Surface processes in the COSMO model – Part I : modeling components
Modeling component
|
Current status
|
Under development
|
Suitable references
|
Surface energy balance
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Surface temperature is area weighted average of temperature of snow covered and snow free surface fraction
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Tile approach with four separate energy budgets (sea/lake/towns/nature)
Provision for mosaic/patch
|
Ament and Simmer (2006)
|
Coupling with the atmosphere
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Explicit coupling
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|
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Soil transfers
|
7-layer soil model
Layer-depth between 1 cm and 14.58 m
Solution of the heat conduction equation
|
|
Heise and Schrodin (2002)
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Frozen soils
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Temperature and soil type dependent computation of fractional freezing/melting of total soil water content in 6 active soil layers
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|
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Vegetation
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One-layer – Evapotranspiration after Dickinson (1984) – interception reservoir
|
|
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Snow model
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One layer – prognostic variables : snow temperature, snow water equivalent, snow density, snow albedo
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Multi-layer – liquid water in snow pack as an additional prognostic variable
|
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Lake model
|
Prescribed surface temperature (analysis)
|
Lake model (Flake)
|
Mironov et al. (2008)
|
Sea-ice
|
Prescribed surface temperature (analysis)
|
Sea-ice model
|
Mironov and Ritter (2003)
|
Ocean model
|
Prescribed surface temperature (analysis)
Charnock formulation for roughness length
|
|
|
Urban areas
|
Modified surface roughness, leaf area index, plant coverage
|
Multi-layer urban canopy parametrization.
|
Martilli et al.(2002)
|
Chemistry module
|
None
|
COSMO-ART : Aerosols and dust emission
|
Vogel et al. (2008)
|
Surface boundary layer
|
Application of the turbulence scheme at the lower model boundary and iterative interpolation.
Roughness length for scalars implicitly considered by calculation of an additional transport resistance throughout the turbulent and laminar roughness layer
|
|
Raschendorfer (1999)
Mironov and Raschendorfer (2001)
|
Surface processes in the COSMO model – Part II : physiography
Component
|
Current status
|
Under development
|
Suitable references
|
Orography
|
GLOBE database
NOAA/NGDC
resolution 30''
|
|
|
Soil types
|
FAO Digital Soil Map of the World
resolution 10 km
|
Harmonized World Soil database
|
|
Land Cover
and
Land sea mask
|
GLC2000;
Lookup tables between land use categories and model parameters
|
|
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Seasonal variability of plant fraction
|
|
NDVI Climatology,
NASA/GSFC
based on
Monthly mean data from SEAWiFS, resolution 2.5 '
|
|
Lake properties
|
|
specific lake database (location + depth) from DWD for FLAKE
|
http://lakemodel.net
|
Aerosol Optical Thickness
|
|
NASA/GISS (Global Aerosol Climatology Project)
|
http://gacp.giss.nasa.gov/data_sets/transport/
|
|
|
|
|
lower boundary condition for soil temperature
|
T2m Climatology
From CRU of University of East Anglia
|
|
|
List of model external parameter fields
|
|
External parameter
|
Short Name
|
Unit
|
Used raw dataset
|
|
|
|
|
geometrical height of earths surface
|
HSURF
|
m
|
GLOBE
|
Geopotential of earths surface
|
FIS
|
m2s-2
|
GLOBE
|
land cover
|
FR_LAND
|
1
|
GLC2000 (GLOBE, DSMW)
|
standard deviation of subgrid scale orographic height
|
SSO_STDH
|
m
|
GLOBE
|
anisotropy of topography
|
SSO_GAMMA
|
1
|
GLOBE
|
angle between principal axis of orography and global E
|
SSO_THETA
|
1
|
GLOBE
|
mean slope of subgrid scale orography
|
SSO_SIGMA
|
1
|
GLOBE
|
surface roughness
|
Z0
|
m
|
GLC2000, GLOBE
|
soil texture
|
SOILTYP
|
1
|
DSMW
|
long wave surface emissivity
|
EMIS_RAD
|
1
|
GLC2000
|
Plant root depth
|
ROOTDP
|
m
|
GLC2000
|
ground fraction covered by plants (vegetation period)
|
PLCOV_MX
|
1
|
GLC2000
|
ground fraction covered by evergreen forest
|
FOR_E
|
1
|
GLC2000
|
ground fraction covered by deciduous forest
|
FOR_D
|
1
|
GLC2000
|
leaf area index (vegetation period)
|
LAI_MX
|
1
|
GLC2000
|
Minimum plant stomata resistance
|
RS_MIN
|
s m-1
|
GLC2000
|
(monthly mean) normalized differential vegetation index
|
NDVI
|
1
|
SEAWIFS
|
Annual maximum of normalized differential vegetation index
|
NDVI_MAX
|
1
|
SEAWIFS
|
ratio of actual montly value/annual maximum normalized differential vegetation index
|
NDVI_RATIO
|
1
|
SEAWIFS
|
(monthly) optical thickness from black carbon aerosol
|
AER_BC
|
1
|
GACP
|
(monthly) optical thickness from dust aerosol
|
AER_DUST
|
1
|
GACP
|
(monthly) optical thickness from organic aerosol
|
AER_ORG
|
1
|
GACP
|
(monthly) optical thickness from SO4 aerosol
|
AER_SO4
|
1
|
GACP
|
(monthly) optical thickness from sea salt aerosol
|
AER_SS
|
1
|
GACP
|
Near surface temperature (climatological mean)
|
T_2M_CL
|
K
|
CRU
|
Lake Depth
|
DEPTH_LK
|
m
|
DWD
|
Lake Fraction
|
FR_LAKE
|
1
|
DWD
|
Surface processes in the COSMO model – Part III : assimilation and analysis
Model parameters
|
Current status
|
Under development
|
Suitable references
|
Soil water content
|
2-dimensional (vertical and temporal) variational technique
using 2-m temperature analyses at 12 and 15 UTC
Analysed variables: Soil moisture of the top 5 soil layers (0-81cm) at 00 UTC
|
|
Schraff and Hess (2002)
Schraff and Hess (2003)
|
Sea surface temperature
|
Correction method
Background field from GME SST analysis using NCEP 0.5° x 0.5° SST analysis that includes satellite data.
