Atef O. Sherif - CIMAP

Cairo University 

FVLab 

Presented By; 

Atef O. Sherif 

Aerospace Department 

Faculty of Engineering 


23 March 2010

15 May 2008 A. O. Sherif 

� General Overview 

� The Numerical Weather Forecast model 

� Model Validation and Enhancements 

� Regional and National Models 

� Sample Applications 

� Conclusions and Recommendations 

NFS-AST Workshop on Supercomputing Applications in Climate and Remote Sensing 

Cairo Egypt, 13-16 May 2008 


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� 1998 FVLab Establishe at Aerospace Department-Cairo 

University 

� 2000 EEAA Air Quality Modeling efforts initiated Using Eta 

Model 

� Feb 2001 First Parallel Computing Experiment at FVLab 

� 2000-2003 Terrain Aerodynamics BSC Projects. Course 

offered “Aerodynamics of Environment and Urban Systems” 

� 2003- Modeling, Simulation and Visualization Lab 

Established at NARSS (NARSS First Cluster) 

� 2004-2006 NARSS MM5 modeling efforts including 

integration of Remote sensing Data. 

� 2005 NARSS initiates efforts to acquire a Terra-Scale HPC 

� 2006 NSF-AST Workshop on Predictive Methodologies for 

Global Weather & Related Disasters, 13-15 March 2006 

� 2006-2008 FVLab Extension to WRF and other Application 

Areas. 

� 2008 NSF-AST Workshop on Supercomputing in Climate and 

RS, 13-16 May 2008 

� 2008 NARSS First Terra-Scale HPC delivered and Installed. 

Applications will include weather simulation using remotely 

sensed data. 

� 2010 FVL First Windows Based Cluster Installed and tested 

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� Aerodynamic modeling of Weather and Climate related issues 

� Boundary layer corrections for urban cities and local land use 

� Assimilation of remotely sensed satellite data to provide physically consistent 

estimates of the meteorological conditions. 

� Modeling relevant physical process related to weather modeling 

� Meteorological assessment of air pollution 

� Extreme air pollution events 

� Atmospheric dispersion and transport of gases and particles 

� Modeling long term local meteorological climate changes 

� Due to aggressive land use/land cover change 

� Due to formation of artificial water bodies 

� Investigation of Wind and Solar Energy Potentials in Egypt 

� Wind Farm Site Operation Planning and Performance Assessment. 

� Study Effects of Dusty Weather on Wind Mill Performance 

� Site Selection and proper Wind Mill Sizing Related Studies 





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12 B.Sc. Students 

Sherif Sadek & M. A. Albeltagy 

B. Sc. Aerospace Engineering, Cairo University, 

Mohamad Abd Alkader, Ahmad Abd Almoaty & Hamada Sultan 

M.Sc. Aerospace Engineering, Cairo University, NARSS 

Hamdi Kandil 

Ph. D., Mechanical Engineering, Alexandria University/ GUC 

Basman El Hadidi 

PhD, Aerospace Engineering, Cairo University 

Atef O. Sherif 

PhD,, Aerospace Engineering, Cairo University 





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� The Egyptian Meteorological Authority, EMA, Ministry of Aviation, 

� The National Authority of Remote Sensing and Space Sciences, NARSS, and The 

National Research Center, NRC, State Ministry of Scientific Research Affairs, 

� The Egyptian Environmental Affairs Agency, EEAA, State Ministry of Environmental 

Affairs, 





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� The Agricultural Research Center- Climate Research Unit, and the Desert Research 

Center, DRC, Ministry of Agriculture, 

� The Water Resources Research Center, WRC, Weather and Climate research Unit, 

Ministry of Irrigation and Water Resources, 

� New and Renewable Energy Authority, NREA, Ministry of Electricity and Energy. 

� Universities, Ministry of Higher Education 

� Flow Visualization laboratory, FVLab, Aerospace department, Cairo University 

� Space Science and Technology Research and Studies Center, Cairo University 

� Center of Environmental Studies, Cairo university 

� Institute of Environmental Studies, Ain Shams University 

� Institute of Postgraduate Studies, Alexandria University 

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� Hurghada 5.2 MW wind farm. of 42 turbines of different technologies (2 blades, 3 blades, 

tubular & rigid towers) has been operational since 1993 as part of the national grid. 


