system 

and the quality of the root zone soil moisture analysis will be checked. 

WP 3432: Surface data assimilation system updating 

Changes in the Forecast System may affect the surface data assimilation system indirectly (e.g. changes 

in the cloud parameterizations may result in improved precipitation forecast) or directly (e.g. new 

parameterizations in the land surface model may result in improved dry down dynamics). Consequently, 

it may be necessary to adjust the model and / or observation errors in the surface analysis. Through WP 

3432 it will be ensured that the quality of the H-SAF product is as high as possible. 

5.5.5 Use of SMOS for soil moisture products development (WP-3440) 

The objective of WP-3440 is to compare SMOS-derived soil moisture with H-SAF products as 

generated by Austria (WP-3100) and ECMWF (WP-3200). Since it operates in L-band (1.4 GHz), 

SMOS will be sensing soil moisture in the presence of vegetation, significant of the roots region. It will


therefore support the efforts to characterise the H-SAF products generated on the base of data from 

operational satellites (specifically MetOp ASCAT) and modelling (at ECMWF). 

WP-3441: SMOS data acquisition and analysis 

The SMOS Level-2 soil moisture products will be acquired as from 2008-2009. Soil moisture products 

obtained from SMOS and MetOp-ASCAT as well as the soil moisture simulated by ECMWF will be regridded 

in order to obtain the three products on the same grid at the European scale. 

WP-3442: Comparison between SMOS and H-SAF soil moisture products 

SMOS level 2 data will be compared with H-SAF soil moisture products with a focus on Europe. The 

following features will be considered: 

● Spatial features of surface soil moisture products from SMOS and ASCAT and ECMWF model, will 

be compared for different seasons. 

● Dynamics of soil moisture will compared between the three products at the monthly, seasonal, and 

annual scales. 

● The effect of vegetation water content on the retrieved surface soil moisture products of both SMOS 

and ASCAT will be analysed by comparison with the ECMWF surface soil moisture. This analysis 

will be performed for spring and autumn where the vegetation phenology is significant. 

5.6 Summary description of soil moisture products 

Descriptive sheets of soil moisture products generated under WP-3000 follow.


SM-OBS-1 

Global surface soil moisture by radar scatterometer 


Global maps of the soil moisture content in the surface layer (0.5-2 cm) generated from the MetOp scatterometer (ASCAT) 

processed soon after each satellite orbit completion. It is a coarse-resolution product (25 km), controlled by the instrument IFOV. It 

is run at the EUMETSAT Headquarters on the base of algorithms and software developed by TU-Wien prior to the start of H-SAF, 

and connected to H-SAF for validation over the European area and feedback for further improvement. The algorithm is supported by 

a global database, specifically recording vegetation, and is based on change detection 

Coverage Strips of 1000 km swaths covering in succession the whole globe 

Cycle 36 hours for full coverage over Europe 

Resolution 25 km, constant through the field of view 

Accuracy 0.05 m 3 m -3 , degrading in the presence of forest, mountains, rock outcrops, water surfaces, urban areas 

Timeliness 130 min (potentially 30 min using the EARS service) 

Dissemination By EUMETCast 

Formats BUFR 


MetOp ASCAT 

5.3 GHz (C-band), resolution 50 and 25 km, basic sampling 12.5 km 


ERS-1/2 AMI-SCAT 5.3 GHz (C-band), resolution 50 and 25 km (after reprocessing) 

Satellites and instruments to be used during the Operational Phase 

MetOp ASCAT 



Soil, land cover and vegetation maps 


Data from meteorological networks 

Soil moisture networks 


The ERS-1/2 and MetOp scatterometers offer the opportunity to measure soil moisture in a relatively direct manner because of the 

high sensitivity of microwaves to the water content in the soil surface layer due to the pronounced increase in the soil dielectric 

constant with increasing water content. This is specifically the case in the low frequency region (1-10 GHz). However, scattering 

from land surfaces also depends on other factors (vegetation, surface roughness). The benefit of using the ERS and MetOp 

scatterometers for soil moisture retrieval is their unique sensor design, which enables direct accounting for the confounding effects of 

surface roughness, vegetation and dielectric properties. Outstanding sensor characteristics are: 

a. the multi-incidence angle viewing capability which allows separating vegetation and soil moisture effects which both influence the 

measured backscatter coefficient; 

b. the high temporal sampling rate which allows monitoring of changes in the highly variable soil wetness conditions through a 

change detection approach (while surface roughness can be assumed to be constant at this spatial scale); 

c. the excellent radiometric accuracy which results in a low noise level and allows analysing multi annual time series. 


For the basic algorithms: ATDD-1.0 Part 3 (Soil moisture), Chapter 2 (provided by TU-Wien) 

For instrument descriptive tablets of AMI-SCAT and ASCAT: Appendix to ATDD-1.0 Part-1


SM-OBS-2 

Regional surface soil moisture by radar scatterometer 


Derived from the global product SM-OBS-1 limited to the H-SAF area. Maps of the soil moisture content in the surface layer (0-2 

cm) generated from the MetOp scatterometer (ASCAT) processed shortly after each satellite orbit completion. Unlike SM-OBS-1, 

which is generated in the EUMETSAT H/Q, this product is generated in Austria (ZAMG). The algorithm performs disaggregation of 

the global-scale product (25 km resolution), to 1-km sampling, making use of pre-computed database of disaggregation parameters 

Coverage Strips of 1000 km swath crossing the H-SAF area [25-75°N lat, 25°W-45°E long] 

Cycle 36 hours 

Resolution Basic 25 km, constant through the field of view; sampling 1 km 

Accuracy 0.05 m 3 m -3 , degrading in dependence of the presence of vegetation 

Timeliness 135 min (potentially 35 min using the EARS service) 

Dissemination By dedicated lines to centres connected by GTS - By EUMETCast to most other users, especially scientific ones 

Formats Values in grid points in the orbital projection or fixed latitude-longitude grid 


MetOp ASCAT 


Envisat ASAR (for database) 5.3 GHz (C-band), resolution 1 km (ScanSAR Global Mode), global coverage in 5 days 




MetOp ASCAT 


GMES Sentinel 1 (for database) Follow-on of Envisat ASAR, being currently defined 



Snow maps 


Data from meteorological networks 

Soil moisture networks 


The product is derived by disaggregating the global product (SM-OBS-1) generated at the EUMETSAT H/Q and disseminated via 

EUMETCast. The disaggregation process makes use of a fine-mesh layer pre-computed and stored in a database. The fine-mesh 

information includes ground-based measurements and SAR imagery from Envisat ASAR operating in the ScanSAR Global Mode. 

The disaggregated product, sampled at km-scale, enables better fitting of local information to better suite hydrological requirements 


For the basic algorithms: ATDD-1.0 Part 3 (Soil moisture), Chapter 3 (provided by TU-Wien) 

For instrument descriptive tablets of AMI-SCAT, ASCAT and ASAR: Appendix to ATDD-1.0 Part-1


SM-ASS-1 

Volumetric soil moisture (roots region) by scatterometer assimilation in NWP model 


Analysed volumetric soil moisture content for four different soil layers (covering the root zone from the surface to 2 metres) 

generated by the ECMWF soil moisture assimilation system at 24-hour time steps. The analysed soil moisture fields are based on a 

modelled first guess, the screen-level temperature and humidity analyses, and the ASCAT-derived surface soil moisture (product 

SM-OBS-1) generated by EUMETSAT and distributed by EUMETCast 

Coverage Global 

Cycle 24 hours (intended as interval between successive model outputs to be disseminated) 

Resolution ~50 km (conditioned by the motion scale correctly described by the model for such type of variable) 

Accuracy To be assessed 

Timeliness 36 h (due to the need to assimilate data observed in the 6-30 hours preceding start of the operational run) 

Dissemination By dedicated lines to centres connected by GTS including ZAMG 

Formats Values in fixed points of reduced Gaussian or latitude / longitude grids 


MetOp ASCAT 





MetOp ASCAT 




Orography derived from Digital Elevation Model 

Atmospheric analyses from ECMWF’s operational Integrated Forecast System 

Conventional SYNOP station data, soil moisture observations from regional networks 


The soil moisture assimilation scheme of ECMWF is currently being upgraded towards an extended Kalman filter, making use of 

observations containing information relevant to root zone soil moisture. This variational method, which is based on the Best Linear 

Unbiased Estimate (BLUE) theory, will be used to constrain the 24-hour forecast of soil moisture on any point of the Gaussian grid to 

be as close as possible to all observations. BLUE systems require an accurate representation of the random errors for the first guess 

(i.e. short-range forecast) and for each type of observations. Each information source is weighed in an inversely proportional ratio to 

its error in the final product, thereby delivering an optimally interpolator to the actual value of soil moisture. To obtain statistically 

optimal estimates, systematic differences between the modelled first guess and the individual observations have to be minimized. 

Observation operators will be developed to correct for biases and to transform the surface soil moisture index into model equivalent 

volumetric soil moisture. Because of the relatively long window used for the variational method (24-hour), the result is available 6 to 

36 hours after observation time. The quality of the product will be validated against in-situ soil moisture profiles from selected 

regional networks. 


For the basic algorithms: ATDD-1.0 Part 3 (Soil moisture), Chapter 4 (provided by ECMWF) 

For instrument descriptive tablets of AMI-SCAT, ASCAT: Appendix to ATDD-1.0 Part-1







2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

3000 Austria 

3100 Austria 

3110 Austria 

3111 Austria → →← → ← 

3112 Austria → →← →← 

3113 Austria → →← → ← 

3120 Austria 

3121 Austria → →← →← 

3122 Austria → → ← →← →← 

3123 Austria → → ← → ← 

3130 Austria 

3131 Austria → →← → ← 

3132 Austria → → ← → ← 

3133 Austria → → ← → ← 

3200 ECMWF 

3210 ECMWF 

3211 ECMWF → →← 

3212 ECMWF → →← 

3213 ECMWF → →← 

3214 ECMWF → →← 

3220 ECMWF 

3221 ECMWF → →← 

3222 ECMWF → →← 

3223 ECMWF → → ← → ← 

3300 Austria 

3310 Austria 

3311 Austria → →← 

3312 Austria → → ← → ← 

3320 Austria ← 

3321 Austria → →← 

3322 Austria → → ← → ← 

3323 Austria → → ← → ← 


3331 Belgium → →← 

3332 Belgium → → ← → ← 

3333 Belgium → → ← → ← 

3340 ECMWF ← 

3341 ECMWF → →← 

3342 ECMWF → → ← → ← 

3343 ECMWF → → ← → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

(continue) 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR





2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

3350 France ← 

3351 France → →← 

3352 France → → ← → ← 

3353 France → → ← → ← 

3400 Austria 

3410 Austria 

3411 Austria → →← 

3412 Austria → → ← → ← 

3420 Austria 

3421 Austria → →← 

3422 Austria → → ← → ← 

3423 Austria → → ← → ← →← → ← 

3430 ECMWF 

3431 ECMWF → →← 

3432 ECMWF → → ← → ← → ← 

3440 France 

3441 France → →← 

3442 France → → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 6 (The snow task) Page 92 

6. The snow observation task (WP-4000) - Cluster-3 


Snow can have a high impact on people's everyday lives. Extensive snow accumulation can cause 

troubles in traffic (cars, trains, airplanes, delivery trucks ...). In certain areas seasonal flooding cause 

damage to e.g. crop lands and residential areas. Flood forecasting can be done using hydrological 

models, where snow parameters such as fractional snow cover and snow water equivalent are used as 

inputs. The hydrological models are used also in hydro power industry for discharge estimation. 

Albedo of snow is very high and therefore has a big effect in the radiation balance. This in turn is an 

important parameter in weather forecasting (especially during the melting season, when the changes are 

rapid) and in climatological models. 

Snow is used as a tourist attraction, especially in alpine and northern regions. All these aforementioned 

points have also a direct or indirect economical connection. 

In most parts of the world seasonal short term variations in stream-flow reflect variations in rainfall only. 

However, at higher latitudes and altitudes where more precipitation falls as snow, runoff depends on 

heat supply for snowmelt rather than the timing of precipitation. The hydrological importance of snow is 

not restricted to areas where it lies for months: many dry-land rivers in areas with little or no snow are 

fed largely by melt-water from high mountains many kilometres away. Snowmelt water is therefore an 

immensely important water resource in many parts of the world for public supply, hydropower, irrigated 

agriculture and other uses. Much of the value of melt-water as a resource lies in its reliable occurrence at 

a particular time of the year and enhanced, if total runoff and timing can be predicted. Accurate 

forecasting can also minimize risk and loss from floods caused by rapid snowmelt. Hydrologists have 

therefore devoted much effort to developing models to simulate and forecast snowmelt runoff. 

Traditionally, input to hydrological models is obtained from point measurements of precipitation and 

temperature at the meteorological stations whereby supported by direct observations of the snow pack 

when possible. 

Historically hydrologists relied mostly on conventional data network systems based on manual ground 

measurements. As the technological progress brought new impulses, automatic meteorological stations 

furnished real-time data from remote mountain areas, which was particularly important for snow 

hydrology. However, ground based observations can by necessity only represent a small part of the 

region of interest creating problems in basins with pronounced topography because of the high spatial 

variability of hydro-meteorological parameters. Snow cover mapping in mountainous areas is 

demanding due to the interfering topography and the heterogeneous ground properties. With the 

growing number of satellite platforms and improvements in processing and transmission of digital data 

obtained from them, it has become possible to obtain frequent snow cover information in near real-time 

through a variety of different sources. Retrieving snow products from satellite data is still a challenging 

task. Sparse ground network due to the rough topography, heterogeneity in snow distribution, the effects 

of slope, aspect, land use, wind and some other factors in the accumulation and melting periods of snow 

make the retrieving of snow products from satellite data difficult. 

Under the leadership of Finland, several countries participate to the activity of Cluster-3. WBS-13 

displays the structure of WP-4000 up to the 3 rd level WP’s. In this Chapter the work plan will be 

described up to 4 th level. In the Appendix WPD’s are provided for 1 st , 2 nd and 3 rd level WP’s.


WP-4000 


Finland (FMI) 

WP-4100 

Flat lands, forests 

Finland (FMI) 

WP-4200 

Mountains 

Turkey (TSMS) 

WP-4300 

Products Validation 

Finland + Several 

WP-4400 

Product developments 

Finland + Several 

WP-4110 


FMI 

WP-4210 


TSMS 

WP-4310 


FMI 

WP-4410 

Snow recognition 

FMI 

WP-4120 


FMI 

WP-4220 


TSMS 

WP-4320 


IMR 

WP-4420 


METU 

WP-4130 


FMI 

WP-4230 


TSMS 

WP-4330 

Validation in Finland 

FMI 

WP-4430 


NMA 

WP-4340 

Validation in Germany 

BfG 

WP-4350 

Validation in Poland 

IMWM 

WP-4440 

Snow status 

TKK 

WP-4360 

Validation in Turkey 

METU 

WP-4450 

Effective snow cover 

SYKE 

WP-4460 

Effective snow cover 

METU 

WP-4470 

Snow water equivalent 

TKK 

WP-4480 

Snow water equivalent 

METU 

WBS-13 - WBS of WP-4000: 1 st , 2 nd and 3 rd level WP’s. 4 th level WP’s defined in next sections. 

It may be observed that the generation of snow parameters is split between Finland and Turkey. Finland 

is responsible of flat lands and forested areas, Turkey for mountainous areas. 

6.2 Observation of snow parameters in flat/forested areas (WP-4100) 


Snow parameters in flat and forested areas will be produced by Finland. The following products will be 

generated: 

• SN-OBS-1: Snow detection (snow mask) by VIS/IR radiometry 

• SN-OBS-2: Snow status (dry/wet) by MW radiometry 

• SN-OBS-3: Effective snow cover by VIS/IR radiometry 

• SN-OBS-4: Snow water equivalent by MW radiometry. 

A number of Finnish Institutes will cooperate to the task, under the overall responsibility of FMI. 

WBS-14 displays the WP’s up to the 4 th level.


WP-4100 

Flat lands and forests 

Finland (FMI) 

WP-4110 


FMI 

WP-4111 


FMI 

WP-4112 

Non-meteorological satellites 

FMI 

WP-4113 


FMI 

WP-4120 


FMI 

WP-4121 


FMI 

WP-4122 


FMI, SYKE, TKK 

WP-4123 


FMI 

WP-4124 

Operations 

FMI 

WP-4130 


FMI 

WP-4131 


FMI, SYKE, TKK 

WP-4132 


FMI 

WP-4133 


FMI 


The conceptual architecture of WP-4100 is shown in Fig. 21, that is the subject of separate documents: 

the “System requirements document” (SRD) and the “System design document” (SDD). 

MODIS 

AVHRR 

SEVIRI 

AMSR-E 

SSM/I 

ASCAT 

MODIS 

AVHRR 

Temperature 

Snow depth 

Nearrealtime 

satellite 

data 

archive 

Satellite 

direct 

acquisition 

Synoptic 

weather 

database 

Product 

generation 

Land use 

data, 

DEM, GIS 


Eumetsat 

members 

and cooperating 

states 

Fig. 21 - Conceptual architecture of the snow product generation chain in Finland. 

Fig. 22 shows the main subsystem components relevant to snow product generation. Each satellite has 

its own real-time data acquisition system for local reception. Near-real-time satellite data from 

EUMETSAT are retrieved via the EUMETCast system. Other satellite data are retrieved with ftp 

connection from NASA or NOAA. Synoptic data for real-time use comes from the FMI's real-time 

database. Archived data for development and validation will be taken from ECMWF archives. End 

products will be stored locally and delivered via web interface to end users and via ftp to EUMETSAT.


Fig. 22 - Main subsystem components of the snow product generation chain in Finland. 

Fig. 23 shows the relationships between satellite data and output products. 

SN-OBS-2 – Snow status 

recognition 

SN-OBS-3 – Effective snow cover 

Fig. 23 - Relationships between satellite data and snow output products.




well as ancillary and auxiliary data necessary to generate snow products. Certain data from R&D 

satellites are acquired from NASA via ftp. 







The orbital positions and earth’s coverage of the MW instruments on NOAA, MetOp and DMSP 

satellites for have been previously shown in Fig. 12. Fig. 24 shows the coverage of the optical 

instrument (AVHRR and MODIS) on NOAA, MetOp, EOS-Terra and EOS-Aqua. 

AVHRR coverage in 6 h by 

NOAA-17, NOAA-18 and 

MetOp-1 

MODIS coverage in 

9 h by EOS-Terra and 

EOS-Aqua 

Fig. 24 - Coverage from AVHRR (in 6 hours) and MODIS (in 9 hours) during the Development Phase. 

