Intercomparison of European

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COSMO Users Seminar
Langen, March 2008
Intercomparison of European Fog Forecast Models
M.Masbou1,2, A. Bott1, M. D. Müller3, N.
W.Nielsen4, C. Petersen4, H. Seidl5, A. Kann5, J.
Cermak6, H. Petithomme7 W. K. Adam8
1 Meteorological Institute, University of Bonn,
Germany, mmasbou_at_uni-bonn.de 2 Laboratoire de
Météorologie physique, University Blaise Pascal,
Clermont-Ferrand, France 3 Institute of
Meteorology, Climatology Remote Sensing,
University of Basel, Switzerland 4 Danish
Meteorlogical Institute, Copenhagen, Denmark 5
Central Institute for Meteorology and
Geodynamics, Vienna, Austria 6 Laboratory for
Climatology Remote Sensing, University of
Marburg, Germany 7 Meteo France, Toulouse,
France 8 Meteorological Observatory Lindenberg,
DWD, Germany
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Fog Formation
1D
3D

• Cooling
• Moistening
• Turbulent Mixing
• Reach saturation

Radiation fog
Advection fog
3D
3D
(1D)
Upslope fog
Valley fog
Precipitation fog
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Fog A visibility reduction
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COST 722 Project
Development of advanced methods for short-range
forecasts of fog, visibility and low clouds
Working Group I Initial Data

• Improved calibration and analysis of satellite
  data
• Recommendation of measurement equipments
• Exchange of knowledge and methods

Working Group II Numerical Models

• Developement of numerical for fog and low clouds
• Improved understanding of physical processes
  during fog events

Working Group III Statistical Methods

• Powerful and highly sophisticated statisitcal
  methods
• Improved expertise on statistical methods
• Basis for the preparation of training material

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Comparison Campaign on the Lindenberg Area
September December 2005
Phase 1 Statistics
Each Participant produce 4 month fog forecast and
quantify statistically his fog forecast quality
(FAR, HR, ETS)
Phase 2 Fine Comparison for chosen fog/no fog
events
Episode 1 fog formation with mid cloud
cover September, 27th 2005 01-05 UTC Episode 2
fog formation with without cloud cover October,
6th 2005 07-09 UTC October, 7th 2005 06-08
UTC Episode 3 fog formation with 8/8 cloud
cover December, 6th 2005 18-00 UTC December,
7th 2005 00-23 UTC
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Lindenberg Area
Observatory of DWD supplies

• Visibility 2m
• Cloud cover

• Radiative fluxes

(SW, LW, Latent and Sensible)

• 10m-Mast T, RH, Wind
• 100m-Mast T, RH, Wind

• Radiosounding

(00, 06, 12 and 18 UTC)

