Diapositive 1

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EGU Assembly 2007
Vienna, April 2007
Numerical Weather Prediction and Data Assimilation
LM-PAFOG Three-Dimensional Fog Forecast Model
with Parameterized Microphysics
M.Masbou1,2, A. Bott1, M. D. Müller3 Jan Cermak4
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 Laboratory for
Climatology Remote Sensing, University of
Marburg, Germany
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Fog Formation
Cooling Increase in humidity
1D
3D
Radiation fog
Advection fog
3D
3D
(1D)
Upslope fog
Valley fog
Precipitation fog
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3D FOG Model LM PAFOG
Droplet number concentration
Liquid Water Content
LM-Dynamics
PAFOG-Microphysics
20 000 m
Boundary
Water/Ice Cloud
Precipitation
qc
Nc
2000 m
Nc
Fog/Stratus
Nc
qc
Soil Model
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PAFOG Microphysics
Supersaturation S
Assumption for droplet spectra Log-normal
0.2
0.25
0.3
CCN Concentration
0.35
D droplet diameter
Dc,0 mean value of D
sc standard deviation of size distribution
(sc0.2)
Diameter in µm
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PAFOG Microphysics
1- Activation Twomey (1954)
k and C depend on their environment (maritime,
rural, urban)
2a-Detailed Condensation/Evaporation
parameterized Köhler relation
Chaumerliac et al. (1987) and Sakakibara (1979)
2b-Time dependent relation between
supersaturation S and diameter D
3-Droplet size dependent sedimentation
Positive Definite Advection Scheme
Bott (1989)
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STANDARD-PAFOG Microphysics
LWC-Standard microphysics
LWC-PAFOG microphysics
500
0.5
g/kg
g/kg
Altitude
0.25
0
0.01
CCN-PAFOG microphysics
51.5
53.5
Latitude
500
70
1/cm3
Lindenberg Observatory 2005 September 27th 03
UTC 27 hours forecast
Altitude
40
10
0
51.5
53.5
Latitude
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Resolution of LM-PAFOG
Horizontal Resolution 100 x 100 pixels ?x,y
2.8 km
Vertical Resolution Atmosphere 40 levels
?zmin 4m
25 levels in the lowest 2 000 m
Soil - 8 levels ?zs,min 5 mm
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Statistical Study
METHOD
Comparison 1 pixel LM-PAFOG with visibility 2m
5 Categories lt 350m, lt 600m, lt 1000m, lt 1500m, lt
3000m
PERIOD
4 months forecast (September-December 2005)
LM-PAFOG
Initialization each day at 00 UTC
Forecast 48 hours
About 6000 hours forecast
FOG CLIMATOLOGY
35 Fog events
Fog episode very rare, 4 of studied time period
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Statistical Study at Lindenberg pixel
1.0
1000 m
Hit Rate
3000 m
0.8
0.6
0.4
0.2
0
0
6
30
48
12
36
42
hours
1.0
1000 m
False Alarm Rate
3000 m
0.8
0.6
0.4
0.2
0
0
6
30
48
12
36
42
hours
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Satellite Verification
October 2005, 6th Lindenberg
Lindenberg
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LM-PAFOG Satellite Verification
x103
2005 October,6th 00 UTC
10
No cloud cover
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SAT FOG Product
LM-PAFOG Fog
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No Pixels
Good Forecast
4
2
x103
0
2005 September,26th 00 UTC
48
0
hours
12
36
10
mid cloud cover
8
6
No Pixels
4
2
0
48
0
hours
12
36
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Comparison SYNOP Procedure
53.5
3000
2m Visibility Measurements
About 30 Stations
latitude
2005 December 6th 21 UTC
1000
51.5
LM-PAFOG
100
53.5
3000
latitude
1000
51.5
SYNOP
LM-PAFOG
100
12
15.5
12
15.5
longitude
longitude
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2005 December 6th-Visibility 1000 m
30
Nb stations
Fog observed
LM-PAFOG Fog
No Stations
Good Forecast
1.0
0
12
36
48
hours
0
0.5
HR
First 6 hours Forecast
NIGHT Fog Forecast
DAY Fog Forecast
0
FAR
0
1.0
0.2
0.8
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2005 December 6th-Visibility 3000 m
30
Nb stations
Fog observed
LM-PAFOG Fog
No Stations
Good Forecast
1.0
0
12
36
48
hours
0
0.5
HR
First 6 hours Forecast
NIGHT Fog Forecast
DAY Fog Forecast
0
FAR
0
1.0
0.2
0.8
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CONCLUSION
3D fog models with complex microphysics and high
resolution
Lindenberg study Low HR but also Low FAR
Satellite Comparison
- very good results in case of low cloudiness
- Interference of stratus in case of fog event
SYNOP Comparison
- Influence of visibility parameterization
- Better forecast by night than by day
Future
- Complete comparison SYNOP/LM-PAFOG on a larger
period
- Implement a better turbulence scheme for
soil/atmosphere exchange by day
Thanks
COST 722
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REFERENCES
Berry, E.X Pranger, M. P. (1974), Equation for
calculating the terminal velocities of water
drops, J. Appl. Meteor. 13, 108-113.
Bott, A. (1989), A positive definite advection
schemme obtained by nonlinear renormalization of
the advective fluxes, Monthly Weather Review 117,
1006-1015.
Bott, A. Trautmann, T. (2002), PAFOG a new
efficient forecast model of radiation fog and
low-level stratiform clouds, Atmospheric Research
64, 191-203.
Chaumerliac, N., Richard, E. Pinty, J.-P.
(1987), Sulfur scavenging in a mesoscale model
with quasi-spectral microphysic Two dimensional
results for continental and maritime clouds, J.
Geophys. Res. 92, 3114- 3126.
Sakakibara, H. (1979), A scheme for stable
numerical computation of the condensation
process with large time step, J. Meteorol. Soc.
Japan 57, 349-353.
Twomey, S. (1959), The nuclei of natural cloud
formation. Part ii The supersaturation in
natural clouds and the variation of cloud droplet
concentration, Geophys. Pura Appl. 43, 243-249.
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Boundary Condition for Nc
Height
1 000m
PAFOG TOP
PAFOG TOP
CCN Concentration
1 000m
sc
Diameter in µm
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MSG SEVIRI Satellite Products
1- Fog is a cloud
2- in water phase
3- composed of small droplets
4- low above the ground and
5- stratiform
Satellite Products
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Pc- Cloud Confidence Level
Blackbody temperature difference
Cloudy
Clear