In may be seen that there is a rather regular and complete coverage of Europe from AVHRR each 6 h 

and MODIS each 9 h. 




be acquired either by direct readout in real-time, or in near-real-time by EUMETCast. AVHRR from 

NOAA and MetOp is acquired both by direct-read-out and EUMETCast. SEVIRI from Meteosat is 

acquired by EUMETCast. SSM/I and SSMIS from DMSP might not be actually used during the 

Development Phase, at least until AMSR-E is available from EOS-Aqua. In case of need, they will be 

acquired via ftp from the UKMO. Pre-processors for all these instruments are available. 

WP-4112: Non-meteorological satellites 

The activity addresses data from R&D satellites, specifically EOS Terra and Aqua. MODIS from both 

Terra and Aqua is acquired both by direct-read-out and via ftp from NASA. AMSR-E from Aqua 

exhibits problem for direct-read-out, and is preferably acquired via ftp. NASA-provided pre-processors 

are available.


WP-4113: Acquisition of ancillary data 


products retrieval, always for on-line quality control. Synoptic observations including snow depth are 

accessible from the FMI database and from ECMWF MARS database. Snow course measurements 

from Finland are available from the SYKE database several months after the summer (typically in 

September). Snow parameters generated by the HIRLAM and ECMWF NWP models are available 

from FMI and ECMWF databases. Snow maps generated by the Land Surface Analysis SAF are 

available from the LSA-SAF database. 


The objective of WP-4120 is to generate the following precipitation products (see Fig. 23): 


• SN-OBS-2: Snow status (dry/wet) by MW radiometry 



The products will be generated starting from algorithms selected or developed internally to FMI (SN- 

OBS-1) or by SYKE (SN-OBS-3) or by TKK (SN-OBS-2 and SN-OBS-4). The developmental 

activities are described under Section 6.5 (WP-4400). The software is implemented at FMI with support 

from SYKE and TKK as their algorithms are concerned. 



various instruments with the products generation chain. It implies: 





SYKE and TKK, responsible of development and testing of the algorithms backing the generation of 

most products (see WP-4400), will provide the necessary databases and assist FMI for the integration of 

software originally developed in a research environment, on the operational facilities in use at FMI; and 

will participate to software validation activities. 


FMI, in cascade from the acquisition and pre-processing systems (see WP-4110), will (with SYKE and 

TKK support; see WP-4122) install the databases, algorithms and codes provided by SYKE and TKK or 

developed at FMI on the available processing facilities, implement the software and perform testing and 

validation. 


FMI will operationally run the snow products generation chain on the available facilities, keep in-line 

and update/upgrade the facilities whenever necessary, maintain data quality (by exploiting the validation 

activity under WP-4300) and distribute the products after quality control (see WP-4130). 






taking into consideration the product error structures, the applicability of the processing algorithm in


respect of the type of snow and geographical situation, the status of cal/val, the availability of auxiliary 

data for quality control, etc.. The appropriate quality control procedures are developed by the Units 

responsible of the product development activity. 


This WP collects the auxiliary data to be used for on-line quality control (in-field snow measurements, 

meteorological information from weather stations, output of NWP, …) and implements the procedures 

generated by WP 4131 on each product generated in WP-4100 before its distribution. 


This WP refers to the operational chain to disseminate the snow products and Q.C. information in realtime 

(by dedicated links) or near-real-time (by EUMETCast through CNMCA and EUMETSAT) or offline 

(from the central archive). A semi-automatic control is applied to monitor the broadcasting status. A 

semi-automatic system is applied to recover from service interruptions and provide delivery in differed 

time. Before delivery, FMI will combine the products from Finland (flat/forested areas) and Turkey 

(mountainous areas) in a single file (see also WP-4233). 

6.3 Observation of snow parameters in mountainous areas (WP-4200) 


The products from Finland are committed for flat and forested areas, generally in northern-central 

Europe. In mountainous areas the products will be generated by Turkey and sent to Finland for 

combination and delivery. The following snow products will be generated over mountainous areas: 




Product SN-OBS-2 (Snow status by MW radiometry) will not be generated in mountainous areas. 

WBS-15, very similar to WP-14 valid for Finland, displays the WP’s of 4200 up to the 4 th level. 

WP-4200 

Mountains 

Turkey (TSMS) 

WP-4210 


TSMS 

WP-4211 


TSMS 

WP-4212 

Non-meteorological satellites 

TSMS 

WP-4213 


TSMS 

WP-4220 


TSMS 

WP-4221 


TSMS 

WP-4222 


METU 

WP-4223 


TSMS 

WP-4224 

Operations 

TSMS 

WP-4230 


TSMS 

WP-4231 


METU 

WP-4232 


TSMS 

WP-4233 


TSMS 



The conceptual architecture of WP-4200 is shown in Fig. 25, similar to Fig. 21 valid for Finland. 

Fig. 25 - Conceptual architecture of the snow product generation chain in Turkey. 

Fig. 26 shows the logic of the snow product generation chain in Turkey. As for the relationships 

between satellite data and snow output products, reference is made to Fig. 23, except that product SN- 

OBS-2 will not be generated in mountainous areas. 

Fig. 26 - Logic of the snow product generation chain in Turkey.




well as ancillary and auxiliary data necessary to generate snow products. Certain data from R&D 

satellites are acquired from NASA via ftp. 







As for the coverage of the satellites and instruments to be used, reference is made to Fig. 12 (SSM/I- 

SSMIS) and Fig. 24 (AVHRR and MODIS) 




be acquired either by direct readout in real-time, or in near-real-time by EUMETCast. AVHRR from 

NOAA and MetOp is acquired both by direct-read-out and EUMETCast. SEVIRI from Meteosat is 

acquired by EUMETCast. SSM/I and SSMIS from DMSP are acquired via ftp from the UKMO. Preprocessor 

for real-time AVHRR is available, data from EUMETCast and UKMO are already preprocessed. 

WP-4212: Non-meteorological satellites 

The activity addresses data from R&D satellites, specifically EOS Terra and Aqua. MODIS from both 

Terra and Aqua and AMSR-E from Aqua are acquired via ftp from NASA. A direct-read-out station for 

EOS Terra/Aqua will be installed at TSMS in the second part of the H-SAF Development Phase. 

NASA-provided pre-processors are available. 

WP-4213: Acquisition of ancillary data 


products retrieval, always for on-line quality control. Various types of observations made available by 

different institutions will be used. For instance, State Hydraulic Works will be in charge of providing 

the discharge and ground truth observations in the basins. Meteorological observations will be mainly 

provided by the currently operational sites in the basins and those planned to be deployed by TSMS in a 

near future. In addition, other observation sites located in the vicinity of the basins will be used 

whenever needed. 


The objective of WP-4220 is to generate the following snow products (see Fig. 23): 




The products will be generated starting from algorithms selected or developed by the Middle-East 

Technical University (METU). The developmental activities are described under Section 6.5 (WP- 

4400). The software is implemented at TSMS with support from METU. 



various instruments with the products generation chain. It implies:






METU, responsible of development and testing of the algorithms backing the generation of all products 

(see WP-4400), will provide the necessary databases and assist TSMS for the integration of software 

originally developed in a research environment, on the operational facilities in use at TSMS; and will 

participate to software validation activities. 


TSMS, in cascade from the acquisition and pre-processing systems (see WP-4210), will (with METU 

support; see WP-4222) install the databases, algorithms and codes provided by METU on the available 

processing facilities, implement the software and perform testing and validation. 


TSMS will operationally run the snow products generation chain on the available facilities, keep in-line 

and update/upgrade the facilities whenever necessary, maintain data quality (by exploiting the validation 

activity under WP-4300) and distribute the products after quality control (see WP-4230). The products 

will refer to mountainous areas, and be complementary to those generated by Finland to cover flat and 

forested areas. 






taking into consideration the product error structures, the applicability of the processing algorithm in 

respect of the type of snow and geographical situation, the status of cal/val, the availability of auxiliary 

data for quality control, etc.. The appropriate quality control procedures are being developed by METU, 

responsible of the product development activity. 


This WP collects the auxiliary data to be used for on-line quality control (in-field snow measurements, 

meteorological information from weather stations, output of NWP, …) and implements the procedures 

generated by WP 4231 on each product generated in WP-4200 before its distribution. 


This WP refers to the operational chain to disseminate the snow products and Q.C. information. A 

semi-automatic control is applied to monitor the broadcasting status. A semi-automatic system is 

applied to recover from service interruptions and provide delivery in differed time. The products will be 

addressed to FMI for assembling the composite product to cover both flat/forested and mountainous 

areas. After that, FMI will provide for distribution in real-time (by dedicated links) or near-real-time 

(by EUMETCast through CNMCA and EUMETSAT) or off-line (from the central archive). 

6.4 Snow products validation (WP-4300) 


Validation of snow observation from space is a hard work, especially because ground systems are 

essentially based on in-field measurements, very sparse and of punctual nature. Comparison with 

results of numerical models obviously suffer of the limited skill of NWP in predicting snow parameters


(a very downstream product that passes through quantitative precipitation forecast, that certainly is not 

the most accurate product of NWP). A mixture of both techniques is generally used, and the results 

change with the climatic situation and the status of soil. 

The objective of WP-4300 is to support snow products quality by: 





WBS-16 shows that five H-SAF participants cooperate to the validation programme, under the 

leadership of Finland (FMI)). 

WP-4300 


Finland (FMI) 

WP-4310 

Valid. philosophy 

FMI 

WP-4320 

Valid. in Belgium 

IRM 

WP-4330 

Valid. in Finland 

FMI 

WP-4340 

Valid. in Germany 

BfG 

WP-4350 

Valid. in Poland 

IMWM 

WP-4360 

Valid. in Turkey 

METU 

WP-4311 

Validation 

methods 

WP-4321 

Tools & 

structures 

WP-4331 

Tools & 

structures 

WP-4341 

Tools & 

structures 

WP-4351 

Tools & 

structures 

WP-4361 

Tools & 

structures 

WP-4312 

Reporting 

& analysis 

WP-4322 

Support to 

calibration 

WP-4332 

Support to 

calibration 

WP-4342 

Support to 

calibration 

WP-4352 

Support to 

calibration 

WP-4362 

Support to 

calibration 

WP-4323 


WP-4333 


WP-4343 


WP-4353 


WP-4363 








Since the nature of remote-sensed snow observation differs substantially from that one of ground based 

systems, comparison of the two measurements requires a number of preventive operations to bring them 

to consistency (upscaling, downscaling, etc.). This WP defines which ground tools have to be used and 

how to make the comparison, including consideration of both mechanical comparisons suitable to build 

statistics (performance indexes) essential for product characterisation, and focused exercises 

(supervised) intended to understand the reasons of differences, particularly useful for calibration. 







4400) for improving calibration;




monitoring and WP’s 4130 and 4230 for quality control). 


Five Units will participate to the validation activities, in five Countries. They have taken active role in 

defining the validation philosophy (WP-4310) and operate in close coordination both among themselves 

and with the Units in charge of products development (WP-4400). In each Country or Unit the work 

programme may be slightly different in respect of both the available tool and the adopted methodology. 

However, for the sake of simplicity, only three type of WP’s are described below. 

WP 4321, 4331, 4341, 4351 and 4361: Tools and structures 

Tools (synoptic weather station snow e-codes, snow e-codes from other weather stations, global snow 

datasets, output of NWP and hydrological models, …) and structures (existing networks, special test 

sites, …) will be either made available or tuned or modified or installed on-purpose to support 

validating H-SAF snow products. 

WP 4322, 4332, 4342, 4352 and 4362: Support to calibration 





campaigns and, sometimes, special tools, will be utilised. 

WP 4323, 4333, 4343, 4353 and 4363: Characterisation 




situations and the different response of remote sensing tools to different types of soil, characterisation 

will take a long time, presumably till the end of the H-SAF Development Project. Only limited 

characterisation will be available at the time of demonstrational products release, substantially more at 

the time of the second release (pre-operational products). Validation will be run routinely, therefore 

mostly basing on operational tools. Methods will be based on categorisation. Data performances will 

be analysed for selected classes and geographic/climatic/seasonal situations by essentially automatic 

methods, to provide standard quality indexes. 





so as to generate “Version-1 products”, i.e. representative data to activate the Hydrological validation 

programme (Cluster-4); then development will continue so as to progressively improve data quality and 

release Version-2 products at about 3.5 years, and a final release at the end of the Development Phase. 






[Note 2 - The titles of the WP’s are now closely associated to the products to be delivered].


[Note 3 - In PP-1.0 there was a voluntary contribution from Italy, concerning experimental products 

from AMSR-E and several types of SAR. This contribution, not budgeted under H-SAF, has been 

withdrawn though, if interesting results come out, H-SAF members will be duly informed]. 

WBS-17 deploys the structure of WP-4400, lead by the FMI. It is noted that, for three of the four snow 

products, there are two similar WP’, one from one of the Finnish institutes referring to flat/forested 

areas, one from METU referring to mountainous areas. However, the corresponding products generated 

by FMI and TSMS will be combined before distribution, as explained under WP’s 4133 and 4233. 

WP-4400 

Product developments 

Finland (FMI) 

WP-4410 

Recognition 

FMI 

WP-4420 

Recognition 

METU 

WP-4430 

Recognition 

NMA 

WP-4440 

Snow status 

TKK 

WP-4450 

Snow cover 

SYKE 

WP-4460 

Snow cover 

METU 

WP-4470 

Water equiv. 

TKK 

WP-4480 

Water equiv. 

METU 

WP-4411 

Ingestion 

model 

WP-4421 

Ingestion 

model 

WP-4431 

Composite 

RGB 

WP-4441 

Ingestion 

model 

WP-4451 

Ingestion 

model 

WP-4461 

Ingestion 

model 

WP-4471 

Forward 

model 

WP-4481 

Forward 

model 

WP-4412 

Recognition 

model 

WP-4422 

Recognition 

model 

WP-4432 

Comparison 

& analysis 

WP-4442 

Retrieval 

model 

WP-4452 

Retrieval 

model 

WP-4462 

Retrieval 

model 

WP-4472 

Assimilation 

model 

WP-4482 

Assimilation 

model 

WP-4413 

Calibration 

& follow-on 

WP-4423 

Calibration 

& follow-on 

WP-4443 

Calibration 

& follow-on 

WP-4453 

Calibration 

& follow-on 

WP-4463 

Calibration 

& follow-on 

WP-4473 

Calibration 

& follow-on 

WP-4483 

Calibration 

& follow-on 





[Note - WP-4430, that is implemented by a Visiting Scientist from Romania in FMI, is recorded in this 

PP-2.0 but not in ATDD-1.0 since there is a dedicated document for it: the Report of the Visiting 

Scientist]. 

6.5.2 Snow recognition (WP-4410 and WP-4420) 

Snow recognition is based on optical sensors, basically AVHRR, MODIS and SEVIRI. The product is 

an output of image classification processing. The snow signature is recognised as differential brightness 

in more short-wave channels, intended to discriminate snow from no-snowed land and snow from 

clouds. Both radiometric signatures are used (specifically, the 1.6 µm channel as compared with others), 

and time-persistency (for cloud filtering by the “minimum brightness” technique applied over a 

sequence of images). The Meteosat/SEVIRI contribution is mostly for southern Europe (including 

mountainous regions) and minimum brightness technique application. For mountainous regions 

multispectral threshold technique implemented on VIS and IR satellite reflectance values is used in 

order to get maximum daily snow coverages. 

WP’s 4411 and 4421: Ingestion model 

These initial WP’s will perform reporting of images from different sensors (SEVIRI, AVHRR and 

MODIS) on a single geometry, correction for Sun zenith angle (and atmospheric, if necessary, that does 

not seem the case), land/water masking, conversion of radiances of short-wave channels into reflectance 

and of thermal IR into equivalent blackbody temperature.


WP’s 4412 and 4422: Recognition model 

The key problem of snow recognition is to discriminate snow from clouds. The cloud mask will be built 

by means of multi-channel thresholding techniques, also accounting for the daily evolution of the scene 

brightness (retention of “minimum brightness” pixels, likely to be cloud-free). For pixels classified as 

“cloud free”, a second multi-channel thresholding process will be applied to distinguish likely snow 

from snow-free land. The product will finally be edited as a binary map. 

WP’s 4413 and 4423: Calibration and follow-on developments 

The product development activity will continue by incorporating the results of validation campaigns to 

calibrate thresholds and improve corrections so as to maximise the Probability Of Detection (POD) and 

minimise the False Alarm Rate (FAR). 

6.5.3 Complementary investigation on Snow recognition (WP-4430) 

This WP is being implemented by a Visiting Scientist from Romania (NMA) operating at FMI. The 

main objective is to extend to central Europe the snow recognition methodology originally developed 

for northern latitudes. 

WP-4431: Use of composite RGB techniques 

This WP operates on SEVIRI images, whose channels will be used for driving the Red, Green and Blue 

guns of a colour monitor. This enables to rapidly appreciate the effect of changing thresholds, with the 

help of the dynamical information from image animation that allows easy detection of interfering clouds. 

WP-4432: Comparisons and analysis of different methods 

The RGB-based method will be used for comparisons with the baseline H-SAF methods (WP’s 4410 

and 4420) and the snow recognition method used in the SAF for Land Surface Analysis (LSA-SAF). 

The focus will be on the performance over Central Europe. 

6.5.4 Snow status (WP-4440) 

Snow status (wet or dry) is observed in the MW range. Currently, the best instrument is AMSR-E on 

EOS-Aqua, but SSM/I-SSMIS also could be used, though providing much worse resolution. The 

product is only elaborated in Finland by TKK, thus mountainous areas are for the moment not 

considered. In the microwave range, snow emissivity is substantially different for dry and wet snow, 

therefore snow status observation is a relatively straightforward application, also facilitated by the allweather 

capability. The emissivity substantially increases when snow is wet, enabling detection of snow 

status. Middle frequencies are used (19 and 37 GHz). The recognition of dry snow for snow pack 

shallower than 80 mm is unreliable due to high penetration depth of microwaves in dry snow. The 

algorithm as stand-alone is unable to discriminate wet snow from bare ground, thus wet snow status is 

recorded only for those locations where Snow detection (product SN-OBS-1) has revealed snow or there 

has been dry snow in the preceding sequence of products. 

WP- 4441: Ingestion model 

This initial WP’s will perform reporting of images from different sensors (AMSR-E and SSMI/-SSMIS) 

on a single geometry, and introduce the land-water mask. 