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� Zafarana 305 MW wind farm. Egypt move on from limited experimental projects to larger scale 

grid connected wind farms. Overall, 305 MW installed in stages: 63 MW in 2001; 77 MW in 

2003/2004; 85 MW in 2006; 80 MW in 2007. Presently, a further 240 MW extension of the 

wind farm is under implementation. The electricity production about 636 GWh at an average 

capacity factor of 40.6%. 

� Gulf of El-Zayt on the Gulf of Suez coast Recently, an area of 656 km2 has been earmarked to 

host a 3,000 MW wind farm. Studies are being conducted to assess the site potential to host 

large scale grid connected wind farms: 200 MW in cooperation with Germany, 220 MW in 

cooperation with Japan and 400 MW as a private sector project. 

� NREA‟s short term plan 

� Currently the recent input is O( 3% ) of the electric demand from renewable energy resources, 

mainly wind and solar, 


Year 2007/2008 2008/2009 2009/2010 2010/2011 

Added wind 

power 

(MW) 

80 120 200 220 

Total (MW) 310 430 630 850 

NREA long-term plan 

In April 2007 the long term plan for wind energy has been announced by the supreme council of energy, It aims at 

increasing the e share of wind energy to reach 20% of the total electric energy demand in by year 2020 (12650 MW) 

So, within few years, Egypt will be considered among leading countries in the world in terms of wind installed capacity. 

The plan also protects the environment along with the GHG emissions abatement through CDM/CER’s green 

certificates. Exporting clean energy generate from renewable to Europe via regional interconnection link. 

A Considerable Investment. 



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� The climate system is global: Observations, theory, and models 

are all needed in climate research. 

� Comprehensive climate models are based on physical laws and 

allow for numerical simulations. 

� The climate system is characterized by a broad range of spatial 

scales and timescales. Consequently, GCMs can effectively 

address large-scale climate features such as the general 

circulation of the atmosphere and the ocean, and subcontinental 

patterns, (e.g., temperature and precipitation). 

� Their formal resolution (grid scale) is at best around 100–200 

km.* 

� Their real resolution is more like 6–8 grid distances **, i.e., of 

the order of 1000 km. This falls short of many key regional and 

local climate aspects, e.g. intensive precipitation. 

� Very high global model resolution would of course give rise to 

simulation of regional and local aspects ***. GCMs of this kind 

are, however, still not feasible due to their high computational 

cost. 

� Other methods are therefore needed, which is the backdrop to 

downscaling. 


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* Meehl GA, Stocker TF, Collins WD, Friedlingstein P, Gaye AT, et al. Global climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, 

et al. eds. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the IPCC. 

Cambridgeand New York: Cambridge University Press; 2007. 

** Grotch SL, MacCracken MC. The use of general circulation models to predict regional climatic change J Climate 1991, 4:286–303. 

*** Mizuta R, Oouchi K, Yoshimura H, Noda A, Katayama K, et al. 20-km-mesh global climate simulations using JMA-GSM model—mean climate states. J 

Meteorol Soc Japan 2006, 84:165–185. 



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Cairo Egypt, 13-16 May 2008

� Global climate models (GCMs) are a fundamental research tool for 

the understanding of climate. 

� Regional climate models (RCMs) are a complementary research 

method, allowing more detailed process studies and simulation of 

regional and even local conditions. 

� They provide key input to climate impact studies as well as to 

adaptation planning, dealing with possible damages and 

opportunities related 

� to climate variability and change. 

� The primary assumption in regional modeling is that data on the 

climate large-scale information is used to force („drive‟) an RCM over 

a limited area. Such a regional domain, as compared to a global one, 

allows for high resolution without a prohibitive increase in 

computational cost. 

� Driving data are supplied to the regional model as lateral (and often 

also sea surface) boundary conditions. The basic set of boundary 

conditions contains temperature, moisture, and circulation (winds), 

as well as sea surface temperature and sea ice. An accurate 

treatment of boundary conditions is a central issue in regional 

modeling. 

� RCMs are vehicles for both research and applications. 





