Inter-comparison of numerical models of fog and low clouds ... - LCRS

Inter-comparison of numerical models of fog and low clouds ... - LCRS

Inter-comparison of numerical models of fog

and low clouds : a proposal

1) Introduction

Météo-France / CNRM – T. Bergot

Inter-comparison : Why?

Paris-CDG fog field experiment

2) The methodology of the inter-comparison

3) Phase 1 : cases study





4) Phase 2 : forecast quality over a long period

To be discussed precisely at the end of phase 1

inter-comparison : why?

1) The goal : link with COST722 objectives

NOT to create a competition between the different participants!

Learn about the value of different existing physical


Improve our understanding of the sensitivity to different physical


Hope : lead to some improvement in parameterisations

Investigate the potential (limitation?) of the different types of

forecast methods

2) The data

Fog field experiment at Paris CDG

Performed by Météo-France/CNRM

Available following a convention between Météo-France/CNRM

and the participants

Paris CDG fog field experiment

Ground measurements :

T / W inside the soil (between

ground and –50cm)

short- and long-wave radiations

Since December 2002

Airport terminal 1:

T / H%

Radiation fluxes

Meteorological tower of 30m :

T / Hu%

The data

12 visibility

measurements /6min

4 ceiling

measurements / 6min

2 winter seasons

Every 30min

frequency of dense fogs (visi < 600m) / hours

The distribution is characteristic to events dominated by

radiation processes

The data

Dense fog :


1) Phase 1 : cases study

inter-comparison : the methodology

Goal : exhibit model deficiencies or weaknesses due to imperfect

representation of physical processes

Focus on specific cases well defined and observed : radiation fog

and low clouds (formation, evolution and dissipation)

Lead to improvements in the physical parameterisations


2) Phase 2 : evaluation of the forecast quality

Goal : investigate the potential and limitation of forecast

performed by numerical models over a long period in order to get

representative results in statistical sense

Objective :

Phase 1 : methodology

Exhibit deficiencies due to imperfect representation of physical

processes involved in the formation and evolution of fog and low


Tools :

The study of simulated boundary layer at local scale using highquality

observational data + effect on fog/low clouds simulations

Focus on vertical processes

1D model

Same initial conditions

No meso-scale flow (no advection + no vertical


Phase 1 : numerical models used

France : 1D COBEL-ISBA :



Spain : 1D HIRLAM

Germany : 1D PAFOG

Switzerland : 1D COBEL-OSU

Denmark : ?

U.K. : ?

First level : 0.5m

20 levels below 200m

Physical parameterizations

High resolution radiation scheme (232 spectral intervals)

Turbulence scheme : turbulent kinetic energy (TKE)

Fine mesh vertical grid

(Bergot 1993 ; Bergot and

Guedalia 1994 ;Guedalia

and Bergot, 1994)

Phase 1 : input data

All participants will used the same initial conditions given by

Météo-France/CNRM issued from the Paris CDG fog field

experiment (send on CD to participants)

Initial vertical atmospheric profiles

T, q, ql, U, V, other?

Between 0 and 5500m ? Step?

Initial soil profiles

T, Wl, Wi, other?

Soil/vegetation characteristic

Profile between ground and 2m in depth?

Spatial heterogeneities : every 3h?

Geostrophic wind

Cloud cover (low, medium, high)

Assimilation at local scale

1) Initialisation of dry atmosphere

Methodology : variational assimilation 1D-Var

Data : local observations, operational 3D NWP forecast

2) Initialisation of fog / low clouds

Define the depth of the cloudy area (minimization of errors on

the radiation fluxes divergence)

Correction of the atmospheric profiles below and inside the

cloudy area (dry / moist mixed area)

3) Initialisation of soil parameters

Soil temperature and moisture have a strong influence on the

surface cooling (energy budget at the surface : spin-up problem!)

Offline version of the ISBA model, driven by observed

atmospheric forcing

Phase 1 : output data

Frequency : 30min? – duration : up to 12h?

Microphysics : visibility at 2m, ceiling, height of cloud/fog

Vertical profiles : T, Q, Ql – levels?

Radiation : short- and long-wave at 2m and 45m, other?

Turbulent exchanges : TKE? Turbulent fluxes? Mixing length?

Soil – vegetation – atmosphere exchanges : H, LE, other?

Send on CD to other participants

Phase 1 : evaluation

Comparison for a given validity (e.g. 06UTC) and a given lead

time (e.g. +6h)

Comparison between the output of participants + comparison

between observations

More efficient if performed centrally, but all participants should be

associated in the evaluation processes

Evaluation of microphysical parameters : formation, evolution and

dissipation (fog, low cloud and LVP conditions -visibility < 600m

and/or ceiling < 200ft)

Evaluation of boundary layer processes : profiles? evolution of

specific parameters?

Evaluation of radiation processes : short-wave and long-wave?

profile? evolution?

Turbulent exchanges : TKE? turbulent fluxes? profiles? evolutions?

Soil – vegetation – atmosphere exchanges : H, LE? evolution?

Phase 1 : schedule

Participants : before October 2004

Description of the numerical model : before October 2004

Input data (convention between participants and Météo-

France/CNRM + distribution on CD) : before the end of 2004

Collection of output on CD : before April 2005

First analysis of results : mid 2005

Inter-comparison : Phase 2

Goal : learn about the quality of the different numerical models (1D,

3D, …) used for fog and low clouds forecasting in a statistical sense.

To be discussed precisely at the end of phase 1

Input : observations from CDG fog field experiment

Output : visibility, ceiling, LVP, T-Hu at 2m, wind at 10m, shortwave

and long-wave radiation at ground

Evaluation : Statistical verification – ROC curves, scatter-plots,

statistical scores (bias, RMS, other)

should be completed in collaboration with WG3 - task 1

“Determine how to evaluate the potential of existing methods”

!! END !!

Mesoscale terms :



•Geostrophic wind



Exchanges between soil,

vegetation and atmosphere


Radiative processes (IR+vis)

Turbulent processes (stable


Microphysical processes




Initialization / forcing

(every 3h)


requirements / forecast

ISBA offline


Mesoscale NWP

model (3D)


Local fog forecasting

formation formation

visibility visibility / vertical thickness

clearance clearance

Temperature at 1m (CI Cobel-Isba)

1D-Var : T / q surface boundary layer

Guess = previous COBEL-ISBA forecast (3h)

Altitude « observations » = 3D NWP Aladin forecast

Surface observations = local data (30m tower, 2m obs.)

Temperature at 1m

(initial conditions)

Temperature at 1m (observation)

2002-2003 Winter

Bias = 0.0°C

Std. Dev. = 0.3°C

Low clouds from Aladin


Initialisation of low clouds

cloud = mixed layer (moist variables)

Assimilation of radiation fluxes at 2m and 45m

IR fluxes when low

clouds are detected

low clouds from local assimilation


3D operational NWP models are not able to give realistic

forecasts (occurrence) of low clouds!

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