WP- 4442: Retrieval model 

The retrieval will be based on rather simple combinations of channels. However, since the measurement 

is affected by the snow depth, change detection with time also will be used. The product will finally be 

edited as a binary map. However, since dry snow of shallow depth is transparent and cannot be 

discriminated from land, the product will only be mapped there where product SN-OBS-1 (snow 

recognition) has detected snow.


WP-4443: Calibration and follow-on developments 

The product development activity will continue to incorporate the results of validation campaigns by 

calibrating thresholds and improve corrections so as to maximise the Hit Rate (HR) and minimise the 

False Alarm Rate (FAR). 

6.5.5 Effective snow cover (WP-4450 and WP-4460) 

Effective snow cover is based on optical sensors, basically AVHRR, MODIS and SEVIRI. The SN- 

OBS-3 product differs from SN-OBS-1 in so far as, in the snow cover map, the resolution elements 

report the fractional snow coverage instead of being binary (snow/snow-free). The possibility of 

appreciating fractional coverage stems from the lack of observed brightness in respect of what would be 

if the pixel were fully filled by snow. The forest canopy obscuring the full visibility to the ground is 

accounted for by applying certain a priori transmissivity information, which must be generated using 

satellite-borne reflectance data acquired under full dry snow cover conditions. These reflectances must 

be measured by the same instrument which is used in the fractional snow coverage estimation. This 

means that the product can be generated for areas where full dry snow cover stays at least for some 

period and that during that period, cloud-free reflectance data are gained. Since the transmissivity 

approach may not work well for bare ground and vegetated lands (different from forest area) on 

mountainous regions, a sub-pixel reflectance model is used. The topographic normalization is performed, 

in order to eliminate the terrain effects on the reflectances of the features in the mountainous regions. 

WP’s 4451 and 4461: Ingestion model 

These initial WP’s will perform reporting of images from different sensors (SEVIRI, AVHRR and 

MODIS) on a single geometry, correction for Sun zenith angle, land/water masking, atmospheric 

corrections, conversion of radiances of short-wave channels into reflectance and of thermal IR into 

equivalent blackbody temperature, and topographic correction in mountainous areas. The transmissivity 

maps will be pre-computed by historical records and kept updated. 

WP’s 4452 and 4462: Retrieval model 

The effective cover will be retrieved moving from PR-OBS-1, that identifies the pixels classified as 

snow. The actual reflectance will be converted into effective cover by making use of the pre-computed 

transmissivity maps. The product will finally be edited as a map of effective cover (percent) with pixellevel 

sampling. 



calibrate thresholds and improve corrections. The effect of tilted terrain and different land use types 

will be investigated. The applicability of scatterometric data from MetOp ASCAT also will be studied. 

6.5.6 Snow water equivalent (WP-4470 and WP-4480) 

Snow water equivalent is observed in the MW range. Currently, the best instrument is AMSR-E on 

EOS-Aqua, but SSM/I-SSMIS also could be used, though providing much worse resolution. 

Microwaves are sensitive to snow thickness and density, convoluted in the snow water equivalent. 

Depending on the snow being dry or wet, the penetration changes (dry snow is more transparent). High 

frequencies are required for dry snow, which is an advantage from the resolution viewpoint. However, 

with increasing snow depth, lower frequencies are necessary for better penetration, thus a multifrequency 

approach is required. It is an all-weather, night-and-day measurement, whose processing 

requires considerable support from ancillary information. Method and performance may be different for 

flat/forested areas and mountainous regions. The potential capability of radar scatterometry also will be 

assessed. Method and performance may be different for flat/forested areas and mountainous regions. 

The variation of snow density and snow characteristics in terms of grain size with respect to elevation 

and time scale are considered in the method for mountainous regions. It is noted that the Snow Water 

Equivalent product (SN-OBS-4) is targeted for the second products release timeframe (at T 0 + 42).


WP’s 4471 and 4481: Forward model 

Generation of SWE requires heavy help from ground-based measurements and pre-computations to 

build a first guess field. A snow emission model developed at TKK will be used to simulate the 

expected brightness temperatures at selected AMSR-E or SSM/I-SSMIS frequencies. The input 

parameters of the TKK model include the snow pack characteristics (depth, density, effective grain size 

and temperature), soil properties (temperature, dielectric constant and effective rms height variation), 

forest canopy characteristics (stem volume/biomass) and near-surface air temperature controlling 

atmospheric emission and transmissivity contributions. 

WP’s 4472 and 4482: Assimilation model 

The satellite brightness temperatures actually observed over the locations of ground observing stations 

will first be used to estimate the effective grain size. This information will be utilised for interpolating a 

background field from the ground observations. Thereafter, an assimilation process will force the 

satellite-observed field and the simulated background field to match each other. 



calibrate thresholds and improve corrections. The effect of tilted terrain and different land use types 

will be investigated. The applicability of scatterometric data from MetOp ASCAT also will be studied. 

6.6 Summary description of snow products 

Descriptive sheets of snow products generated under WP-4000 follow.


SN-OBS-1 

Snow detection (snow mask) by VIS/IR radiometry 


Binary map of snow / no-snow situation. VIS/IR images from GEO are used. The product may be processed in different ways and 

have different quality depending on the surface being flat, forested or mountainous. The algorithm is based on thresholding of 

several channels of SEVIRI, the most important being those in short-wave, thus the product is generated in daylight. In order to 

search for cloud-free pixels, multi-temporal analysis is performed over all images available in 24 hours (in daylight) 

Coverage The H-SAF area [25-75°N lat, 25°W-45°E long] 

Cycle Daily 

Resolution 1 to 5 km, depending on the instrument providing the retained pixel (best for MODIS, worst for SEVIRI) 

Accuracy POD 95 %, FAR 10 % - Depending on geographical situation (flat/forested areas, mountainous regions) 

Timeliness Fixed time of the day, product updated to account for data available until 1 h before delivery 


Formats Values in fixed grid points of the Meteosat projection (GEO satellites) or fixed latitude-longitude grid (WGS 84) 

representing the resolution of the used satellite (polar orbiting satellites). Also JPEG or similar for quick-look. 


AVHRR on NOAA and MetOp 6 VIS/IR channels, specifically the 3 short-wave channels, resolution 1 km s.s.p. 

MODIS on EOS-Aqua and EOS-Terra 36 VIS/IR channels, specifically the 4 short-wave channels with resolution 0.5 km s.s.p. 

SEVIRI on Meteosat-8 and follow-on 12 VIS/IR channels, specifically High-Resolution VIS (resolution ~1.7 km over Europe) 


VIIRS on NPP 

22 VIS/IR channels, specifically 3 short-wave channels with resolution 0.4 km s.s.p. 



VIIRS on NPP and NPOESS 


SEVIRI on Meteosat-8 and follow-on 12 VIS/IR channels, specifically High-Resolution VIS (resolution ~1.7 km over Europe) 



Land cover and vegetation maps 

Snow field measurements 


The product is an output of image classification processing. The snow signature is recognised as differential brightness in more 

short-wave channels, intended to discriminate snow from no-snowed land and snow from clouds. Both radiometric signatures are 

used (specifically, the 1.6 micron channel as compared with others), and time-persistency (for cloud filtering by the “minimum 

brightness” technique applied over a sequence of images). The Meteosat/SEVIRI contribution is mostly for southern Europe 

(including mountainous regions) and minimum brightness technique application. For mountainous regions multispectral threshold 

technique implemented on VIS and IR satellite reflectance values is used in order to get maximum daily snow coverages. 


For the basic algorithms: ATDD-1.0 Part 4 (Snow parameters), Chapter 2 (provided by FMI and METU) 

For instrument descriptive tablets of AVHRR, MODIS, SEVIRI and VIIRS: Appendix to ATDD-1.0 Part-1


SN-OBS-2 

Snow status (dry/wet) by MW radiometry 


This product indicates the status of the snow mantle, whether it is wet or dry and, in time series, thawing or freezing. Multi-channel 

MW observations are used (middle frequencies), and the algorithm is based on thresholding. In order to remove ambiguity between 

wet snow and bare soil, use is made of product SN-OBS-1 for preventive snow recognition, and of exploitation of change detection 


Cycle Daily 

Resolution 10-30 km (0.25 deg grid), depending on the location (best for northern parts, worst for southern parts of the H-SAF 

area) 

Accuracy HR 80 %, FAR 10 % - Depending on snow thickness (it must not be too shallow) 



Formats Values in fixed grid points in latitude/longitude grid - Also JPEG or similar for quick-look. 


SSM/I on DMSP up to 15 


SSMIS on DMSP from 16 onward 21 frequencies, 24 channels, resolution 50 km @ 19 GHZ, 30 km @ 37 GHz 

AMSR-E on EOS-Aqua 



AMSR-2 on GCOM-W 6 frequencies, 12 channels, resolution 16 km @ 19 GHz, 8 km @ 37 GHz 


SSMIS on DMSP from 16 onward 21 frequencies, 24 channels, resolution 50 km @ 19 GHZ, 30 km @ 37 GHz 



CMIS on NPOESS (being re-designed) 66 frequencies, 77 channels, resolution 16 km @ 19 GHz, 8 km @ 37 GHz 

MW radiometers of the GPM (up to 8) 5-7 frequencies, 9-13 channels, resolution 30-50 km @ 19 GHz, 15-30 km @ 37 GHz 



Land cover and vegetation maps (Geographical Information System) 

Snow depth and weather information from synoptic stations 

Field measurements in specially-equipped ground stations 


In the microwave range, snow emissivity is substantially different for dry and wet snow, therefore snow status observation is a 

relatively straightforward application, also facilitated by the all-weather capability. The emissivity substantially increases when snow 

is wet, enabling detection of snow status. Middle frequencies are used (19 and 37 GHz). The recognition of dry snow for snow pack 

shallower than 80 mm is unreliable due to high penetration depth of microwaves in dry snow. The algorithm as stand-alone is unable 

to discriminate wet snow from bare ground (a problematic solution for mountainous regions), thus wet snow status is recorded only 

for those locations where Snow detection (product SN-OBS-1) has revealed snow or there has been dry snow in the preceding 

product. 


For the basic algorithms: ATDD-1.0 Part 4 (Snow parameters), Chapter 3 (provided by TKK) 

For instrument descriptive tablets of SSM/I, SSMIS, AMSR-E / AMSR-2, CMIS (before descoping) and one advanced GPM 

radiometer (GMI): Appendix to ATDD-1.0 Part-1


SN-OBS-3 

Effective snow cover by VIS/IR radiometry 


The combined effect, within a product resolution element, of fractional snow cover and other reflective contributors is used to 

estimate the fractional cover at resolution element level. The product may be processed in different ways and have different quality 

depending on the surface being flat, forested or mountainous. The algorithm is based on multi-channel analysis of AVHRR, the most 

important being those in short-wave, thus the product is generated in daylight. The “deficit” of brightness in respect of the maximum 

one is correlated to the lack of snow in the product resolution element. In the case of forests, the expected maximum brightness (or 

the “transmissivity”) is evaluated in advance by a high-resolution instrument (MODIS). In order to search for cloud-free pixels, multitemporal 

analysis is performed over all images available in 24 hours (in daylight) 


Cycle Daily 

Resolution 5 to 10 km (0.05 degrees), depending on the location (best for northern parts, worst for southern parts of the H-SAF 

area) 

Accuracy Around 20 % - Depending on geographical location (flat/forested areas, mountainous regions) 



Formats Values in fixed latitude-longitude grid representing a resolution element of the used instrument. Also JPEG or 

similar for quick-look. 



MODIS on EOS-Aqua and EOS-Terra 36 VIS/IR channels, specifically the 4 short-wave channels with resolution 0.5 km s.s.p. 

SEVIRI on Meteosat-8 and follow-on 12 VIS/IR channels (in seasonal snow covered areas resolution >5 km, TBD) 


VIIRS on NPP 




VIIRS on NPP and NPOESS 


SEVIRI on Meteosat-8 and follow-on 12 VIS/IR channels, (TBD) 



Land surface temperature, land cover and vegetation maps 

Snow field measurements 


The product differs from SN-OBS-1 in so far as, in the snow map, the resolution elements report the fractional snow coverage 

instead of being binary (snow/snow-free). The possibility of appreciating fractional coverage stems from the lack of observed 

brightness in respect of what would be if the pixel were fully filled by snow. The forest canopy obscuring the full visibility to the 

ground is accounted for by applying certain a priori transmissivity information, which must be generated using satellite-borne 

reflectance data acquired under full dry snow cover conditions. These reflectances must be measured by the same instrument as 

which is used in the fractional snow coverage estimation. This means that the product can be generated for areas where full dry 

snow cover stays at least for some period and that during that period, cloud-free reflectance data are gained. Since the transmissivity 

approach may not work well for bare ground and vegetative lands (different from forest area) on mountainous regions, subpixel 

reflectance model is used. The topographic normalization is performed preferably, in order to eliminate the terrain effects on the 

reflectances of the features in the mountainous regions. 


For the basic algorithms: ATDD-1.0 Part 4 (Snow parameters), Chapter 4 (provided by SYKE and METU) 

For instrument descriptive tablets of AVHRR, MODIS, SEVIRI and VIIRS: Appendix to ATDD-1.0 Part-1


SN-OBS-4 

Snow water equivalent by MW radiometry 


Maps of snow water equivalent derived from MW measurements sensitive to snow thickness and density. The product may be 

processed in different ways and have different quality depending on the surface being flat, forested or mountainous. The algorithm is 

based on assimilating MW brightness temperatures of several channels at frequencies with different penetration in snow, into a firstguess 

field built by the (sparse) network of stations measuring snow depth 


Cycle Daily/weekly 

Resolution 10-30 km (0.25 degrees), depending on the location (best for northern parts, worst for southern parts of the H-SAF 

area) 

Accuracy To be assessed - Tentative: 20 mm - Depending on geographical situation (flat/forested, mountainous) 



Formats Values in fixed latitude/longitude grid, each representing the area covered by the nominal resolution of the used 

instrument. - Also JPEG or similar for quick-look 


SSM/I on DMSP up to 15 4 frequencies, 7 channels, resolution 50 km @ 19 GHz, 30 km @ 37 GHz, 15 km @ 90 GHz 

SSMIS on DMSP from 16 on 21 frequencies, 24 channels, resolution 50 km @ 19 GHZ, 30 km @ 37 GHz, 15 km @ 90 GHz 

AMSR-E on EOS-Aqua 6 frequencies, 12 channels, resolution 20 km @ 19 GHz, 10 km @ 37 GHz, 5 km @ 90 GHz 


AMSR-2 on GCOM-W 6 frequencies, 12 channels, resolution 16 km @ 19 GHz, 8 km @ 37 GHz, 4 km @ 90 GHz 

MetOp ASCAT 



SSMIS on DMSP from 16 on 21 frequencies, 24 channels, resolution 50 km @ 19 GHZ, 30 km @ 37 GHz, 15 km @ 90 GHz 

AMSR-2 on GCOM-W 6 frequencies, 12 channels, resolution 16 km @ 19 GHz, 8 km @ 37 GHz, 4 km @ 90 GHz 

CMIS on NPOESS (being redesigned) 

66 frequencies, 77 channels, resolution 16 km @ 19 GHz, 8 km @ 37 GHz, 4 km @ 90 GHz 

MW radiometers of the GPM 

(up to 8) 

5-7 frequencies, 9-13 channels, resolution 30-50 km @ 19 GHz, 15-30 km @ 37 GHz, 8-15 km @ 

90 GHz 



Land surface temperature, land cover and vegetation maps (Geographical Information System) 

Snow depth and weather information from synoptic stations 

Field measurements in specially-equipped ground stations 


Microwaves are sensitive to snow thickness and density, i.e. to the snow water equivalent. Depending on the snow being dry or wet, 

the penetration changes (dry snow is more transparent). High frequencies are required for dry snow, which is an advantage from 

the resolution viewpoint. However, with increasing snow depth, lower frequencies are necessary for better penetration, thus a multifrequency 

approach is required. It is an all-weather, night-and-day measurement, whose processing requires considerable support 

from ancillary information. Method and performance may be different for flat/forested areas and mountainous regions. The potential 

capability of radar scatterometry also will be assessed. Method and performance may be different for flat/forested areas and 

mountainous regions. The variation of snow density and snow characteristics in terms of grain size with respect to elevation and time 

scale are considered in the method for mountainous regions. 


For the basic algorithms: ATDD-1.0 Part 4 (Snow parameters), Chapter 5 (provided by TKK and METU) 

For instrument descriptive tablets of SSM/I, SSMIS, AMSR-E / AMSR-2, CMIS (before descoping), one advanced GPM radiometer 

(GMI) and ASCAT: Appendix to ATDD-1.0 Part-1







2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

4000 Finland 

4100 Finland 

4110 Finland 

4111 Finland → → ← 

4112 Finland → → ← 

4113 Finland → → ← 

4120 Finland 

4121 Finland → →← →← →← 

4122 Finland → →← →← →← 

4123 Finland → →← → ← → ← 

4124 Finland → → ← → ← 

4130 Finland 

4131 Finland → →← → ← 

4132 Finland → → ← → ← 

4133 Finland → → ← → ← 

4200 Turkey 

4210 Turkey 

4211 Turkey → → ← 

4212 Turkey → → ← 

4213 Turkey → → ← 

4220 Turkey 

4221 Turkey → →← →← →← 

4222 Turkey → →← →← →← 

4223 Turkey → →← → ← → ← 

4224 Turkey → → ← → ← 

4230 Turkey 

4231 Turkey → →← → ← 

4232 Turkey → → ← → ← 

4233 Turkey → → ← → ← 

4300 Finland 

4310 Finland 

4311 Finland → →← 

4312 Finland → → ← → ← 


4321 Belgium → →← 

4322 Belgium → → ← → ← 

4323 Belgium → → ← 

4330 Finland ← 

4331 Finland → →← 

4332 Finland → → ← → ← 

4333 Finland → → ← 

↑ ↑ ↑ 

↑ 

KO 

↑ 

RR 

PDR WS-1 CDR 

(continue) 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR





2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

4340 Germany ← 

4341 Germany → →← 

4342 Germany → → ← → ← 

4343 Germany → → ← 

4350 Poland ← 

4351 Poland → →← 

4352 Poland → → ← → ← 

4353 Poland → → ← 

4360 Turkey ← 

4361 Turkey → →← 

4362 Turkey → → ← → ← 

4363 Turkey → → ← 

4400 Finland 

4410 Finland 

4411 Finland → →← 

4412 Finland → → ← → ← 

4413 Finland → → ← → ← →← → ← 

4420 Turkey 

4421 Turkey → →← 

4422 Turkey → → ← → ← 

4423 Turkey → → ← → ← →← → ← 

4430 Romania 

4431 Romania → →← 

4432 Romania → →← 

4440 Finland 

4441 Finland → →← 

4442 Finland → → ← → ← 

4443 Finland → → ← → ← →← → ← 

4450 Finland 

4451 Finland → →← 

4452 Finland → → ← → ← 

4453 Finland → → ← → ← →← → ← 

4460 Turkey 

4461 Turkey → →← 

4462 Turkey → → ← → ← 

4463 Turkey → → ← → ← →← → ← 

4470 Finland 

4471 Finland → → ← → ← 

4472 Finland → → ← → ← →← → ← 

4473 Finland → → ← →← → ← 

4480 Turkey 

4481 Turkey → → ← → ← 

4482 Turkey → → ← → ← →← → ← 

4483 Turkey → → ← →← → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 7 (The Hydro validation programme) Page 114 

7. The Hydrological validation programme (WP-5000) - Cluster-4 


The purpose of the Hydrological validation programme is to provide independent assessment of the 

usefulness of H-SAF products in operational hydrology and water management. It should not be 

confused with “product validation” that is functional to improve calibration and characterise the error 

structure. However, as a by-product, the activities for benefit assessment will provide valuable output 

for cal/val, as well as the feedback to the data producers for possible products quality improvement. 