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NASA Research Strategy: Prediction Goals 





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Improved weather prediction tools will help enhance day to day operations of wind related activities. Improved 

Climate predictions will help enhance medium and long term planning and economic/policy/strategic related studies 

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� A Desire to use numerical meteorological models to asses air 

pollution, temperature inversion phenomenon, transport of 

pollutants/dust (sand storms), micro-climate change due to natural 

causes like formation of lakes, desertification, etc…, man made causes: 

different land use categories and for assessment and utilization of the 

local and regional Wind and Solar energy potentials. 

� A Desire to utilize and integrate the available remotely sensed 

observations to enhanced computational model outputs with 

improvement of land surface modeling and accuracy and assimilation of 

meteorological satellite data. 

� Recent numerical experiments suggests that severe deforestation around 

the Mediterranean in the last 2000 years was a major factor in current 

dry conditions and this has been attributed to change in albedo, and 

increased evapo-transpiration. 

� Statistical trends from observations (over past 50 years) in the Eastern 

Mediterranean point to increased summer temperatures, decreased 

winter temperatures and reduced annual precipitation. However, recent 

observations suggest that atmospheric sensitivity to land use change 

occurs locally may be due to intensive irrigation and changed albedo. 





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� Global Model Results may not provide information locally, 

specially with the limited number of observation source in the 

area. 

� Meso-scale meteorology studies atmospheric phenomena with 

typical spatial scales between 10 and 1000 km. Examples of mesoscale 

phenomena include gap winds, down slope windstorms, land-sea 

breezes, etc … 

� Most weather phenomena that impacts human activity occur on 

the meso-scale 

Scale Length Area Locale 

Micro 1 m - 1 km 1 m² - 1 km² local 

Meso 1 km - 100 km 1 km² - 100 km² regional 

Macro 

(Synoptic) 


100 km - 10 000 km 100 km² - 10 000 km² continental 

Mega > 10 000 km >10 000 km² global 




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� The Developed “Weather Model for Egypt” 

was first based on the 5 th generation 

NCAR/Penn state meso-scale model (MM5) 

and later upgraded to use The Weather 

Research and Forecast Model, WRF. 

� Both MM% and WRF are open source 

models, Continuously being improved by 

contributions from users worldwide 

� The two models allows to simulate and 

predict meso-scale and regional scale 

atmospheric circulations. 





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Initial version of the Model was first established in 2000 at FVLab-CU in cooperation with EEAA, extended to use satellite data at 

NARSS in 2002-2006 and Further Enhanced with pre and post processing and WRF at FVLab-CU 2006 to present 





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Surface data are 

based on NOAA 

satellite data 

obtained via 

HRPT receiving 

stations. 




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Satellite data is continuously received 

at NARSS using HRPT receiving 

station. 

Four receiving stations are available in 

Egypt at NARSS, EMA, DRC and 

ARC 

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� Several sets of 

simulations were 

performed; using 

FDDA0: as a reference 

case, FDDA1: Grid 

FDDA from FNL., 

FDDA2: Grid FDDA 

from ATOVS, FDDA3: 

Grid FDDA from FNL + 

ATOVS. 

� Comparison of 

simulations results 

with surface 

observations at nine 

monitoring locations and 

soundings at five 

monitoring locations. 

� Validation results in 

FDDA1 is more efficient 

for research where FNL 

datasets are available 


Vertical temperature profile 

for the different FDDA 

Techniques: at Helwan 

Station 

Ground temperature inversion, 

GTI, and Particulate matter 

Measurements, PM10 over Greater 

Cairo 

FDDA1 was better correlated and more efficient for 

research where FNL datasets are available 




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Subsidence Temperature Inversion, SDI, over 

Cairo vs satellite based Aerosol Optical Depth 

AOD 

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Monthly average wind speed at 50m elevation 2006 





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WRF were used for 

the different domain 

on a Unix based 

Cluster. 

