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

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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

Input

Output

Evaluation

Schedule

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

parameterisations

Improve our understanding of the sensitivity to different physical

parameterisations

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 :

visibility


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

themselves?

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

clouds

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

velocity)


Phase 1 : numerical models used

France : 1D COBEL-ISBA :

COBEL : http://www.rap.ucar.edu.staff/tardif/COBEL

ISBA : http://www.cnrm.meteo.fr/mc2/index.htm

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)

http://www.rap.ucar.edu/staff/tardif/COBEL


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 :

ALADIN

•Advections

•Geostrophic wind

clouds

ISBA

Exchanges between soil,

vegetation and atmosphere

COBEL

Radiative processes (IR+vis)

Turbulent processes (stable

cases)

Microphysical processes

(condensation-evaporation,

sedimentation)


Observations

Initialization / forcing

(every 3h)

Adjustment

requirements / forecast

ISBA offline

guess

Mesoscale NWP

model (3D)

COBEL/ISBA

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

bias=-41.9W/m2

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

bias=-1.0W/m2

3D operational NWP models are not able to give realistic

forecasts (occurrence) of low clouds!

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