Feedback from the users at all stages of products’ development is highly required. The products have to 

be validated in catchments/areas with different properties, such as size, character and climatic zones of 

Europe, located in both plain and mountainous regions. Taking into account difficulties with proper 

validation of products such as precipitation, soil moisture and snow, that are characterised by high 

spatial and temporal variation and lack of real ground truth, impact studies and independent validation 

with use of operational hydrological models are highly required. 

Main activities of the Hydrology validation programme are: 

• requirements analysis - determination of optimal products presentation/distribution, according to 

the needs of operational hydrological services - information needs, data format, desired 

spatial/temporal resolution, delivery path, timeliness. This should include an analysis of existing 

gaps and the prioritisation of the needs, perhaps within a proposed time frame; 

• development of the methodology and algorithms (interfaces) for products up-scaling, down-scaling, 

averaging over catchments etc.; 

• development of methodology and algorithms for merging the satellite products with other data to 

achieve more complete products both in time and space scale, especially for the areas with spatially 

scarce standard observations; 

• use of hydrological/hydrodynamic models for impact studies for each type of products 

(precipitation, snow, soil moisture) and for different catchments (size, location, character); 

• validation of final products with the use of hydrological models - selection of well equipped study 

catchments in different areas of Europe. Adaptation of hydrological models for assimilation of 

satellite products from Clusters 1 to 3. Task performed by pilot users; 

• determination of the requirements for improvements of product algorithms as a result of impact 

studies - in this way, Cluster 4 supports the work of Clusters 1 to 3 (precipitation, soil moisture and 

snow); 

• creation of structure for on-going H-SAF products validation and quality assessment during the 

operational phase of H-SAF. 

Under the leadership of Poland, eight Countries participate in the “core” activity of Cluster-4 (impact 

studies). In addition, the leading Countries of Clusters 1, 2 and 3 provide input for Education and 

Training on the use of H-SAF products. 

WBS-18 displays the structure of WP-5000 up to the 3 rd level WP’s. For each Country a different 

colour emphasises its contribution to Cluster-4. In this Chapter the work plan will be described up to 4 th 

level. In the Appendix WPD’s are provided for 1 st , 2 nd and 3 rd level WP’s.


WP-5000 

Hydrological validation 

Poland (IMWM) 

WP-5100 

Products training 

Poland + Several 

WP-5200 

Impact study 1 

Belgium 

WP-5300 


Finland 

WP-5400 


France 

WP-5500 


Germany 

WP-5600 


Italy 

WP-5110 

Soil moisture 

Austria 

WP-5210 

Development 

& models 

WP-5310 

Development 

& models 

WP-5410 

Development 

& models 

WP-5510 

Development 

& models 

WP-5610 

Development 

& models 

WP-5120 

Snow 

Finland 

WP-5220 

Scheldt 

river 

WP-5320 

Kemijoki 

basin 

WP-5420 

Grand & Petit 

Morin 

WP-5520 

Rhine 

catchment 

WP-5620 

Tanaro 

river 

WP-5130 

Precipitation 

Italy 

WP-5230 

Meuse 

river 

WP-5430 

Beauce 

region 

WP-5440 

Adour-Garonne 

basin 

WP-5630 

Arno 

river 

WP-5640 

Basento 

river 

WP-5700 


Poland 

WP-5800 


Slovakia 

WP-5900 


Turkey 

WP-5710 

Development 

& models 

WP-5720 

Sola 

river 

WP-5810 

Development 

& models 

WP-5820 

Myjava 

river 

WP-5910 

Development 

& models 

WP-5920 

Susurluk 

basin 

WP-5730 

Skawa 

river 

WP-5740 

Czarna 

river 

WP-5830 

Nitra 

river 

WP-5840 

Kysuca 

river 

WP-5930 

West Black 

Sea basin 

WP-5940 

Upper 

Euphrates 

WP-5850 

Hron 

river 

WP-5860 

Topla 

river 

WP-5950 

Upper 

Karasu 

WP-5960 

Kırkgöze 

basin 

WBS-18 - WBS of WP-5000: 1 st , 2 nd and 3 rd level WP’s. 4 th level WP’s defined in next sections. 

The logic of the WBS is as follows: 

• eight Countries will perform impact studies, each one over a number of test sites. This activity is 

recorded in 2 nd level WP’s 5200 to 5900; 

• the same Countries contribute to the developments necessary to perform the impact studies (3 rd level 

WP’s 5210, 5310, 5410, 5510, 5610, 5710, 5810 and 5910); 

• the leads of the three H-SAF production Clusters provide training (3 rd level WP’s 5110 to 5130). 

7.2 The Education and Training programme (WP-5100) 

Satellite-derived products require plenty of care for utilisation. Their nature is different from that one of 

ordinary ground-based systems. Since the only quantity that can be measured from space is radiation, 

the geophysical parameter is only indirectly linked to the original measure. The intermediate retrieval 

process works differently for different situations of the geophysical parameter, and introduces biases 

such as range of applicability, scale, etc., that the products validation activity attempts to characterise. 

The accuracy also is variable through the field of view, depending on the situation of the addressed 

scene. The calibration and re-calibration activity attempts to minimise errors, but the degree of success 

is discontinuous in space and in time. The Education and Training programme associated to Cluster-4 

intends to make Hydrologists aware of product characteristics and error structures.


The Units responsible of generating H-SAF products will provide Hydrologists with the necessary 

information. It is reminded that products will be distributed to users in several steps, according to the 

logic of stepwise development (see Fig. 5 in Chapter 2). Demonstrational products will be released 

around T 0 + 24, pre-operational products around T 0 + 42 and a final operational version at the end of the 

Development Phase. Consequently, the E&T programme will start in association with demonstrational 

products release. 

WBS-19 deploys the structure of WP-5100, lead by Poland as responsible of Cluster-4, and 

implemented by Austria, Finland and Italy. 

WP-5100 

Products training 

Poland (IMWM) 

WP-5110 

Soil moisture 


WP-5111 

Initial workshop on products, 

methods and algorithms 

WP-5112 

Manual on product use 

in hydrological applications 

WP-5113 

Distance learning sessions 

for updating and re-training 

WP-5120 

Snow 

Finland (FMI) 

WP-5121 



WP-5122 



WP-5123 



WP-5130 

Precipitation 

Italy (CNMCA) 

WP-5131 



WP-5132 



WP-5133 




Training will be planned for three different user groups: 

● scientists in the H-SAF; 

● scientists using H-SAF products as data and input to their studies and/or hydrological models; 

● end users of products as static images, just for viewing; for instance in hydrological services or 

forecasters in weather offices. 

There are variations from corresponding WP’s of the same name on the different products but, for the 

sake of simplicity, the following uniform description is provided. 

WP’s 5111, 5121 and 5131 - Initial workshop on products, methods and algorithms 

At the 1 st H-SAF Workshop (WS-1) to be held at approximately T 0 + 24 a broad-view presentation of all 

H-SAF products will be provided. Shortly after start of the distribution of demonstrational products, 

specialised workshops will be organised by the leaders of Clusters 1, 2 and 3. The specialised 

workshops will focus on algorithms and processing methods, and will make use of the preliminary 

results of the validation exercises intended to characterise the product error structure. They will pave 

the way for the follow-on training and re-training activity. 

WP’s 5112, 5122 and 5132 - Manual on product use in hydrological applications 

An online manual will be written so that there will always be an easily browsable documentation 

available for reference use. The online manual will describe the H-SAF products both scientifically and 

technically in a compact and user-oriented manner. It will give the users a quick reference to the 

products, but also have links to more in depth documents of the scientific background and validation.


WP’s 5113, 5123 and 5133 - Distance learning sessions for updating and re-training 

The distance learning is coming more popular and the technical possibilities for that begin to be at 

feasible level. During the course of H-SAF project it is obvious that distant learning will be one of the 

ways to reach users and scientists that are not able to attend the workshops. Distant learning sessions 

also give complement to the workshops. The sessions will be organised during the last two years of the 

H-SAF Development Phase. 3-4 sessions are foreseen, but the material will be available for later use on 

the H-SAF web. It is currently assumed that the VisitView software will be used for the sessions 

(http://www.ssec.wisc.edu/visitview). The preliminary content of the sessions will be: 

• for each snow product, a short introduction to the methods and their strengths/weaknesses 

• how to read the data products - technical description 

• how the data products are organised - technical description 

• explanation of coordinate system and projection of the products 

• basic principles of evaluating the products. 

Distance learning and self learning material make use of EUMeTrain project tools and methods as far as 

applicable. Also cooperation with EUMeTrain will be sought in realisation of the sessions. 

7.3 The impact study programme 


The purpose of the H-SAF Hydrological validation programme is to provide independent assessment of 

the benefit of satellite-derived data in practical hydrological applications. This is distinct from the 

product validation, that only addresses the quality of the products, independently whether they are 

useful or not. There may be reasons why a geophysical parameter, although very accurately measured, 

has little or no impact on the practical application. The most obvious situation is when, among the 

factors that control the application, there is some that dominates the overall application performance: 

maybe inadequacy of available models, insufficient knowledge of the terrain response characteristics; 

but also practical limitations such as lack of good communications, etc.. In the case of satellite-derived 

products, the main reason for possible lack of impact is the inadequacy of the space-time resolution of 

the product to the size and response-time of the hydrological basin. It is expected that the impact of 

satellite data may be marginal for too small / fast-response basins, good for medium-size basins and 

again marginal for very large basins for which the evolution is predictable thus actual measurements are 

relatively less important whereas forecast fields are sufficient (and more comfortable to use). 

In meteorology, where NWP models are very well performing, the impact of new data can be 

anticipated by Observing System Simulation Experiments (OSSE). In Hydrology numerical models are 

less performing and the influence of the basin morphology is so great that the transportation of OSSE 

results into different environments would be problematic. Therefore, practical experiments are better 

suited to assess the impact of novel data. These impact studies need to be carried out on a variety of 

geo-morphological situations and climatic regions through the EUMETSAT membership. A number of 

test sites have been identified to perform the impact studies. Fig. 2 in Chapter 2 provided a broad idea 

of the coverage from test sites. Fig. 27 provides a somewhat more detailed view.


Fig. 27 - Location and geo-morphological situation of test sites for the impact studies.


7.3.2 Impact studies in Belgium (WP-5300) 

Two test sites have been selected for the hydrological validation of the H-SAF products in Belgium. 

They belong to the two main river basins in Belgium. They have contrasted hydrological characteristics 

and each represents an important landscape in the river basin it belongs to. The Demer catchment is 

mainly situated in the loamy region with a fairly flat topography in the Scheldt river basin whereas the 

Ourthe has a large part situated in the hilly Ardens which contributes much to the Meuse river regime. 

The former is mainly covered with agricultural area whilst the latter has a large fraction covered with 

both deciduous and coniferous forests. The total annual precipitation over the Demer is on average 

about the ¾ of the corresponding precipitation over the Ourthe. These contrasts may even be more 

pronounced between sub-areas of these sub-catchments. 

WBS-20 deploys the structure of WP-5200. 4 th level WP’s are described in Section 7.3.10. 

WP-5200 


Belgium (IRM) 

WP-5210 

Development & models 

Belgium (IRM) 

WP-5211 

Requirements from the impact study 

WP-5212 

Upscaling, downscaling 

WP-5213 

Data fusion, assimilation 

WP-5214 

Hydrological modelling 

WP-5220 

Scheldt river basin 

Belgium (IRM) 

WP-5221 

Site infrastructures consolidation 

WP-5222 

Impact assessment experiments 

WP-5223 

Analysis of results & lesson learnt 

WP-5330 

Meuse river basin 

Belgium (IRM) 

WP-5331 


WP-4232 


TSMS 

WP-5333 



7.3.3 Impact studies in Finland (WP-5300) 

The Finnish test site consists of a large river system in the boreal forest zone, highly relevant for hydropower 

production, snow melt main source of annual discharge. 

The test site has been used for the development and validation of operational remote sensing 

applications. 

The impact study will investigate how well the current operational hydrological forecasting system of 

the Finnish Environment Institute (SYKE) simulates the maximum snow water equivalent prior to the 

on-set of snow melt and the fractional snow covered area during the melting period. This includes the 

assessment of accuracy improvement to be obtained in hydrological forecasting by using H-SAF snow 

products. 

It is noted that Finland joined the Hydrological validation programme in early 2008. 

WBS-21 deploys the structure of WP-5300. 4 th level WP’s are described in Section 7.3.10.


WP-5300 


FMI 

WP-5310 


FMI-ARC 

WP-5311 


WP-5312 


WP-5313 


WP-5320 

Kemijoki basin 

FMI-ARC 

WP-5321 


WP-5322 


WP-5323 


WP-5314 


WBS-21 - WBS of WP-5300: 2 nd , 3 rd and 4 th level WP’s 

7.3.4 Impact studies in France (WP-5400) 

Three test sites have been selected for the hydrological validation of the H-SAF products in France. 

The test catchments of Grand and Petit Morin are small-medium basins located in a flat agricultural area. 

These catchments contain two main rivers having a strong influence on surface water quality used for 

drinkable water for an important urbanized area near the Paris greater area. This site is well 

instrumented with a long term period of measurements. 

The Beauce region is a flat agricultural area with wheat and corn main crops. Therefore, during all the 

year, approximately a half of the fields are bare soil. This type of site is particularly well adapted for 

validation of satellite soil moisture estimations (flat surface and large percentage of bare soil). 

The Adour-Garonne basin is a large basin stretching from the Pyrenees mountains to flatlands. This test 

site was selected for many reasons: large area permitting the use of consequent number of satellite data 

among the area, domain well known from the hydrogeological, hydrological and climatological points 

of view, area where the SIM model was originally calibrated, existing network on this area for 

continuous soil moisture measurements (SMOS Cal/Val activities with the SMOSMANIA network of 

Météo-France). 



WP-5400 


France (Météo-France) 

WP-5410 


Météo-France 

WP-5420 

Grand and Petit Morin 


WP-5430 

La Beauce region 


WP-5440 

Adour-Garonne basin 


WP-5411 

Requirements from 

the impact study 

WP-5421 

Site infrastructures 

consolidation 

WP-5431 


consolidation 

WP-5441 


consolidation 

WP-5412 

Upscaling, 

downscaling 

WP-5422 

Impact assessment 

experiments 

WP-5432 


experiments 

WP-5442 


experiments 

WP-5413 

Data fusion, 

assimilation 

WP-5423 

Analysis of results & 

lesson learnt 

WP-5433 


lesson learnt 

WP-5443 


lesson learnt 

WP-5414 

Hydrological 

modelling 


7.3.5 Impact studies in Germany (WP-5500) 

The Rhine basin is rather large (185,300 km²), covering Germany (about 100,000 km²), Switzerland, 

France and The Netherlands (20,000 to 30,000 km²), Austria and Luxemburg (about 2,500 km²) as well 

as Italy, Liechtenstein and Belgium (small parts). The size of the study area supports the intensive 

investigation of the benefit of large scale remote sensing products at different scales ranging from the 

scale of the sub-catchments (several hundreds to thousands of square kilometers) to the whole basin. 

[Note: in PP-1.0 three test sites were mentioned, Sieg, Sulzbach and Dill, all sub-basins of Rhine]. 

The various hydrological phenomena in the Rhine basin are caused by meteorological processes acting 

jointly on the basin characteristics. A transition from maritime climate in the north and northwestern 

parts to more continental conditions in the south and southeastern parts is observed. Three main 

climatic regions can be differentiated from the climate perspective and the consideration of orographic 

effects: the Alps and pre-Alps (catchment upstream of Basel), the medium mountain ranges (between 

Basel and Cologne) and the plains in the North (downstream of Cologne). Melt water and precipitation 

runoff from the Alps dominate the flow regime during the spring and summer months. In winter the 

precipitation runoff from the uplands is more important. The influence of the uplands grows more and 

more further downstream, and over the year the discharge becomes very compensated. 



WP-5500 


Germany (BfG) 

WP-5510 


BfG 

WP-5511 


WP-5512 


WP-5513 


WP-5520 

Rhine catchment 

BfG 

WP-5521 


WP-5522 


WP-5523 


WP-5514 


WBS-23 - WBS of WP-5500: 2 nd , 3 rd and 4 th level WP’s 

7.3.6 Impact studies in Italy (WP-5600) 

The hydrological validation programme in Italy will make use of three test sites, in North, Centre and 

South respectively, of different sizes and affected by different hydrological problems. The aim of this 

WP is to evaluate the impact of the H-SAF products (precipitation, snow cover and soil moisture) on the 

hydrology models used by the Italian Civil Protection Department (DCP). The variety of the Italian 

landscapes (alluvial plain, mountains, .. etc) joined with the emergency management requirements are 

the main specific elements to be taken into account in the development of the 5600 WP. 


WP-5600 


Italy (DPC) 

WP-5610 


Italy (DPC) 

WP-5620 

Tanaro river basin 

Italy (DPC) 

WP-5630 

Arno river basin 

Italy (DPC) 

WP-5640 

Basento river basin 

Italy (DPC) 

WP-5611 



WP-5621 


consolidation 

WP-5631 


consolidation 

WP-5641 


consolidation 

WP-5612 

Upscaling, 

downscaling 

WP-5622 


experiments 

WP-5632 


experiments 

WP-5642 


experiments 

WP-5613 

Data fusion, 

assimilation 

WP-5623 


lesson learnt 

WP-5633 


lesson learnt 

WP-5643 


lesson learnt 

WP-5614 

Hydrological 

modelling 



7.3.7 Impact studies in Poland (WP-5700) 

Three test sites have been selected for the hydrological validation of the H-SAF products in Poland. 