Observations from Synop-Ship and buoy, sea ice cover analysis from BSH for the Baltic Sea .
|
|
Wergen and Buchhold (2002)
Schraff and Hess (2003).
|
Sea-ice extent
|
Sea ice cover analysis from BSH (German Institute for shipping and hydrology) for the Baltic Sea , resolution lon/lat: 0.167 x 0.1 degrees., NCEP analysis in other areas
|
|
Wergen and Buchhold (2002),
Schraff and Hess (2003).
|
Sea ice temperature
|
Interpolated from monthly ECMWF climatology
|
Implementation of bulk thermodynamic sea ice model presently applied operational in GME.
|
|
Sea-ice concentration
|
None
|
|
|
Snow depth
|
Correction method
Used Data: Background values from COSMO model, Snow depth observations from synop stations, present and past synop weather, precipitation amount, 2-m temperature analysis (plus model prediction).
Monthly snow depth climatology of ECMWF for permanently glacial covered areas.
|
Major revision of snow model within COSMO project COLOBOC at Meteo Suisse. Modifications in calculation of rho_snow, t_snow, additional use of snow observations in the alpine region.
|
Wergen and Buchhold (2002),
Schraff and Hess (2003).
|
Lake
|
Closest point from SST analysis, adapted to model terrain height. Climatological lake temperature for Bodensee and Lake Geneva.
|
|
|
Vegetation
|
None
|
|
|
References:
Ament, F. and Simmer, C., 2006: Improved Representation of Land-Surface Heterogeneity in a Non-Hydrostatic Numerical Weather Prediction Model, Boundary-Layer Meteorology, 121, 153-174
Heise E., Schrodin R. Aspects of snow and soil modelling in the operational short range weather prediction models of the German weather service // Computational technologies. 2002. V. 7. Special issue. P. 121-140
Martilli, A., Clappier, A., Rotach, M. W.: 2002, ’An urban surfaces exchange
parameterisation for mesoscale models’, Bound.-Layer Meteor., 104, 261-304.
Mironov D. and Matthias Raschendorfer (2001): Evaluation of Empirical Parameters of the New LM Surface-Layer Parameterization. Scheme. COSMO Technical Report, No. 1, Deutscher Wetterdienst, Offenbach am Main, Germany
Mironov, D., and B. Ritter, 2003: A first version of the ice model for the global NWP system GME of the German Weather Service. Research Activities in Atmospheric and Oceanic Modelling, J. Cote, Ed., Report No. 33, April 2003, WMO/TD, 4.13-4.14.
Mironov, D. , 2008: Parameterization of lakes in numerical weather prediction. Description of a lake model. COSMO Technical Report, No. 11, Deutscher Wetterdienst, Offenbach am Main, Germany.
Raschendorfer, M. (1999): The new turbulence parameterization of LM, Quarterly Report of the. Operational NWP-Models of the DWD, No 19, 3-12, May 1999
Schraff, C. and R. Hess (2002): Datenassimilation für das LM, Promet Jahrgang 27, Heft 3/4, p 156-163.
Schraff, C. and R. Hess (2003): A Description of the Nonhydrostatic Regional Model LM Part III : Data Assimilation. Available from DWD.
Vogel, H., Pauling, A., Vogel, B. (2008), Numerical simulation of birch pollen dispersion with an operational weather forecast system, Int J Biometeorol. 2008 Nov;52(8):805-814, doi:10.1007/s00484-008-0174-3.
Wergen, W. and M. Buchhold (2002): Datenassimilation für das Globalmodell GME, Promet Jahrgang 27, Heft 3/4, p 149-155.
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