Physics 81km 27km 9km 3km 1km 

Microphysics WSM 1 WSM 1 WSM 1 WSM 1 WSM 1 

Longwave Radiation RRTM 2 RRTM 2 RRTM 2 RRTM 2 RRTM 2 

Shortwave Radiation Dudhia scheme 3 Dudhia scheme 3 Dudhia scheme 3 Dudhia scheme 3 Dudhia scheme 3 

Surface Layer MM5 similarity 4 MM5 similarity 4 MM5 similarity 4 MM5 similarity 4 MM5 similarity 4 

Land Surface NOAH 5 NOAH 5 NOAH 5 NOAH 5 NOAH 5 

Planetary Boundary layer YSU 6 YSU 6 YSU 6 YSU 6 YSU 6 

Cumulus Parameterization Kain-Fritsch 7 Kain-Fritsch 7 No no no 




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WRF – Simulated Observations Difference % 

Month K (m/s) c K (m/s) c K (m/s) c 




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June 2007 5.51 2.40 5.25 2.64 -4.95 9.09 

July 2007 4.71 2.28 5.2 2.79 9.42 18.28 

August 2007 4.97 2.41 4.94 2.70 -0.61 10.74 

September 2007 5.11 2.57 5.07 2.87 -0.79 10.45 

October 2007 4.74 2.50 4.54 2.86 -4.41 12.59 

November 2007 4.95 3.01 4.85 2.66 -2.06 -13.16 

December 2007 4.78 3.05 4.85 2.66 1.44 -14.66 

January 2008 4.95 2.82 5.4 2.62 8.33 -7.63 

February 2008 5.38 3.08 5.22 2.68 -3.07 -14.93 

March 2008 5.51 3.02 5.41 2.93 -1.85 -3.07 

April 2008 5.57 2.71 5.42 2.93 -2.77 7.51 

May 2008 5.55 2.5 5.04 2.94 -10.12 14.97 

Yearly 5.168 2.62 5.11 2.74 -1.14 4.38 

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Mean Hourly Power Output (W/m 2 ) 

Monthly Power Output (KWh/m 2 ) 

500 

400 

300 

200 

100 

0 

01/08 02/08 03/08 04/08 05/08 06/07 07/07 08/07 09/07 10/07 11/07 12/07 

350 

300 

250 

200 

150 

100 

50 


Month 

H=20 m 

H=50 m 

H=80 m 

H=100 m 

H=200 m 

0 

01/08 02/08 03/08 04/08 05/08 06/07 07/07 08/07 09/07 10/07 11/07 12/07 

Month 

H=20 m 

H=50 m 

H=80 m 

H=100 m 

H=200 m 

Yearly Power Output (MWh/m 2 ) 

2 

1.5 

1 

0.5 

0 

20 50 80 100 200 

Elevation 




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Wind Roses and Frequency Distribution 




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Wind Speed-Direction Histories 

24 hours Two Days Simulation at Two Locations 




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Day 1 

Operation not an option 


Day 2 

Operation probable 

Day 3 

Operation probable 

3 days average 

Operations probable every day 




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Power Density (W/m^2) 

1600 

1400 

1200 

1000 

800 

600 

400 

200 

0 

Power density Variation with elevation 

Elevation 2m 

Elevation 10m 

Elevation 50m 

Elevation 100m 

Elevation 200m 


13:00 

15:00 

17:00 

19:00 

21:00 

23:00 

1:00 

3:00 

5:00 

7:00 

9:00 

11:00 

13:00 

Hour 

15:00 

17:00 

19:00 

21:00 

23:00 

1:00 

3:00 

5:00 

7:00 

Note that high power density is not resolved at grid spacing 

Coarser than 3km 

at Loc-01 A Sample 

Daily Average Power Density for Day-1 at Loc-01 

Elevation/Grid spacing 27km 9km 3km 1km 

10m 298.80 247.01 227.85 255.74 

50m 620.62 439.16 382.64 423.23 

100m 756.76 514.39 471.87 474.69 

Grid spacing 1km 




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Power density at 50m elevation > power density at 100m elevation 

Wind mile tower is 100m height 

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Power Density Factor 

1.20000 

1.00000 

0.80000 

0.60000 

0.40000 

0.20000 

0.00000 

0 5 10 15 20 25 30 


Grid Spacing (km) 

10m Elevation 

50m Elevation 

100m Elevation 

200m Elevation 




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The locations of 

WMO stations 

used for the 

evaluation 

The near-surface temperature difference between ―Ref‖ 

and ―DA MQ‖ simulations in two different situations 

Badr, H. S., El Hadidi, B. M., Sherif, A. O., Evaluation of Data Assimilation on Numerical Weather Prediction for Egypt, accepted IEEE 

International Geosciences and Remote Sensing Symposium (IGARSS),, USA, 2010 

Abdel-Kader, M.M., B.M. El-Hadidi, and A.O. Sherif, “Seasonal Evaluation of Temperature Inversion over Cairo”, Proceeding of the IEEE 

International Geosciences and Remote Sensing Symposium (IGARSS), Boston, USA, July 6-11, 2008. 