Sola and Skawa lie in the upper Wisła (Vistula) basin that is the richest in water region of Poland. 

Intensive precipitation over a vast area lasting for a couple of days and reaching up to 200 mm a day 

(orographic effects on the Northern slopes of the Tatra and Beskidy Mountains) as well as small 

retention capacity of the river valleys bring about fast and violent water rising in the streams and rivers. 

Precipitation and runoff indicators considerably exceed the nation-wide mean values. From the 

hydrological point of view the maximum flood hazards are caused among others by the Soła river (apart 

from the Skawa, the Raba and the Dunajec rivers). Another important factor determining the flood risk 

in the catchment is growing settlement, which is concentrated along the rivers. 

The Czarna River was chosen as an example of characteristic low-laying river. There are huge 

differences between Czarna and Soła/Skawa catchments concerning meteorological, topographical and 

geomorphological characteristics, rainfall-runoff transformation process and land-use (predominantly 

agriculture). Characteristics of freshets also are different. High water levels and floods are caused by 

melting snow or by both melting snow and rain fall. Flash floods can occur in this region of Poland. 


WP-5700 


Poland (IMWM) 

WP-5710 


IMWM 

WP-5720 

Soła river catchment 

IMWM 

WP-5730 

Skawa river catchment 

IMWM 

WP-5740 

Czarna river basin 

IMWM 

WP-5711 



WP-5721 


consolidation 

WP-5731 


consolidation 

WP-5741 


consolidation 

WP-5712 

Upscaling, 

downscaling 

WP-5722 


experiments 

WP-5732 


experiments 

WP-5742 


experiments 

WP-5713 

Data fusion, 

assimilation 

WP-5723 


lesson learnt 

WP-5733 


lesson learnt 

WP-5743 


lesson learnt 

WP-5714 

Hydrological 

modelling 


7.3.8 Impact studies in Slovakia (WP-5800) 

Five test sites have been selected for the hydrological validation of the H-SAF products in Slovakia. 

They are representative of variable hydrological conditions. Some are lowlands and other mountainous, 

well covered or not covered by meteorological radar. The basins were selected also with respect to 

floods occurred in the last years. 

The Myjava river and the Nitra river basins were selected in a generally flat area prone to flash floods, 

one (Myjava) of small size, the other (Nitra) of medium size. The Kysuca river basin was selected as a 

typical hydrological system of highlands. The Hron river basin was selected as a small-medium size


mountainous test site with hydrological effects controlled by snow melting. The Topla river basin was 

selected as a small basin in uplands, representative of typical hydrological regimes. 


WP-5800 


Slovakia (SHMÚ) 

WP-5810 

Develop. & models 

SHMÚ 

WP-5820 

Myjava river basin 

SHMÚ 

WP-5830 

Nitra river basin 

SHMÚ 

WP-5840 

Kysuca river basin 

SHMÚ 

WP-5850 

Hron river basin 

SHMÚ 

WP-5860 

Topla river basin 

SHMÚ 

WP-5811 

Requir. from 


WP-5821 

Infrastructures 

consolidation 

WP-5831 


consolidation 

WP-5841 


consolidation 

WP-5851 


consolidation 

WP-5861 


consolidation 

WP-5812 

Upscaling, 

downscaling 

WP-5822 

Impact assess. 

experiments 

WP-5832 


experiments 

WP-5842 


experiments 

WP-5852 


experiments 

WP-5862 


experiments 

WP-5813 

Data fusion, 

assimilation 

WP-5823 

Results analysis 

& lesson learnt 

WP-5833 



WP-5843 



WP-5853 



WP-5863 



WP-5814 

Hydrological 

modelling 


7.3.9 Impact studies in Turkey (WP-5900) 

Five test sites have been selected for the hydrological validation of the H-SAF products in Turkey. 

The Susurluk river basin is selected as it reflects different climatic and hydrologic characteristics of 

Marmara Sea as well as Mediterranean transition regions. The impact study will focus on the 

conversion of effective precipitation into surface runoff and possible flood frequency analysis with 

preliminary flood inundation map preparation on the basis of 5, 10, 25, 50 and 100 year return periods. 

Additionally, a fuzzy expert system model is expected to be developed for the rainfall-runoff conversion 

system in the basin. 

The Western Black Sea basin lies in northern part of the country with relatively high water potential and 

is located in a high precipitation receiving area in Turkey. The area has been flooded several times in 

recent years as a result of heavy rains. The impact study will focus on the possible rainfall-runoff 

transformation system in a selected sub-basin. Additionally, water resources management will also be 

considered with simple logical and rational rules. 

Water perhaps is the most valuable natural asset in the Middle East as it was a historical key for 

settlement and survival in Mesopotamia, “the land between two rivers”. At present, the Euphrates and 

Tigris are the two largest trans-boundary rivers in Western Asia where Turkey, Syria, Iran, Iraq and 

Saudi Arabia are the riparian countries. The Euphrates and Tigris basins are largely fed from snow 

precipitation over the uplands of northern and eastern Turkey whereby nearly two-thirds occur in winter 

and may remain in the form of snow for one half of the year. A sustained period of high flows during 

the spring months mainly resulting from melting of the snowpack (60-70 % in volume of the total yearly 

runoff) causes not only extensive flooding, inundating large areas, but also the loss of much needed 

water required for irrigation and power generation purposes during the summer season. Many of the 

large dams in Turkey are located in the Euphrates basin. The aridity of the region and the water


requirements of the downstream nations necessitate accurate and optimum operation of these dams. 

Accordingly, modelling of areal snow cover in the mountainous regions of Eastern Turkey is crucial for 

water resources management. The Upper Euphrates basin and the Upper Karasu basin, located on the 

Upper Euphrates river, and the Kırkgöze basin, located on the headwaters of the Euphrates river, were 

selected as representative to monitor and model the snow cover in Eastern Turkey. 


WP-5900 


Turkey (METU) 

WP-5910 

Develop. & models 

METU 

WP-5920 

Susurluk river 

ITU 

WP-5930 

West Black Sea 

ITU 

WP-5940 

Upper Euphrates 

METU + AU 

WP-5950 

Upper Karasu 

AU 

WP-5960 

Kırkgöze basin 

AU 

WP-5911 

Requir. from 


WP-5921 


consolidation 

WP-5931 


consolidation 

WP-5941 


consolidation 

WP-5951 


consolidation 

WP-5961 


consolidation 

WP-5912 

Upscaling, 

downscaling 

WP-5922 


experiments 

WP-5932 


experiments 

WP-5942 


experiments 

WP-5952 


experiments 

WP-5962 


experiments 

WP-5913 

Data fusion, 

assimilation 

WP-5923 



WP-5933 



WP-5943 



WP-5953 



WP-5963 



WP-5914 

Hydrological 

modelling 


7.3.10 Typical activities implied by the impact studies 

In WBS’s 21 to 27 homogenised names of 4 th level WP’s have been indicated. In effect, for each test 

site the work programme will be rather specific but, for the sake of simplicity, the following uniform 

description is provided. 

WP’s 5210, 5310, 5410, 5510, 5610, 5710, 5810 and 5910: Development and models 

In general, the work performed in WP’s 5210 to 5910 is described to a fair level of detail in the 



There are variations from corresponding WP’s of the same name in the different Countries but, for the 

sake of simplicity, the following uniform description is provided. 

WP’s 5211, 5311, 5411, 5511, 5611, 5711, 5811 and 5911: Requirements from the impact study 

These WP’s do not refer to the data quality requirements, that have been stated in the general context of 

the H-SAF Development Proposal [Applicable document Ref. 2] and recorded in Chapter 2, Table 2. 

The addressed requirements concern what is needed to enable performing the impact studies addressed 

in WP’s 5300 to 5900. Data are considered especially as concerns their operational characteristics 

(formats, timeliness, etc.), differentiating versus basin size and structure. The necessary tools, structures, 

models, etc., will be identified and their availability or need for tuning or development assessed.


WP’s 5212, 5312, 5412, 5512, 5612, 5712, 5812 and 5912: Upscaling, downscaling 

Starting from the original product characteristics, reduction for compatibility with basin scale and 

morphology will be necessary. Techniques for performing areal integration will be assessed. Methods 

for this purpose will be collected if available, or tuned or developed, with regard to the structures of 

both satellite-observed data and test sites. 

WP’s 5213, 5313, 5413, 5513, 5613, 5713, 5813 and 5913: Data fusion, assimilation 

Fusion between satellite-derived and ground-based data will be necessary, especially with decreasing 

size of the basin. Rain gauge networks and radar (when available) will be the primary ground-based 

information sources. The data fusion environment will rely on GIS. The geophysical parameters 

carried forward in hydrological models may have different structure from that one of the satellitederived 

data. Assimilation schemes will be developed to transfer information into the model in the most 

effective way. 

WP’s 5214, 5314, 5414, 5514, 5614, 5714, 5814 and 5914: Hydrological modelling 

The Hydrological validation of H-SAF products is intended to be carried out in the realistic environment 

based on existing hydrological models. Minor adaptations could be necessary. Table 10 records the 

hydrological models currently selected for the impact studies on the specified test sites. 

Table 10 - List of main hydrological models to be used for the Hydrological validation programme 

Model Acronym’s expansion Country Basin 

MP Modelling Platform of the IMWM Poland 

Soła 

Skawa 

Czarna 

Finland Kemijoki 

HBV Hydrologiska Byrans Vattenbalansavdelning model Germany Rhine 

Turkey Kırkgöze 

SIM Safran-Isba-Modcou hydro-meteorological model France 

Grand and Petit Morin 

Beauce 

Adour-Garonne 

SCHEME SCHEldt and MEuse model Belgium 

Demer-Scheldt 

Ourthe-Meuse 

SRM Snowmelt Runoff Model Turkey 

Upper Euphrates 

Upper Karasu 

HEC-HMS 

Hydrologic Engineering Center’s Hydrologic Modeling 

Susurluk 

Turkey 

System 

Western Black Sea 

Hron-NAM Hron and Nedbør-Afstrømmings Model Slovakia 

Myjava 

Kysuca 

Nitra 

Hron 

Topľa 

DRiFt Discharge River Forecast Rainfall Runoff model Italy Tanaro 

MOBIDIC MOdello di Bilancio Idrologico DIstribuito e Continuo Italy Arno 

NASH Named after the mathematician who expressed it Italy Basento 

WP’s 5220-30, 5320, 5420-40, 5520, 5620-40, 5720-40, 5820-60 and 5920-60: Activities on test sites 

For each test site the impact study will have different characteristics. However for the sake of simplicity, 

we provide uniform descriptions of the 4 th level WP’s. 

WP’s 5221, 5231, 5321, 5421, 5431, 5441, 5521, 5621, 5631, 5641, 5721, 5731, 5741, 5821, 5831, 

5841, 5851, 5861, 5921, 5931, 5941, 5951 and 5961: Site infrastructures consolidation 

Generally, the availability of basic infrastructures (raingauge stations, hydrometers, possibly radar, 

experimental fields) has played a major role in selecting the test site. The availability of basin model, 

DEM, GIS, cartography, risk maps, and other information arising from previous studies have been taken


into account too. However, in order to perform the actual experiment (impact study) a certain degree of 

“personalisation”, tuning and possibly complementing will be necessary. This will be performed in the 

build-up phase of the experiment. 

WP’s 5222, 5232, 5322, 5422, 5432, 5442, 5522, 5622, 5632, 5642, 5722, 5732, 5742, 5822, 5832, 

5842, 5852, 5862, 5922, 5932, 5942, 5952 and 5962: Impact assessment experiments 

The impact studies will be of several types, changing with test site. In general, they will exploit the data 

ingest schemes developed under WP-5200 (downscaling/upscaling, areal integration, data fusion, 

assimilation in the hydrological model). A typical experiment will consist of performing parallel runs of 

the model with and without the satellite-derived observations, but other schemes are possible, including 

supervised exercises based on expert judgment. 

WP’s 5223, 5233, 5323, 5423, 5433, 5443, 5523, 5623, 5633, 5643, 5723, 5733, 5743, 5823, 5833, 

5843, 5853, 5863, 5923, 5933, 5943, 5953 and 5963: Analysis of results and lesson learnt 

This implies evaluating both the impact of each satellite-derived product and their global contribution, 

according to comparison criteria established a-priori as part of WP-5200 (Developments); analyse the 

reasons for the result, classifying occasional and structural limitations. The output of the critical 

analysis will be fed back to the satellite product providers. 

7.4 Reporting 

Impact studies use to be activities of highly scientific content. As such, each study will probably give 

rise to internal scientific reports, often bulky, and scientific publications, often too short and difficult to 

be understood. For the purpose of H-SAF, the Hydrological validation plan established a number of 

concepts. [Note: the Hydrological validation plan was elaborated in the time period between PP-1.0 and 

PP-2.0, and it is contained in a bulky internal document, “REP-1”]. The following is an abstract. 

Contents of reporting 

For each experiment, the results will be reported to the Project Team and will, as a minimum, include; 

• information on what was the objective of the impact study (e.g., flood forecasting); 

• main basin characteristics (size, hydrological regime, …); 

• description of the meteorological event; 

• assessment of the benefit of satellite versus no-satellite, possibly for each product; 

• judgement whether the result was occasional or structural; 

• advice on how the results could have been better. 

In addition, any result that can be utilised for augmenting the products calibration/validation activity, 

although achieved as a ‘marginal’ outcome in respect of the impact assessment objective, should be 

conveyed to the Units in charge of Validation (WP-2300, WP-3300 and WP-4300) and/or Development 

(WP’s devoted to calibration in WP-2400, WP-3400 and WP-4400). 

Reporting mechanism 

There is a need to establish the mechanisms for automatic reporting and the content of the report (time 

of reception, format check, some quick test on message soundness). There is also a need for building 

the database of reports in a specific area of the Central archive (see WP-1230 in Chapter 3) for 

consultation and feedback in between all participants to the Hydrological validation programme. Some 

requirements are: 

• standard documentation archive with a specified structure for each cluster and freely available for all 

H-SAF partners; 

• user-friendly discussion list divided into certain topics; 

• data base should be accessible through standard ftp and http browsers. 

Each report coming from each hydrological validation/impact centre should be highly structured and 

clearly flagged in order to get automatically distributed to the destination, i.e. Clusters 1-3 depending on


the product validated. Such reports sent to the Hydrological validation section of the Central archive 

would then be distributed to one or all the Clusters depending on the product tested. It is suggested that 

the report should be considered with respect to: 

• report frequency (depending on product, e.g., soil moisture once a month, precipitation weekly, 

snow monthly); 

• report structure (country, catchment, date, H-SAF product type, .. etc.); 

• report format (both .pdf and .doc); 

• distribution protocol (ftp); 

• additional recipients (Project Team, Cluster 1-3, archive, …). 

Also there should be a provision for quality control to be included in the report. 

First validation report is expected to be ready half a year after establishing continuous availability of 

individual satellite products. Later on, validation reports should be prepared at least twice a year. 

After satellite product changes made by Cluster 1-3, validation impact studies will be repeated and new 

results reported if product developers will be able to provide reprocessed satellite products. Such cases 

would be taken under consideration while developing the report naming system. 

Main event 

The 2 nd H-SAF Workshop, planned for T 0 + 48, will review the preliminary results of the impact studies 

run after about two years of availability of products regularly distributed. It will provide substantial 

input to REP-4, the Report dedicated to the Hydrological validation programme. 

7.5 Summary description of test sites 

In the next pages one-sheet descriptions are provided for each selected test site. The following is 

reported: 

• significant pictures of the area (one large-scale for localisation purpose, one small-scale) 

• the reasons for selection 

• a summary description of the area 

• a list of significant facilities 

• mention of the heritage of performed studies on the test site (independent of H-SAF) 

• highlights of the planned impact study.


WP-5220 The Scheldt river basin Belgium (IMR) 

Reason for selection 

Prone to inundations; operational warning system by Aminal 

Summary description 

Surface: 1775 km 2 

Length of main river: 

63 km 

Morphology type: Fairly flat (17–173 m, see Figure). Soils: 37% Luvisols, 21% Podzols, 16% 

Fluvisols, 14% Podzoluvisols, 4% Arenosols, 3% Gleysols 

Vegetation type: 

47 % crops, 25 % meadow, 14% deciduous forests, 9% impervious area 

Responsible administration: Ministry of the Flemish Community: AWZ, Aminal 

Other special features: Precipitation: ~770 mm year -1 

Streamflow: fast response to rainfall, contribution from aquifers 

Facilities 

Number of raingauges: Automatic, 2; daily, 15 

Closest meteorological radar: Zaventem (see Figure) 

Experimental facilities: - 

Other special features: Discharge measurements at Diest and at several tributaries 

Heritage of performed studies, and planned activities (Independent of H-SAF) 

Test site for various past research projects (impact of climate changes); test site for HEPDO project 

(operational hydrological ensemble predictions) 

Highlights of the planned impact study 

The impact study will focus on flood forecasting; possible specific applications for soil moisture products in 

this agricultural sub-basin. 

In order to assess the benefit of satellite-derived data, the experimental activity will consist in comparing the 

results of a baseline hydrological simulation using H-SAF products and using other information available in 

real-time; it will consist in analyzing the possible improvement in skills of forecast performed with initial 

conditions obtained using additional H-SAF products.


WP-5230 The Meuse river basin Belgium (IMR) 


Prone to inundations; represents the hydrological conditions in the Ardennes. 




149 km 

Morphology type: Hilly (117-650 m, see Figure). Soils: 87% Cambisols, 8% Luvisols, 4% 

Lithosols 


35% meadow, 25% deciduous forest, 23% coniferous forest, 15% crops 

Responsible administration: Ministry of the Walloon Region: MET-SETHY, DGRNE 

Other special features: Precipitation: ~ 980 mm year -1 

Streamflow: mainly from surface runoff 

Facilities 

Number of raingauges: Automatic: 9; daily: 15 

Closest meteorological radar: Wideumont (see Figure) 


Other special features: Discharge measurements at Tabreux and at several tributaries 


Test site for various past research projects (impact of climate changes, data assimilation); test site for 

HEPDO project (operational hydrological ensemble predictions) 


The impact study will focus on flood forecasting; possible specific applications for snow products in this 

elevated sub-basin. 



real-time; it will consist in analyzing the possible improvement in skills of forecast performed with initial 

conditions obtained using additional H-SAF products.