• Soil temperature
• Soil moisture

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Participants
Statistical Model MOS-ARPEGE
France H. Petithomme
MOS statistics using linear discriminant analysis
Uses model output of the hydrostatic global model
ARPEGE
Predictand visibility with different thresholds
Predictor pressure at the ground, cloud cover,
10m wind speed, RH2m, T2m
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Operational models
Austria H. Seidl and A. Kann
Model name ALADIN-AUSTRIA
Resolution 9.6 km horizontal, 45 vertical
layers
Model domain Europe
Boundary values global model ARPEGE
Dynamics Hydrostatic
Turbulence Louis scheme
Visibility Post-processing in case of
T-inversion gradient RH and T
Denmark C. Petersen and N.W. Nielsen
Model name DMI-HIRLAM
Resolution 16 km horizontal, 40 vertical layers
Model domain Europe
Boundary values ECMWF analyses and forecasts
Dynamics Hydrostatic
Turbulence prognostic TKE
Visibility MOS approach depending on ground
measurements and model forecasts
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Non-operational models
Germany M. Masbou and A. Bott
Model name LM-PAFOG (COSMO-FOG)
Resolution 2.8 km horizontal, 40 vertical
layers, ?zmin4m
Model domain 280 x 280 km limited area
Boundary values COSMO-EU
Dynamics Nonhydrostatic, fully compressible
Turbulence Louis scheme
Visibility diagnostic variable depending on
CCN, LWC, aerosol concentration at 2m
Switzerland M.D. Müller
Model name NMM-PAFOG
Resolution 1 km horizontal, 45 vertical layers
Model domain 160 x 160 km limited area
Boundary values NMM 13 km
Dynamics Nonhydrostatic, fully compressible
Turbulence prognostic TKE
Visibility complex relation of moist forecasted
parameter at 2m
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Statistical Study
METHOD
Comparison 1 pixel of Model area with visibility
2m
5 Categories lt 350m, lt 600m, lt 1000m, lt 1500m, lt
3000m
Basing on contingence table analyses
PERIOD
4 months forecast (September-December 2005)
MODELS
Initialization each day at 00 UTC
FOG CLIMATOLOGY
35 Fog events
Fog episode very rare, 4 of studied time period
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Ensemble Forecast
To analyse the basic quality of the European
models
Ensemble forecast extracted from the 4 models
Fog event probability of the ensemble
Fog event probability of the i-th model
Quantity of available forecasts
Average out disagreements between ensemble
member
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Hit Rate
What fraction of the observed fog" events were
correctly forecast?
BLACKLM-PAFOG
REDENSEMBLE
GREENHIRLAM
BLUEALADIN
MAGENTAMOS-ARPEGE
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False Alarm Rate
What fraction of the observed "no-fog" events
were incorrectly forecast as fog"?
BLACKLM-PAFOG
REDENSEMBLE
GREENHIRLAM
BLUEALADIN
MAGENTAMOS-ARPEGE
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False Alarm Ratio
What fraction of the predicted fog" events
actually did not occur (i.e., were false
alarms)?
BLACKLM-PAFOG
REDENSEMBLE
GREENHIRLAM
BLUEALADIN
MAGENTAMOS-ARPEGE
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Equitable Threat Score
How well did the forecast fog" events correspond
to the observed fog" events?
BLACKLM-PAFOG
REDENSEMBLE
GREENHIRLAM
BLUEALADIN
MAGENTAMOS-ARPEGE
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Case I Visibility 2m
Date September, 26-27 th 2005
After a rain episode bringing warm and humid air,
residual cloud parcel
Radiative fog
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Visibility 2m case I
Legend
Vis lt1000 m
gt1000 m
Vis
lt3000 m
VIS-2m-NMM-PAFOG-2709200503
Lindenberg
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LWC 2m case I
Legend
LWCgt 0.1g/kg
gt0.01 g/kg
LWC
lt0.1 g/kg
Lindenberg
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Case I Vertical profile at Lindenberg
BLACKOBSERVED
REDLM-PAFOG
GREENALADIN
BLUEHIRLAM
CYAN NMM-PAFOG
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Case I Radiative Fluxes
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Case I Close to the ground
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Case II Visibility 2m
Date December, 6-7 th 2005
Stable moist layer with a tendency to light rain,
full cloud cover
Low stratus and Fog
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Visibility 2m case II
Legend
Vis lt1000 m
gt1000 m
Vis
lt3000 m
VIS-2m-NMM-PAFOG-2709200503
Lindenberg
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LWC 2m case II
Legend
LWCgt 0.1g/kg
gt0.01 g/kg
LWC
lt0.1 g/kg
Lindenberg
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Case II Vertical profile at Lindenberg
BLACKOBSERVED
REDLM-PAFOG
GREENALADIN
BLUEHIRLAM
CYAN NMM-PAFOG
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Case II Radiative Fluxes
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Case II Close to the ground
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CONCLUSION

• 4 Models involved NO BEST MODEL
• MOS-ARPEGE statistic model
• ALADIN-AUSTRIA, DMI-HIRLAM 3D mesoscale
  models, ad hoc cloud water near the surface
• NMM-PAFOG, LM-PAFOG 3D high-resolution
  fog forecast model, complex microphysics

Statistical and fine Analysis of autumn 2005s
fog events

• 20 of the fog forecast according with
  measurements

• Initialization and Assimilation of the boundary
  layer determinant role for a successful fog
  forecast

• Visibility parameterization decisive key

• Vertical diffusion usually not designed to work
  well near the surface

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Outlooks

• Adapted turbulent scheme for high vertical
  resolution

• Long time verification of 3D fog forecast model
  considering spatial distribution of fog

• Adjusting the visibility parameterization

Thanks
COST 722
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Parameters in Fog Formation
Important Parameters in Fog Formation
Cooling of moist air by radiative flux
divergence Vertical mixing of heat and
moisture Vegetation Horizontal and vertical
wind Heat and moisture transport in
soil Advection Topographic effect
Once the fog has formed
Longwave radiative cooling at fog
top Gravitational droplet settling Fog
microphysics Shortwave radiation
(Duynkerke, P.G.,1991)
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What is FOG ?
WMO definition
Suspension of very small, usually microscopic
water droplets in the air, generally reducing the
horizontal visibility at the Earths surface to
less than 1km
Forecaster definition (Roach, W.T., 1994)
Fog occurs whenever the horizontal visibility
falls below 1km. Cloud base descending to ground
level is also experienced as fog.
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Case III Visibility 2m
Date October, 6-7 th 2005
Under influence of high pressure system, no cloud
cover
Radiative fog
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Visibility 2m case III
Legend
Vis lt1000 m
gt1000 m
Vis
lt3000 m
VIS-2m-NMM-PAFOG-2709200503
Lindenberg
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LWC 2m case III
Legend
LWCgt 0.1g/kg
gt0.01 g/kg
LWC
lt0.1 g/kg
Lindenberg
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Case III Vertical profile at Lindenberg
BLACKOBSERVED
REDLM-PAFOG
GREENALADIN
BLUEHIRLAM
CYAN NMM-PAFOG
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Case III Radiative Fluxes
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Case III Close to the ground