Badr, H.S., B.M. El-Hadidi, and A.O. Sherif, “FDDA Enhancement of the Meso-scale Meteorological Modeling System for Egypt”, Proceeding 

of the 10th Cairo International Conference on Energy and Environment, Luxor, Egypt, March 13-15, 2007. 




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Sample results for the principal set: ―Ref‖ simulations vs. ―DA 

MQ‖ simulations scatter plots and near surface temperature 

at Cairo Airport Station 

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� RM resolution marks their core potential. Higher resolution improves the 

representation of landscape features such as mountain ranges, and lakes, 

as well as other surface features. 

� These give rise to local or regional circulation and precipitation features, 

modify temperature, winds, and so on. 

� Similar types of features include bathymetric detail, straits, etc. Higher 

resolution is furthermore beneficial for the simulation of synoptic and 

meso-scale systems including fronts, precipitation, and other extremes. 

� Another important output is the input that can be provided for impact 

studies 

� RMs adds useful information to GCM results, or sparse empirical data. 

The value of this information, however needs to be assessed,. 

� The mere appearance of more detail can be noted to provide incentives 

for stakeholders to consider Regional NWP models, when focus is on 

local-to-regional areas or extremes on, mountains, precipitation, winds 

along the coasts. 





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� Lateral boundary conditions of Regional Models do not pose a 

„well-posed‟ Problem. 

� This signifies that a unique solution does not exist, i.e., it is not 

possible to specify exactly the right conditions. 

� Even if other constraints were fulfilled, the driving GCM model 

and the regional models have different resolutions and may also 

differ in their process descriptions. 

� Furthermore, GCM data for boundary conditions is typically 

available at 6 h or so intervals. The time resolution in Regional 

Models ranges from a few minutes to around half an hour. 

� Even though one interpolates in time between two successive 

boundary condition data sets to match the time resolution in the 

regional model, this gives rise to yet another inexactness in 

providing boundary conditions. 

Staniforth A. Regional modeling: a theoretical discussion. Meteorol. Atmos Phys 1997, 63. 

McDonald A. Lateral boundary conditions for operational regional forecast models: A review. HIRLAM Technical Report No. 

32, HIRLAM Project, Norrko¨ping, Sweden; 1997 

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� The quality of Regional Model simulations depends on the quality 

of the regional models themselves. Equally important is the quality 

of the driving data and the boundary conditions. 

� GCMs have skill and suffer from systematic biases. In GCMs,a 

systematic error in some climate aspect might be due to a non-local 

process, which of course complicates model improvements. 

� Regional Model evaluation is often done with so-called perfect 

boundary condition Simulations* (also called hindcasts). In these 

experiments, boundary conditions are derived from global 

meteorological analyses or re-analyses ** that are compilations of 

observed, rather than simulated, conditions. This enables evaluation 

without, or at least with considerably reduced, systematic biases in 

their large-scale forcing. 

� Evaluation furthermore becomes feasible in a „time-series sense‟ 

against observations, rather than only in terms of climate statistics as 

is the case for studies made in „climate mode‟. This is important in 

particular when evaluating how well variability and extremes can be 

modeled. 


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* Christensen JH, Machenhauer B, Jones RG, Schar, C, Ruti PM, et al. Validation of present-day regional climate simulations over Europe: LAM simulations with 

observed boundary conditions. Clim Dyn 1997, 13:489–506. 

** Uppala SM, Kallberg PW, Simmons AJ, Andrae U, Bechtold VD, et al. The ERA-40 re-analysis. Quart J R Met Soc 2005, 131:2961–3012. 

Kalnay E, KanamitsuM, Kistler R, CollinsW, Deaven D, et al. The NCEP/NCAR 40-year reanalysis project.Bull Am Meteor Soc 1996, 77:437–471. 