WP-5320 The Kemijoki river catchment Finland (FMI) 


Large river system at boreal forest zone, highly relevant for hydro-power production, snow melt main source 

of annual discharge. 


Surface: 

51 000 km² 


550 km 

Morphology type: 

Relatively flat with some hill regions, 


Mainly forests and open/forested bogs 

Responsible administration: 

Other special features: 

Facilities 

Number of raingauges: 

Closest meteorological radar: 

Experimental facilities: 

Other special facilities: 

Regional Environment Centre of Lapland 

SYKE, FMI (also responsible for monitoring and hydrological forecasting, 

using a HBV-based Watershed Simulation and Forecasting System) 

Dozens 

One in the middle of the catchment 

Two major research establishments with hydro-met observations 

Heritage of performed studies, and planned activities (independent of H-SAF) 

Main region in Finland for hydrological research, also highly relevant for the development and of validation of 

operational remote sensing applications. In addition to the management of hydropower-production flood 

monitoring/prevention is an important remote sensing application). 


The impact study will investigate how well the current operational hydrological forecasting system of SYKE 

simulates the maximum snow water equivalent prior to the on-set of snow melt and the fractional snow 

covered area during the melting period in the case of Kemijoki drainage basin. This includes the assessment 

of accuracy improvement to be obtained in hydrological forecasting by using H-SAF snow products.


WP-5420 Grand and Petit Morin France (Météo-France) 


These two catchments are representative of human-influenced and agricultural sedimentary lands of the 

Paris greater area. The Grand Morin and Petit Morin Rivers are tributaries of Marne River, upstream the 

Paris greater area. The two rivers highly contribute to the floods of the Marne River and have a strong 

influence on surface water quality used for drinkable water. 


Surface: 1,840 km 2 (Grand Morin 1,190 km 2 , Petit Morin 650 km 2 ) 

Length of main rivers: 

118 km (Grand Morin), 86 km (Petit Morin) 

Morphology type: Fairly flat. Clay 17 %, loam 78 %, sand 5 %. 


Agricultural area, including forests (30 %) and grasslands 

Responsible administration: Direction regionale de l’environnement (DIREN) 

Other special features: Météo France, CEMAGREF 

Facilities 

Number of raingauges: 26 

Closest meteorological radar: Two: Arcis sur Aube and Trappes 

Experimental facilities: Three TDR continuous measurements of soil moisture 

Other special features: Two climatic stations 


Grand and Petit Morin are important test area for hydrologic studies. Orgeval is a subcatchment of the 

Grand Morin. It is an experimental watershed operated by CEMAGREF. It is well instrumented and has 

been monitored for approximately 40 years. Surface moisture measurements have been made since 1997. 

It is also a test site for remote sensing studies and was the location for several field experiments. 


The focus here will be on validation of soil moisture estimates by the SIM model. Of course, relating 

measurements of soil moisture to computed quantities, especially with a coarse resolution model such as 

SIM is not a minor task. However a methodology has been developed in previous field programs such as 

MUREX. The site is well adapted for these comparisons because it is large enough (about 30 SIM grid 

points) and quite flat.


WP-5430 La Beauce region France (Météo-France) 


The main crops in the Beauce region are wheat and corn. Therefore, from September to December, many 

bare soil fields exist before wheat sowing. For spring period, other bare soils are prepared to corn sowing. 

Therefore, at all dates approximately a half of fields are bare soil. This type of site is well adapted for 

validation of satellite soil moisture estimations (flat surface, a large percentage of bare soil). 


Surface: 

40 x 40 km². 


N/A (not a hydrological basin). 


Very flat area. 60 % loam, 30 % clay, 10 % sand. 


Mostly wheat and corn. 

Responsible administration: N/A (agricultural area). 

Other special features: - 

Facilities 

Number of raingauges: None. 

Closest meteorological radar: Trappes. 

Experimental facilities: Gravimetric and TDR punctual measurements (campaigns). 



A large data base was developed in the framework of the national project ACI-Beauce for the years 2003- 

2004. The data base consists of soil moisture, roughness and vegetation measurements as well as remote 

sensing satellite data. 


The objective for the Beauce study is the same as for the Morin with more emphasis on real estimates of 

surface soil moisture. The physical environment is slightly different in term of vegetation cover. It is expected 

that from field measurements and various satellite estimates of surface soil moisture including the H-SAF 

contribution a real estimation will be available. It will be a valuable comparison point for SIM.


WP-5440 Adour-Garonne basin France (Météo-France) 


The area is quite well equipped with precipitation networks. It is also rather well known from the hydrogeological, 

hydrological and climatological points of view. State of the art vegetation maps are available. The 

area has been the location of several land-atmosphere interaction studies. The SIM model was originally 

calibrated there. 


Surface: 102,000 km 2 (Garonne 62,000 km 2 , Adour 16,800 km 2 , Dordogne 23,900 km 2 ) 

Length of main rivers: Garonne 623 km (including springs in Spain), Adour 350 km, Dordogne 480 km 


These are complex river basins which include both head waters in the Pyrenees 

and large sections of plain rivers. 


A mixture of crops and forests 

Responsible administration: Direction regionale de l’environnement (DIREN) 


Facilities 


Closest meteorological radar: Bordeaux-Merignac 

Experimental facilities: Specific equipments for SMOS campaigns 



Coordinated studies for this area started in 1985 in preparation of the HAPEX-Mobilhy program which took 

place in 1986. Field activities, including soil moisture measurements have never ceased since then and new 

developments are planned in the framework of the SMOS programme. 

2 PHD thesis are been completed in 1998 and 2003 dealing with hydrological modelling for the Adour- 

Garonne. 


The planned impact study will consist of 2 parts. First, an additional validation of the H-SAF precipitation 

products will be performed. They will be compared to the operational precipitation maps which are computed 

every day using the standard rain gauges network. Second, the SIM model will be adapted and ran using H- 

SAF precipitation products as forcing. The results will be compared to the standard output. The objective 

these is a global hydrological validation of the products.


WP-5520 Rhine catchment Germany (BfG) 


The investigation of a large scale catchment, such as that of the river Rhine, that covers a variety of morphological and 

climatological conditions as well as different land use types, is considered very effective for a comprehensive investigation 

of the benefit of satellite based meteorological data (rainfall, snow variables, soil moisture). At the Federal Institute of 

Hydrology (BfG) a calibrated HBV model of the river Rhine is running within an environment for water level forecasts at low 

and middle flows. Additionally, detailed in-depth studies on subbasins of the Rhine (Sieg, Saar) were conducted at BfG. 


Surface: Total basin area: 185,300 km², modelled area: about 160,000 km 2 

Length of main Total length: 1,320 km starting at the source of the Vorderrhein at the outlet of Lake Toma (CH), 1,104 

river: 

river-kilometers from official km-0 at Konstanz to Rhine Delta, area of investigation: up to river-kilometer 

Morphology 

type: 


Responsible 

administration: 

Other special 

features: 

Facilities 

Number of raingauges: 


857 at Lobith (Dutch-German boarder) 

Alp and High Rhine: influenced by high mountain area, quarter of which is covered by glaciers; affected 

by numerous glacier and high mountain streams; numerous lakes and reservoirs; 

Upper Rhine: flow through Upper Rhine Tectonic Rift; lowland plain with flatter gradient than the High 

Rhine caused development of network of channels (furcation zone); 

Middle Rhine: deep incised meandering river valleys; Lower Rhine: typical lowland river with wide 

meanders; 

Rhine Delta: flat terrain; in the natural state the watersheds in the sub-catchment depend on the water 

levels of the rivers 

Mixture of forests, meadows, pastures, agricultural crop lands, built-up areas; 

Germany: Wasser- und Schifffahrtsverwaltung (WSV) (= Water and Shipping Administration), Water 

Authorities of the Länder (German Federal States): RP, HE, BY, NW, BW, NI, SL, TH; Switzerland: 

Bundesamt für Umwelt (BAFU); France: Agence de l’eau Rhin-Meuse; Service de la Navigation du 

Nord-Est, Nancy ; The Netherlands: Rijksinstituut voor Integraal Zoetwaterbeheer en 

Afvalwaterbehandeling (RIZA) ; Luxemburg: Administration de la Gestion de l’Eau ; Austria: Amt der 

Vorarlberger Landesregierung; Belgium: Direction Générale des Ressources Naturelles et de 

l’Environnement (DGRNE), Service d'Etudes Hydrologiques (SETHY 

Federal Institute of Hydrology (BfG), Koblenz, Germany; International Commission for the Protection of 

the Rhine (ICPR); International Commission for the Hydrology of the Rhine basin (CHR); Commissions 

Internationales pour la Protection de la Moselle et de la Sarre (CIPMS) 

204 synoptic stations (6-12 h), 45 rain gauges (hourly, TTRR stations) 

Hannover, Essen, Flechtdorf, Neuhaus, Neuheilenbach, Frankfurt/Main, Eisberg, 

Türkheim, München–Fürholzen, Feldberg/Schwarzwald 


In the course of several BfG projects the Rhine catchment was investigated under a number of aspects, e.g. impact of 

climate change on discharges, optimization of flood protection measures. Results are well documented, expert knowledge 

on this catchment is available at BfG. 


The investigational activity within this large catchment will focus on studying the impact of H-SAF satellite based products 

(individually and combined) in operational hydrology with emphasize on water balance component analyses (discharge 

analysis). First the impacts on the entire catchment are investigated on a coarser scale. Model results then will guide 

decisions on further in-detail investigations of sub-catchments (e.g. river Sieg, Saar).


WP-5620 Tanaro river basin Italy (DPC) 


It is an example of relatively large basin in Northern Italy, where the effects of formation and propagation of 

floods are substantially balanced. The alpine characterisation is strong, since a large fraction of the basin 

has altitude exceeding 2000 m, but the impact of the hilly environment (“Langhe” hills) is rather constraining 

for flood formation. 


Surface: 7,985 km 2 


208 km 


Relatively large sub-alpine basin - 3900 m height difference 


Cultivated (47 %), Woods (32 %), Bush and natural grass (14 %), Sparse 

vegetation (4 %) 

Responsible administration: Regional Environment Protection Agency (ARPA) of Piedmont 


Facilities 

Number of raingauges: 107 rain gauges; 25 water level staff 

Closest meteorological radar: 2 (Torino - Bric della Croce, Savona - Monte Settepani) 


Other special facilities: - 


The basin has been intensively studied after the large flood in 1994.The upper part of the catchment, where 

rain is generally more intense, lay on the Ligurian mountains but the larger part is in the Piedmont region 

and here the areas more affected by flood are located. Many assessments were performed, aimed at 

defining the flood prone areas function of recurrence period (resulting in appropriate statements within the 

“Plan for the hydro-geological asset of the Po Basin”). A monitoring network was largely increased, including 

both classic ground stations and new Doppler radar, C band. Here the radar data mosaic and the output 

used for feeding hydrological run/off models were firstly tested, in the framework of real time emergency 

management. In addition to the meteo-hydrological issue, the role of the hydraulic configuration of the valley 

lineament is important. 


The impact study will focus on evaluating the improvement given by the use of satellite derived products, 

both singularly and combined, in the flood forecasting chain. The catchment could be divided in two different 

parts. The first one is greatly mountainous, characterised by torrential flow. The lower part is typically alluvial 

flat, with fluvial flow. The Tanaro discharge into the Po river, so that the discharge itself depends on the Po 

level. Greater attention will be paid on precipitation products. Snow cover will be considered too, since a 

large part of the catchment is higher than 1000 m.


WP-5630 Arno river basin Italy (DPC) 


Often flooded region located close to Florence, densely-populated city and important cultural centre. The 

region is equipped with rain gauges network and within radar cover. A forecasting operational chain is 

already running, representing a good reference for evaluating the project results 


Surface: 8,228 km 2 . 


241 km. 


60 % with height lower than 300 m, 34 % with height between 300 m and 

600 m, and the 9 % between 600 m and 900 m. 


Forests and agriculture. 

Responsible administration: Basin Authority of the Arno River. 


Facilities 

Number of raingauges: 86 rain gauges; 50 water level staff. 

Closest meteorological radar: 1 ( Pisa - San Giusto provides a partial coverage of the catchment). 




The catchment was affected by several events. The most important was probably the flood occurred in 1966, 

which affected also the city of Florence, producing more than 30 casualties and large damages to the 

cultural heritage. Several studies have been performed, and a warning system for flood forecasting has 

recently been set up; thus the site represents a good reference for evaluating the impact of H-SAF products. 



both individual and combined, in the flood forecasting chain. Greater attention will be paid both on the soil 

moisture and snow cover parameters, since during the 1966 flood an important contribution to the in-flow 

was given by rapid melting of the snow fallen during the previous days, on the close Apennines mountains.


WP-5640 Basento river basin Italy (DPC) 


The region is prone to floods and is interesting site for the impact study on the snow cover product. 

The hydrological model running in this basin (NASH) is the most commonly used for emergency 

management at the DPC. 


Surface: 1,535 km 2 . 


157 km. 


17 % is composed by flat area in front of the Ionian sea, 50 % by a hill 

region and 33 % by mountains lower than 1500 m. 


Forest and agriculture. 

Responsible administration: Inter-Regional Authority of the Basilicata basin. 


Facilities 

Number of raingauges: 5 rain gauges; 4 water level staff. 

Closest meteorological radar: 1 (Brindisi, 150 km far from the Basento catchment). 




Although the Basento basin has been often affected by floods and flash floods, no deep studies have been 

performed so far. In the near future the DCP is planning to increase the monitoring network, including the 

installation of some Doppler meteorological radar which ensures coverage of a part of the Basento drained 

area. 



both individual and combined, in the flood forecasting chain. At the time the closest radar to the area is the 

Brindisi one, 150 km far from the Basento river, thus only useful for early warning, without any rain rate 

quantitative estimation and consequently no use for feeding hydrological models. Greater attention will be 

paid on the snow parameter.


WP-5720 Soła river catchment Poland (IMWM) 


Mountainous river with small retention capacity of river valleys, rapid water rising and high risk of flash 

floods. 


Surface: 784.8 km 2 


38.7 km 


Mountainous 


80 % of forests 

Responsible administration: Regional Office for Water Management, Kraków 

Other special features: IMWM, Kraków 

Facilities 

Number of raingauges: 18 in total, 15 of them are telemetric stations 

Closest meteorological radar: Two: Ramża, Brzuchania 


Other special facilities: 10 water gauges 


The Soła catchment is well adapted for hydro-meteorological observations. Observation and measurement 

network consists nowadays of meteorological and hydrological telemetric stations for national and local 

monitoring needs. Dense network of traditional rain- and water gauges provided great amount of data also in 

the past. That was the main reason why the Soła catchment was selected as a test site. The Soła 

catchment was chosen to be modeled within Emergency Flood Recovery Project introduced thanks to the 

world bank loan after a great flood in southern Poland, which took place in 1997. Several studies were also 

performed concerning estimation of maximum reliable precipitation and maximum reliable high waters. Soła 

catchment is located within the extend of a new meteorological radar in Brzuchania (under calibration). 


The impact study will focus on flood forecasting. The upper Soła catchment is a part of the Upper Wisła 

(Vistula) Basin. This is the richest in water part of Poland. Intensive precipitation over a vast area, which lasts 

for a couple of days, may reach up to 200 mm a day. This occurs due to orographic effects on the Northern 

aspects of the Tatra and Beskidy Mountains. On the other hand small retention capacity of the river valleys 

causes rapid rising of water level. The average river fall is 9,8 ‰, so floods are very quick. The most 

hazardous floods originate in upper parts of the Soła river. 

In order to assess the benefit of satellite-derived data, the experimental activity will use satellite data for 

preparation and re-calibration of hydrological models and to increase quality of hydrological forecasting.


WP-5730 Skawa river catchment Poland (IMWM) 


Mountainous river with small retention capacity, rapid water rising and high risk of flash floods. 


Surface: 






606.2 km² 

55.5 km 

Mountainous, 

60 % of forests 

Regional Office for Water Management, Kraków 

IMWM, Kraków 

Facilities 

Number of raingauges: 8 in total and all of them are telemetric stations 

Closest meteorological radar: Two: Ramża, Brzuchania 




94 % of the Skawa catchment is located in the Carpathians and this determines characteristic of the river. 

The Skawa catchment is considered to be the controlling catchment for the results obtained in the Soła 

catchment during hydrological modelling. The research is performed irregularly, in case of hazardous 

hydrological phenomena, such as flash floods or extreme low waters. This aims to create a basis for the 

future prediction of dangerous events such as: 

• Flood in Maków Podhalański in 2004 (almost whole town was under water) 

• Flash floods in the surroundings of Wadowice few months ago, 


The impact study will focus on flood forecasting. The upper Skawa catchment is also very rich in water. The 

Skawa catchment is long and not very wide. It has a dense river network, consisting in majority of short 

streams with a big river falls. The mean annual sum of precipitation in the upper part of the catchment varies 

from 700 to 800 mm. The average river fall is around 5,8 ‰. Conditions in this catchment are very similar to 

those in the Soła catchment. Precipitation and runoff considerably exceeds the mean values for Polish rivers. 

Most flood hazards originate in Soła and Skawa catchments. 

In order to assess the benefit of satellite-derived data, the experimental activity will use satellite data for 

preparation and re-calibration of hydrological models and to increase quality of hydrological forecasting.


WP-5740 Czarna river catchment Poland (IMWM) 


Low-lying catchment with ground monitoring network consisting of telemetric posts. The catchment is located 

within the of extent horizontal beam of one meteorological radar in Brzuchania. High water levels and floods 

are caused by snow-melt or by both melting snow and rain falls. Taking into account existing water reservoir 

and dense settlement, additional satellite information is expected to improve flood control. 


Surface: 






Facilities 


Closest meteorological radar: Brzuchania 



250,4 km² 

23,7 km 

lowland 

40% of forest, 60% arable 

Regional Office for Water Management, Kraków 

IMWM, Kraków 


The Czarna river has its headwaters in Świętokrzyskie Mts. and therefore risk of floods rises due to melting 

snow in early spring. Settlements located in upper part of the catchment are under constant threat of 

floodings. Discharge of water surplus from the Chańcza Reservoir during very high water levels can 

meaningfully influence floodings below the reservoir. 

Hydrological forecasting system was implemented in the Czarna catchment (rainfall-runoff model and flood 

wave transformation) as a part of local warning system for Staszów administrative district. 


The impact study will focus on the conversion of effective precipitation and snow into surface runoff. In order 

to assess the benefit of satellite-derived data, the experimental activity will be used in a regional flood 

modelling. Additionally, a fuzzy expert system model is expected to develop for the rainfall-runoff conversion 

system in the area.


WP-5820 Myjava river basin Slovakia (SHMÚ) 


Flash floods were occurred in last years in this catchment 




65.5 km 


Lowland-Downs 


Arable Land 

Responsible administration: Slovak Hydro-Meteorological Institute (SHMI). 


Facilities 

Number of raingauges: 3 telemetric 

Closest meteorological radar: C-band Doppler weather radar Malý Javorník, range cca 50 km 

Experimental facilities: Local warning system is installed in this catchment 



None 


The impact study will focus on water balance components analyses by means of precipitation and outflow. 

Rainfall-runoff model Hron will be used for testing the satellite derived products - precipitation and soil 

moisture to improve operational hydrology and flash flood forecasting and warning in this river basin. 

In order to assess the benefit of satellite-derived data, the experimental activity will focus on studying the 

impact of H-SAF satellite-derived precipitation rate, cumulative precipitation and soil moisture with 

emphasize on water balance components analyses (precipitation and outflow).


WP-5830 Nitra river basin Slovakia (SHMÚ) 


The Nitra river basin is a significant industrial, mining and agricultural region of Slovakia. Flash floods have 

occurred in the upper part of the basin recently. 




75.3 km 


Lowlands-Upland 


Forest, Arable Land 



Facilities 

Number of raingauges: Total 10, 6 of them telemetric 

Closest meteorological radar: C-band Doppler weather radar Malý Javorník, range ∼ 100 km 




None 


The impact study will focus on the improvement of hydrological forecasting and water management in this 

catchment and the efficiency in agriculture irrigation. 

In order to assess the benefit of satellite-derived data, the experimental activity will be focused on studying 

the impact of H-SAF satellite-derived precipitation rate, cumulative precipitation and soil moisture in 

operational hydrology with emphasize on water balance components analyses (precipitation and outflow).


WP-5840 Kysuca river basin Slovakia (SHMÚ) 


Mountain catchment, rich of precipitations, significant tributary into water reservoir Hričov on Vah cascade. 




57.2 km 


Upland-Highlands 


Forest 



Facilities 


Closest meteorological radar: None 




None 


The impact study will focus on studying the impact of H-SAF satellite-derived precipitation rate, cumulative 

precipitation and snow parameters in operational hydrology and water balance components analysing 

(precipitation and outflow). Rainfall-runoff model Hron will be used for testing the satellite products to 

improve hydrological forecasting, water management mainly in the industry and to improve flood protection 

in the mountainous regions of Slovakia. 

In order to assess the benefit of satellite-derived data, the experimental activity will focus on comparison of 

hydrological model runs with and without H-SAF satellite derived products.


WP-5850 Hron river basin Slovakia (SHMÚ) 


The Hron river basin was selected as a representative for mountainous basin which runoff generation from 

snow-melting process plays important role. No water reservoirs are located in the basin. 




98.4 km 


Highlands 


Forest 



Facilities 


Closest meteorological radar: C-band Doppler weather radar Kojšovská hoľa, range cca 100 km 




Model HBV was used in this catchment during EFFS project. 

Model Hron, which will be used for testing, was developed on this catchment. 


The impact study will focus on studying the impact of H-SAF satellite-derived products with emphasizes to 

snow parameters and cumulative precipitation in operational hydrology. 

In order to assess the benefit of satellite-derived data, the experimental activity will based on rainfall-runoff 

model Hron, which will be used for testing the satellite products to improve hydrological forecasting and flood 

protection in central part of Slovakia.


WP-5860 Topla river basin Slovakia (SHMÚ) 


This subcatchment represents natural hydrological regime of one of tributary Bodrog river basin in eastern 

part of Slovakia and is situated in the range of new modern weather radar. 




85.2 km 


Upland 


Forest, Arable Land 



Facilities 


Closest meteorological radar: C-band Doppler weather radar Kojšovská hoľa, range cca 50 km 




Model Mike 11 was tested in the framework of a Slovak-Danish project. 


The impact study will focus on studying the impact of H-SAF satellite-derived products with emphasizes to 

snow parameters and cumulative precipitation in operational hydrology. 

In order to assess the benefit of satellite-derived data, the experimental activity will be conducted by rainfallrunoff 

model NAM (as a part of Mike 11 model) for testing the satellite products to improve hydrological 

forecasting and generally to support civil protection in the area of Bodrog river basin.


WP-5920 Susurluk river basin Turkey (ITU) 


Availability of different meteorological data sources including radar, ground, and some satellite data 


Surface: 






Facilities 

Number of raingauges: 17 automatic, 3 synoptic 

Closest meteorological radar: Balıkesir radar 



22,399 km 2 (will be divided into sub-basins) 

272 km 

Mix of flat and highlands and agricultural land 

Forests in the north and scarce vegetation in the south 

Ministry of Forest and Environment 

TSMS, SHW 


There are intense industrial areas; Flood risk and inundation maps; Water resources management and 

development; Agriculture 


The impact study will focus on the conversion of effective precipitation into surface runoff and possible flood 

frequency analysis with preliminary flood inundation map preparation with 5, 10, 25, 50 and 100 year return 

period. In order to assess the benefit of satellite-derived data, the experimental activity will be used in a 

regional flood frequency modelling by considering cumulative semi-variograms leading to a suitable Krigging 

numerical model for this drainage basin. Additionally, a fuzzy expert system model is expected to develop for 

the rainfall-runoff conversion system in the area.


WP-5930 West Black Sea basin Turkey (ITU) 


It is observed from the previous records that this area is prone to potential flood hazards and such a detailed 

study will enhance the flood hazard mitigation in the area. 


Surface: 






Facilities 

Number of raingauges: 23 automatic, 7 synoptic 

Closest meteorological radar: Zonguldak radar 



29,598 km 2 (will be divided into sub-basins) 

350 km 

There is a narrow shoreline limited by rather suddenly rising escarpments 

which enhance orographic rainfall. 

The are is dominantly covered by forests and shrubs. 

Ministry of Forest and Environment 

TSMS, SHW 


Flood risk and inundation maps; Water resources management and development; Agriculture 


In order to assess the benefit of satellite-derived data, the experimental activity will be used in the expert 

system modelling with soft computing based on the fuzzy systems approach. Additionally, Kriging modelling 

will be employed for regional rainfall, runoff and groundwater recharge maps.


WP-5940 Upper Euphrates basin Turkey (METU + AU) 


The eastern part of Turkey is mountainous and valuable in terms of snowmelt. The basin is located at the 

headwater of Euphrates River which is fed by snowmelt during the spring months. Euphrates originates from 

the mountainous, rough topography of Eastern Anatolia. For this mountainous topography of Eastern 

Anatolia, snow is the main supply of the Euphrates River. Among the several branches of Euphrates River, 

Upper Euphrates River Basin, which is also known as Karasu Basin, receive high amount of its annual 

discharge mainly from snowmelt runoff. It was the main pilot basin for snow hydrology modelling due to 

gauging and accessibility. 




250 km 


Mountainous, elevation ranges between 1125-1500 m. Hypsometric mean 

elevation is 1977 m. 




Facilities 


Closest meteorological radar: None 



Pasture, cultivated land and bare land 

SHW (State Hydraulic Works) and EIE (Electrical Power Resources Survey 

and Development Administration) 

Snow pillow, snow depth, snow lysimeter, radiation and albedo 

measurement with Automated Snow-Meteorological Stations 


Water resources management and development. Flood forecasting. Flood risk for agricultural lands. 

Optimum reservoir operation of large dams located on Euphrates River. A number of Master and PhD Thesis 

were completed. Projects supported by NATO and DPT (Turkish State Planning Organization) were 

completed on hydrological model application with GIS and RS integration. SRM which is an operational and 

physical model was applied to the basin where it is divided into several elevation zones. NOAA and MODIS 

satellite snow cover and daily snow albedo are being used as inputs or output comparison parameter of 

these models. 


The impact study will focus on the use of satellite derived data in an operational model. The Euphrates-Tigris 

basin is largely fed from snow precipitation over the uplands of north and eastern Turkey. To address the 

need for improved management of a sustained period of high flows during the spring resulting from melting 

of the snowpack, snowmelt model will be applied over the mountainous topography. 



an operational model e.g. SRM) for a large scale basin.


WP-5950 Upper Karasu basin Turkey (AU) 



headwater of Upper Euphrates Basin which is fed by snowmelt during the spring months. It is one of the pilot 

basins for snow hydrology modelling since it is a representative one for mesoscale modelling as a sub-basin 

of Upper Euphrates Basin. 




80 km 

Morphology type: Mountainous, elevation ranges between 1640 – 3112 m. 

Vegetation type: Pasture (59 %), Bareland (14 %), Fallow (10 %), Forest (1.5 %) 

Responsible administration: SHW (State Hydraulic Works) and EIE (Electrical Power Resources Survey 

and Development Administration) 


Facilities 





None 




Water resources management and development. Flood forecasting. Flood risk for agricultural lands. 

Optimum reservoir operation of large dams located on Euphrates River. Projects supported by NATO and 

DPT (Turkish State Planning Organization) were completed on hydrological model application with GIS and 

RS integration. The operational model studies including HEC-1, physically based snow energy and mass 

balance models and distributed radiation index models were applied to the basin where it is divided into 

several elevation zones. NOAA and MODIS satellite snow cover and daily snow albedo are being used as 

inputs or output comparison parameter of these models. 


The impact study will focus on flood forecasting and optimum operation of reservoirs. The Euphrates-Tigris 

basin is largely fed from snow precipitation over the uplands of north and eastern Turkey. To address the 

need for improved management of a sustained period of high flows during the spring resulting from melting 

of the snowpack, snowmelt model will be applied over the mountainous topography. 



an operational model for a medium scale basin.


WP-5960 Kırkgöze basin Turkey (AU) 



headwater of Upper Karasu Basin which is fed by snowmelt during the spring months. It is one of the pilot 

basins for snow hydrology modelling since it is a representative one for micro scale modelling as a sub-basin 

of Upper Karasu Basin. 




15 km 

Morphology type: Mountainous Elevation ranges between 1830-3140 m. 

Vegetation type: Pasture (86 %), Bare land (7 %), Forest (4 %) 

Responsible administration: SHW (State Hydraulic Works) 


Facilities 





None 




Projects supported by NATO and DPT (Turkish Stat Planning Organization) were completed on hydrological 

model application with GIS and RS integration. The conceptual model studies including, SLURP and HBV 

were applied to the pilot basin it is divided into several elevation zones. Current studies aim at real time 

forecast by using precipitation and temperature data from Numerical Weather Prediction Models (ECMWF 

and MM5). NOAA and MODIS high-resolution snow cover and daily albedo are being used with these 

models. HBV model has been calibrated using multi-objective criteria. 


The impact study will focus on flood forecasting and water management. The Euphrates-Tigris basin is 

largely fed from snow precipitation over the uplands of north and eastern Turkey. To address the need for 

improved management of a sustained period of high flows during the spring resulting from melting of the 

snowpack, snowmelt model will be applied over the mountainous topography. 



an operational model (e.g. HBV) for a small scale basin.







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5633 Italy → → ← → ← 

5640 Italy 

5641 Italy → →← 

5642 Italy → → ← 

5643 Italy → → ← → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

(continue) 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR





2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

5700 Poland 

5710 Poland 

5711 Poland → →← 

5712 Poland → →← →← 

5713 Poland → →← →← 

5724 Poland → →← → ← → ← 

5720 Poland 

5721 Poland → →← 

5722 Poland → → ← 

5723 Poland → → ← → ← 

5730 Poland 

5731 Poland → →← 

5732 Poland → → ← 

5733 Poland → → ← → ← 

5740 Poland 

5741 Poland → →← 

5742 Poland → → ← 

5743 Poland → → ← → ← 

5800 Slovakia 

5810 Slovakia 


5812 Slovakia → →← →← 

5813 Slovakia → →← →← 

5814 Slovakia → →← → ← → ← 

5820 Slovakia 



5823 Slovakia → → ← → ← 

5830 Slovakia 



5833 Slovakia → → ← → ← 

5840 Slovakia 



5843 Slovakia → → ← → ← 

5850 Slovakia 



5853 Slovakia → → ← → ← 

5860 Slovakia 



5863 Slovakia → → ← → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

(continue) 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR





2005 

T 0 

2006 

T 0 +12 

2007 

T 0 +24 

2008 

T 0 +36 

2009 

T 0 +48 

2010 

T 0 +60 

5900 Turkey 

5910 Turkey 

5911 Turkey → →← 

5912 Turkey → →← →← 

5913 Turkey → →← →← 

5914 Turkey → →← → ← → ← 

5920 Turkey 

5921 Turkey → →← 

5922 Turkey → → ← 

5923 Turkey → → ← → ← 

5930 Turkey 

5931 Turkey → →← 

5932 Turkey → → ← 

5933 Turkey → → ← → ← 

5940 Turkey 

5941 Turkey → →← 

5942 Turkey → → ← 

5943 Turkey → → ← → ← 

5950 Turkey 

5951 Turkey → →← 

5952 Turkey → → ← 

5953 Turkey → → ← → ← 

5960 Turkey 

5961 Turkey → →← 

5962 Turkey → → ← 

5963 Turkey → → ← → ← 

↑ 

KO 

↑ 

RR 

↑ 

PDR 

↑ ↑ 

WS-1 CDR 

↑ 

SIRR 

↑ 

STRR 

↑ 

WS-2 

↑ 

SVRR 

↑ 

ORR

H-SAF Project Plan 2.0, October 2007 - Update PP-2.2, 10 April 2008 - Chapter 8 (Risk analysis) Page 156 

8. Risk analysis and management 

8.1 General approach 

The “Stepwise development approach” adopted for H-SAF (see Fig. 5 in Chapter 2) is the main 

safeguard against major failures. In fact, initial developmental risks are minimised by starting with 

available databases, proven algorithms and current instruments. This will allow early delivery of 

prototype products to the end-user to Cluster-4 participants for familiarisation with formats, 

presentations and generic product aspects. To pass to the demonstrational products at approximately T 0 

+ 24 the main developmental activities (thus risks) are: 

• integrations of the various software/hardware components so as to transfer product generation from 

a scientific to an operational environment; 

• calibration/validation activities so as to characterise the products to be distributed to user. 

Further developments will depend on augmented databases, advanced algorithms, new instruments 

becoming available, more extensive cal/val activity, and user feedback, particularly from the 

Hydrological validation programme being activated at T 0 + 24. There are risks associated to such 

activities, but the effect of failure will never be catastrophic: at most, data quality will not improve after 

the demonstrational version with the foreseen progress rate (that per-sé would be a failure, since the 

demonstrational products will not have the quality foreseen by the User Requirements Document at the 

end of the 5-year Development Phase). This means that “technical risks” will generally be low and their 

effect would be a “graceful degradation” of data quality. 

“Programmatic risks” may be more serious. The H-SAF undertaking is shared among 12 participating 

Countries, with several units in certain Countries. There are two families of activities: satellite products 

generation and hydrological experimental utilization. The product generation activity is split into three 

themes, with production centres physically distinct; two of them are actually further split between two 

centres, that brings the number of production centres to five, in five different Countries. The 

hydrological activity is spread over 7 Countries (and more units in some Country). Under this condition, 

coordination could represent a serious risk. 

However, the work programme organisation (see WBS-01 in Chapter 2) has been structured so as to 

minimise programmatic risks. For each theme, a “Cluster” of participants has been defined, with one 

Participant ensuring coordination within the theme. The general Coordination task (WP-1000), in 

addition to classical management activities, also includes a monitoring structure (the centralised archive, 

WP-1200) and the engineering function for standardisation and configuration control (WP-1300) to 

ensure minimisation of programmatic risks in addition to technical risks. 

The feedback between Cluster-4 (Hydrological validation) and Clusters 1+2+3 (Products generation) 

will have to be properly organised. The cal/val activities attached to products generation could be a 

vehicle for this purpose, within the constraint that the Hydrological validation must remain independent 

of data production. 

8.2 Specific risk analysis 

Due to the wide number of activities (5 WP’s of 1 st level + 24 of 2 nd level + 97 of 3 rd level shown in 

Table 4 of Chapter 2, + 259 of 4 th level mentioned in the text !) an exhaustive risk analysis would imply 

a document of size comparable to this text. However, since, as stated before, the H-SAF stepwise 

development approach is safe from dramatic failures, we limit ourselves to offer here a short list of 

major risks, Cluster by Cluster, including the Coordination task. The analysis includes the identification 

of the potential risk, the problem it represents, the management provision and the risk rate (probability 

that the risk materialises).


Coordination task (WP-1000) 

R-1.01 - Development of the centralised archive and the connections with U-MARF. 

Potential problem - The monitoring facility is off-line, but also serves for addressing products to the 

scientific community including that one involved in the Hydrological validation programme. This has 

sizeable technological implications. 

Risk management - A certain number of hydrological units may recover the data from their 

corresponding meteorological service, that generally gets the data directly from the GTS. 

Risk rate - Low. 

R-1.02 - Compliance with engineering standards. 

Potential problem - Each production centre (there are 5) will use as far as possible its own SW/HW 

environment. Although portability is not a requirement, the compliance with standards is a prerequisite 

for credibility and updating capabilities. 

Risk management - The “Engineering” module of WP-1000 will take care of issuing standard criteria 

applicable to all participants in charge of products generation. 

Risk rate - Medium-high. 

R-1.03 - Feedback from users and hydrological units. 

Potential problem - The results from the Hydrological validation programme are needed for product 

quality improvement. Hydrologists might not be fast enough to report back and to emphasise the 

features relevant for product improvement. 

Risk management - Staffing of WP-1000 in Italy includes the Departimento Protezione Civile (DPC), 

also taking part to the Hydrological validation programme. Also, WP-5100 will take care of E&T on 

the use of satellite data in hydrology. 

Risk rate - Medium. 

R-1.04 - Inter-Cluster schedule synchronisation. 

Potential problem - Developments in the different Clusters are currently planned so as to have a 

demonstrational product delivery at approximately T 0 + 24. This is needed in order to leave enough 

time for the execution of the Hydrological validation programme. 

Risk management - The production lines from Clusters 1, 2 and 3 are totally independent. Delay in one 

chain will not propagate to other chains. Start of release of demonstrational products from different 

Clusters or within Clusters can be de-phased if needed. 


Cluster 1 (WP-2000) 

R-2.01 - Availability of satellite direct-read-out. 