Onogi K, Tsutsui J, KoideH, SakamotoM, Kobayashi S, et al. The JRA-25 reanalysis. J Meteor Soc Japan 2007, 85:369–432. 



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Cairo Egypt, 13-16 May 2008





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� Availability of suitable observational data limits model evaluation. It is much 

more attractive to evaluate a model in terms of physical processes such as 

energy and water budgets and fluxes as well as state variables (such as 

temperature). Observational data on the former is, unfortunately, quite 

limited. 

� Finally, even though RMs are run at relatively high resolution, they still fall 

short of the scale and nature of such point data as is collected on 

meteorological stations, ocean buoys, and such. 

� This is a complication in particular for the evaluation of many kinds of 

extremes, as data generated with RCMs (gridded data) are more homogenous 

in space compared to observations (station data). For example, in the former, 

extremes are typically attenuated compared to point values observed at 

stations. * 

� Model evaluation on the process level (e.g., fluxes) or by means of 

integrative metrics (e.g., river run-off) rather than in terms of state variables 

(e.g., temperature) is an avenue that deserves more exploration.** 

� Another important limitation is the relatively high demand of computational 

resources which can put a limit on the number, resolution, or length of RCM 

runs. 

* Haylock MR, Hofstra N, Klein Tank AMG, Klok EJ, Jones PD, et al. A European daily high-resolution gridded dataset of surface temperature and precipitation.J 

Geophys Res 2008, 113:D20119. Doi:10.1029/2008JD10201. 

** Lind P, Kjellstro¨m E. Water budget in the Baltic Sea drainage basin: valuation of simulated fluxes in a regional climate model. Boreal Env Res 2009, 14:56–67. 

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� Data assimilation in meteorological weather prediction and forecast 

models improves accuracy of surface and aloft variables and are 

essential to predict site wind conditions for both operational and 

planning tasks of Wind Farms. Comparison between MM5 and WRF 

predictions and the possible effects on operation is needed. 

� Prediction of extreme pollution events has been validated and should 

prove to be useful for studies related to degradation of performance of 

Wind units. 

� Land cover change significantly impacts local meteorological 

conditions 

� Along the lake shore, diurnal variations decreased by 2 o C with significant 

“sea-breeze” around artificial lakes. Velocity is up to 5 m/s. 

� Relative humidity increase by 90% along the lake shores. 

� Urban encroachment in Delta increases average daily temperature by 0.28 degrees 

� Intensive irrigation in new developed lands may results in significant temperature 

reduction in the cultivated areas 

� Potential for Wind/Solar Energy Site Select, Operational Planning is 

Promising 

� A joint Research Project addressing main ideas presented could be 

beneficial to both sides 





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� “I did not build on cultivated Lands” 

Egypt lands are approximately 86% base and Sedimentary rocks, and 4-5% cultivated 

lands. If europeans can afford to think of transporting energy over 1000‟s Kms, 

Egyptians should seriously consider transporting energy over 100‟s kms. 

� “ and I did not contaminate the waters of the river Nile” 

Use of artificially created water pools for cooling purposes. Underground water and 

even the Nile water may be used to create the required pools. 

� There is a need to continuously revise the current assessments of both Wind and Solar 

energy potentials in the light of Climate changes and the prevailing weather and climate 

patterns. Local contributions to such assessments are highly recommended. 

� There is a need and strong desire to involve the local expertise in the R & D efforts 

needed for Assessments, Site Selections, Design, Development, Testing and Operations 

of both wind and solar energy power plants and their integration into the National 

Energy Network. 

� Problems related to the effects of the local weather, cloud cover, dust storms, humidity, 

thermal inversions,.. On the efficiency and the effectiveness of operations of wind and 

solar power plants need to be further stressed and studied. 

� There is a need for a national capacity building to raise the awareness level among the 

media, the legislative body, the scientific community and the community at large. 

� There is a need for a national capacity building to train the professionals from the media, 

the legislative bodies, the top and the middle management, the professionals ia all 

aspects related to renewable energy. 

� There is a strong need to integrate renewable energy related information into educational 

curricula. 

� A joint Egyptian-US effort to prepare proposals for R&D projects to satisfy the above 

needs is solicited





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Atef O. Sherif - CIMAP

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