Potential problem - Direct acquisition of satellites at the Rome station is essential, due to the timeliness 

requirement for the precipitation products (15 min for data from LEO/MW, 5 min for data from SEVIRI 

+ LEO/MW, not including product transmission time via, e.g., EUMETCast). Missing acquisition 

would cause not compliance of product availability timeliness with user requirement. 

Risk management - Direct acquisition is partially backed-up by EUMETCast. Near-Real-Time 

acquisition from EUMETCast is anyway needed to cover areas outside the acquisition range of the 

Rome station. 

Risk rate - Low in general. For DMSP and MetOp, see R-2.02 and R-2.03, respectively.


R-2.02 - Acquisition of MW data from DMSP. 

Potential problem - Data from the military DMSP (SSM/I and now SSMIS) are currently not received in 

Rome. Work is in progress. Until SSM/I or SSMIS are acquired, the only MW data will come from 

NOAA and MetOp AMSU/MHS, but product quality will be inferior. 

Risk management - For the short term, a link with UKMO is envisaged. Attempts to include SSM/I- 

SSMIS data in the EUMETCast transmission programme will be done. Direct acquisition is planned for 

the long term. According to plan, near-real-time data should be available at the end of the Project. 


R-2.03 - Acquisition of AMSU and MHS from MetOp. 

Potential problem - MetOp-1 has been launched successfully, but does not have a backup in orbit. 

Risk management - In case of MetOp-1 failure, the MetOp-2 launch would be anticipated. Anyway, 

there will be at least two NOAA satellites in orbit equipped with AMSU and MHS. 


R-2.04 - Availability of instrument processors. 

Potential problem - Optimised processors are in principle available for all selected instruments, but 

some (specifically for SSMIS) are not yet implemented at CNMCA. Integration problems may arise. 

Risk management - SSMIS data acquired from UKMO or by EUMETCast are already pre-processed. 

The processor will be procured contextually with direct-read-out, at the end of the Development Phase. 

Risk rate - Low-medium. 

R-2.05 - Baseline software integration. 

Potential problem - The software will be implemented on the base of processing methods and databases 

developed and tested in a scientific institute (CNR-ISAC), using different platforms and operating 

systems from what is available at CNMCA. Integration problems may arise. 

Risk management - Current analysis has not overemphasized this problem. The “Engineering” module 

of WP-1000 will minimise this sort of problems by instructing about standards to be complied with. In 

case of difficulties, the schedule of the first products release will be affected (see R-2.13). 


R-2.06 - Suitability of the CNMCA hardware to support the envisaged computational load. 

Potential problem - The precipitation retrieval software developed at ISAC has so far being run in a 

scientific environment, timeliness-free. In H-SAF, timeliness is a major user requirement. At the 

present stage of assessment, it cannot be stated that the hardware currently available at CNMCA is 

undoubtedly able to guarantee the required throughput. 

Risk management - Current analysis has not overemphasized this problem. If need arises, additional 

hardware will be procured, but this could affect the schedule of the first products release (see R-2.13). 


R-2.07 - Development of improved retrieval algorithms. 

Potential problem - The need for an early release to activate the Hydrological validation programme will 

force accepting products of quality as allowed by currently consolidated methods. Improved methods 

will focus on full exploitation of sounding channels of SSMIS, advanced AMSU/MHS processing 

including resolution enhancement, SEVIRI+MW fusion by “morphing” to replace “rapid-update”, etc.: 

however, all these activities imply risks of delays of pre-operational products or of disappointing results. 

Risk management - Having decoupled the release of demonstrational products, the development of 

improved methods will be performed off-line, associated to all appropriate testing and validation. Early 

results from the Hydrological validation programme will be instrumental. 

Risk rate - Low-medium.


R-2.08 - Augmentation of the cloud-radiation database. 

Potential problem - In the current retrieval scheme, the quality of precipitation products will depend on 

the availability of representative samples in the cloud-radiation database. Currently the database 

includes a substantial amount of samples in the Mediterranean and southern Europe areas, and very few 

in north-west Europe. In other areas the product quality could be lower. 

Risk management - Provision is made in the Project Plan for augmenting the cloud-radiation database, 

especially in central-eastern Europe. A few Participants to Cluster-1 will provide documented 

meteorological events data, that will be converted into cloud-radiation models by CNR-ISAC. 


R-2.09 - Availability of cal/val data for development and follow-on operations. 

Potential problem - Precipitation observation from space is a very indirect technique and reflects a much 

ill-conditioned problem. Accurate calibration coefficients tuning at various steps of the retrieval 

algorithm is necessary. Due to the variability of precipitation types and of the geographical/climatic 

conditions across Europe, calibration will need to be separately tuned over several conditions. 

Risk management - The initial “calibration” performed by CNR-ISAC contextually with algorithm 

development will be extended by exploiting the contribution of several Participants to Cluster-1. Their 

activity will mostly refer to “validation” of the retrieved product, that could be used to trace back certain 

error features to defects of calibration. However, at least “characterisation” of the measurement’s error 

structure will be ensured, so that data utilisation can be properly guided. 


R-2.10 - Integration of results from developmental activities of Cluster participants. 

Potential problem - Several Participants will contribute to Cluster-1 by developmental activities for 

improved precipitation products over their area. Certain activities will have prompt utilisation (e.g., for 

cloud-radiation database augmentation, for parameterisation of effects such as surface emissivity, etc.), 

other ones (e.g., alternative algorithms) have little chance to be exploited since their inclusion into the 

overall processing chain may create more problems than benefits. 

Risk management - The software to be implemented will have a modular structure to enable, in 

principle, replacement of one module by an advanced one. The “Engineering” task in WP-1000, 

involving standardisation instructions, should favour incorporating updates from different sources. The 

cost/benefit ratio of any updating operation will be carefully checked. 


R-2.11 - Quality of the products generated by assimilation in a NWP model. 

Potential problem - Precipitation products (rate and accumulated) will be generated by a limited-area 

NWP model currently being used at CNMCA, after extension of the covered area, as a safeguard against 

occasionally missing observations and for space-time continuisation purposes. Data quality will be 

difficult to be well characterised since the Validation programme is tuned to validate observed data 

Risk management – The NWP model in use at CNMCA has been submitted (and uses to be often resubmitted) 

to extensive validation, though not specifically tuned to the precipitation products. Some 

special effort will be made for H-SAF, with the help of the Validation programme (WP-2300). 

Risk rate - Low.


R-2.12 - Timeliness of products distribution. 

Potential problem - The “delay” requirements (15 min for MW accurate measurements on a orbit-byorbit 

base, 5 min for IR-MW merged products) are intended as “readiness for distribution” at the 

production centre (CNMCA). End users will acquire the products with a delay depending on their 

connection with CNMCA and/or EUMETCast, or the EUMETSAT U-MARF. 

Risk management - Since the centralised archive connected to U-MARF is installed at CNMCA (under 

WP-1200 responsibility), the products will be available for self-service practically at the same time of 

the end of process: but the acquisition time at end-users upon inquiry is out of H-SAF control. Those 

users that are connected to CNMCA via regional branches of the GTS or by bi-lateral arrangement may 

have faster acquisition, others using EUMETCast less fast but still with a delay of few minutes. WP- 

1200 will arrange these issues as appropriately as possible. 

Risk rate - Low for centres connected to CNMCA or equipped with EUMETCast reception. Not 

applicable for U-MARF (self-service). 

R-2.13 - Schedule of Versions release. 

Potential problem - The timing of demonstrational products release is constrained by two conflicting 

requirements: 1) to provide data on a regular basis at the earliest possible date so as to enable the 

Hydrological validation programme to last possibly three years; 2) to provide data of acceptable quality 

and well characterised error structure. As a result of several risks as identified in previous paragraphs, 

the nominal date of T o + 24 could be at risk. The timing of pre-operational products release, that 

incorporates main improvements, is less critical, but still must come early enough to enable 

Hydrologists evaluating the impact of improved data quality. 

Risk management - Before demonstrational products release, a number of prototypes will be distributed 

for early start of Hydrologists to at least familiarise with data structures and formats. The CDR (Critical 

Design Review) will assess which products can be released at T 0 + 24 or so. If the delay is such that 

even the target of T 0 + 30 is unrealistic, than the definition of the demonstrational service will be 

descoped. The User Requirements Document (URD) defines nominal and threshold performances of 

products for being acceptable for release. For pre-operational products release, the flexibility is such 

that a nominal date (currently stated as T 0 + 42) might not be necessary: the various improved modules 

could be implemented when ready and sufficiently tested, under control by the Configuration 

management task (under WP-1300). 

Risk rate - Medium-high. 


R-3.01 - Acquisition of ASCAT from MetOp. 

Potential problem - MetOp-1 has been launched successfully and ASCAT is working properly, but the 

satellite does not have a backup in orbit. A MetOp-1 failure would prevent surface soil moisture be 

generated until MetOp-2 is launched. If the ASCAT payload fails, but the other primary instruments 

work, it is unlikely that MetOp-2 launch is anticipated. ERS-2 is end-of-life. The use of other 

scatterometers (QuikScat) is not foreseen (unsuitable frequency and totally different processing chain). 

Risk management - In case of MetOp-1 launch failure, the MetOp-2 launch would be anticipated. 

Meanwhile, the part of activity based on the ERS-2 scatterometer will be possible to continue until the 

satellite is active. The product for the roots region could still be generated, though based on less input 

data. Other possibilities (passive MW radiometry and SAR) are considered only as demonstration 

activities not budgeted within H-SAF). 

Risk rate - Low in terms of probability of the event, but highest impact if it happens.


R-3.02 - Calibration and validation problems. 

Potential problem - Not many Participants (actually, only Belgium and France in addition to Austria and 

ECMWF) have offered validation activities for soil moisture. In addition to scarce support, there is the 

problem of difficult comparison between this large-scale product and the sparse and punctual nature of 

ground measurements. 

Risk management - In addition to the activity explicitly labelled as Validation (WP-3300), further input 

information will be acquired from the Hydrological validation programme that, in several cases, implies 

soil moisture measurements over test sites. Comparison with modelled soil moisture rather than actual 

measurements also would help. 


R-3.03 - Developmental activities. 

Potential problem - France and Italy have offered developmental activities in the area of soil moisture. 

The offered activities present distinct risks. The activity of France is centred on the SMOS project. 

This is a totally new satellite development that implies risks of launch or payload failure, as well as risks 

that the expected mission objectives (soil moisture significant of the roots region) are not achieved. The 

activity of Italy considers passive MW radiometry for large-scale surface soil moisture and L-band SAR 

for high-resolution soil moisture in the roots region. Apart from the need for demonstration, the activity 

is foreseen on a best effort basis outside the H-SAF budget and will only cover the Italian national 

territory, thus cannot provide backup to the baseline use of ASCAT in case of MetOp launch failure (see 

R-3.01 above). [Note: in PP-2.0 the demonstration activity from Italy has been withdrawn]. 

Risk management - Collaboration with the SMOS project will anyway be pursued at least in the area of 

modelling soil moisture in the roots region in the framework of the ECMWF activity (WP-3200). As 

for MW radiometry and L-band SAR, the opportunity of resuming the Italian offer and transforming the 

demonstration activity into some sort of undertaking will be considered in case of MetOp/ASCAT 

failure. 

Risk rate - If MetOp/ASCAT are successful, the question of risk is irrelevant. Otherwise risk is high. 


R-4.01 - Coordination of work for shared core products. 

Potential problem - The activity of generating core products is shared on the basis of flatlands and forest 

(Finland responsibility) and mountainous regions (Turkey responsibility). Boundaries between the two 

activities are not too sharp. Overlapping areas can occur (that is not a problem) and gaps as well (that 

would be a problem). 

Risk management - Appropriate coordination between the two Participants involved (Finland and 

Turkey) will minimise the probability of gaps in the product coverage. 


R-4.02 - Satellite data availability. 

Potential problem - Currently, data from DMSP (SSM/I and SSMIS) are received via UKMO, and EOS- 

Aqua (AMSR-E) via ftp. Although the time-resolution requirement for snow product is rather 

comfortable (24 h to be reduced to 6 h when moving to the Operational Phase), the target timeliness (1 h 

after the observation time) is at risk. The main drawback of late availability of MW images is that the 

Snow status and Snow water equivalent products might fail compliance with timeliness requirements. 

Risk management - An attempt will be made with EUMETSAT to have SSM/I-SSMIS data included in 

the EUMETCast transmission schedule. For AMSR-E, that could be in principle received in real-time 

by the same (existing) stations used to receive MODIS, the problem is with NASA management of the 

satellite operations, thus could be attempted to be solved. 

Risk rate - Medium.


R-4.03 - Quality of the Snow Water Equivalent product. 

Potential problem - Appropriate instruments to measure SWE from space are not available. The most 

informative ones make use of relatively high frequency MW (at low frequency dry snow tends to be 

transparent). Support from ancillary and auxiliary information, e.g. from GIS and very sparse snowobserving 

sites), is largely necessary. This implies that it is difficult to anticipate what the product 

accuracy will be, and that the risk of irregularly distributed performances is high. 

Risk management - In order to control the quality of SWE, since the instantaneous measurement is 

subject to large uncertainties, the best approach consists of continuous tracing of the product evolution 

with time. Use of ASCAT also is foreseen, especially to appreciate variations. 


R-4.04 - Problems of calibration and validation. 

Potential problem - The experience of the Institutes responsible of snow products generation so far has 

been mainly limited to national application. Extending the coverage across the whole Europe will imply 

severe problems of calibration, since auxiliary and ancillary data are needed for processing, and 

transportability of the calibration practise to different geo-morphological and climatic conditions is 

limited. Unfortunately, not many Participants (actually, only Belgium, Germany and Poland in addition 

to Finland and Turkey) have offered validation activities for snow parameters. 

Risk management - In addition to the activity explicitly labelled as product Validation (WP-4300), 

further input information will be acquired from the Hydrological validation programme that, in several 

cases, implies snow parameter measurements over test sites. 


R-4.05 - Developmental aspects. 

Potential problem - It may be expected that, particularly in mountainous regions, the space resolution of 

snow products achievable by the instruments so far selected for use in H-SAF will not be satisfactory 

for hydrological purposes. High resolution, specifically of Snow Water Equivalent, would require SAR, 

but the frequencies currently adopted by operational SAR are too low, so that dry snow is essentially 

transparent. Developmental activities in the area of snow, additional to that one of Finland and Turkey, 

has only been offered by Italy on a best effort basis outside the H-SAF budget, and will only cover 

selected sites of the Italian national territory. [Note: in PP-2.0 the demonstration activity from Italy has 

been withdrawn]. 

Risk management - Although the offer from Italy has been withdrawn from PP-2.0, it could be resumed 

if the case of insufficient characteristics of SWE arises. 



R-5.01 - Coordination problems 

Potential problem - Cluster-4 is supported by 9 Countries (and more units in several Countries), 8 of 

which performing impact studies over test sites (there are 23 !). Implementation of the experiments will 

not be a problem, since each Unit has proposed activities with a strong heritage. Optimization of 

activities so as to have a good compromise between redundancies (useful for improving the level of 

confidence in the results) and coverage of situations (i.e. representativeness) may be a serious problem. 

Risk management - Experimental activities are expensive and only can be afforded if embedded in preexisting 

activities financially supported by national/local authorities. Therefore, tough coordination will 

not be possible. It will rather be an attempt to harmonise a series of activities being carried out in 

compliance with independent local constraints. The amount of support for the Hydrological validation 

programme is rather large. The 22 selected test sites cover a rather representative range of situations. 

Risk rate - Medium-high.


R-5.02 - Understanding of the objectives of the Hydrological validation programme 

Potential problem - When analysing the work programmes submitted by the various Participants, a trend 

can be detected to mix up the “product” validation (i.e. “distance” of the measured from the true value 

of the parameter) and the “hydrological” validation (i.e., assessment of the impact of the product on the 

hydrological application, e.g. flood forecasting). A positive aspect of this is that the cal/val activity will 

be fed by much more input than nominally declared. The risk is that the independent assessment of data 

benefit, a pre-requisite for supporting the proposal for a possible follow-on Operational Phase, tends to 

be forgotten (also because of the practical reason that it represents a more difficult undertaking). 

Risk management - The two project Workshops at T 0 + 18 and T 0 + 48 will be structured the first to 

monitor the consistency of detailed planning with the objective, the second to report according to the 

specific questions that are placed on the table, e.g. the preliminary results of the impact studies. 


R-5.03 - Feed back of Cluster 4 activities to the product-generation responsible Clusters 1, 2 and 3. 

Potential problem - Additional to the main objective of independent assessment of the benefit of the new 

products, the Hydrological validation programme can contribute to data quality improvement on-line 

with the H-SAF continuing development scheme (see Fig. 5 in Chapter 2). If not well structured, this 

dialogue could fail, with the result that possibilities of helping convergence between user requirements 

and product performances could be missed. 

Risk management - Fig. 5 shows that feedback from users is expected in response to prototype products 

distribution, to the regular distribution of demonstrational products as an element relevant to move to 

pre-operational products, and for the assessment of the benefit of the final products to place as basis of 

the possible Proposal for the follow-on Operational Phase. The Cluster 4 leader (Poland) has a specific 

interface with the Coordination leader (see previous R-1.03, that also reminds the role of WP-5100 for 

E&T on the use of satellite data in hydrology). 


Conclusion of the risk analysis 

The analysis of the various risks highlights that system-level risks, thanks to the stepwise development 

approach, do not exist. The following risks have got relatively higher rates: 

• technical - only two: 

- [R-1.02] - products to be generated in five different SW/HW environments, with limited chance 

to be forced to common standards; 

- [R-3.01] - failure of ASCAT in orbit, with dramatic effect on Cluster-2, especially if the other 

primary instruments are successful, thus the launch of MetOp-2 is not anticipated (that would be 

the case if some of the primary instruments on MetOp-1 fails); 

• programmatic: 

- [R-2.13] - schedule of demonstrational products release for Cluster-1 as a result of possible 

convoluted slippage of a number of developmental activities, though individually apparently onhand; 

- [R-5.01] - coordination within Cluster-5, due to the large scatter of activities subject to local 

technical and administrative constraints in 7 different Countries. 

Reference to the Appendix 

The Appendix, delivered as a separate document, includes: 

A.1 - The list of WPD sheets (5 for 1 st level + 24 for 2 nd level + 97 for 3 rd level + 259 for 4 th level) 

A.2 - Work Package Description sheets for 1 st , 2 nd and 3 rd level; 4 th level mentioned in the 3 rd level sheet 

A.3 - The list of Deliverables and their location in H-SAF documentation (with time reference).

(H-SAF) PROJECT PLAN - Version 2

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