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More information on some input arrays can be found when moving the cursor above the corresponding field in the questionnaire. Those fields are also explained in the glossary.

CLM: Climate Version of the Local Model

General information

Model name and version

short nameCLM
full name Climate Version of the Local Model
revision
date08-10-2006; Version 3.19
last change

Responsible for this information

nameGeyer
instituteGKSS Forschungszentrum
addressMax-Planck-Strasse 1
zip21502
cityGeesthacht
countryGermany
phone++49 4152 871871
fax++49 4152 8741871
e-mailbeate.geyer(belongs-to)gkss.de

Additional information on the model

Contact person for model code

same as person above
nameDr. Andreas Will
instituteBTU Cottbus
divisionsLS Umweltmeteorologie
streetBurger Chaussee 2
zip03044
cityCottbus
countryGermany
phone+49-355-69-1171
emailwill@tu-cottbus.de
fax+49-355-69-1128

Model developer and model user

developer and userGerman Weather Service (DWD) and CLM-Community http://www.clm-community.eu/

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarks

Model use at your institution

operational
for research
other use

Model code available?

is available?yes
more detailsonly for CLM-Community members and for research purposes

Minimum computer resources required

typeparallel supercomputers or LINUX cluster
time needed for rundepends on model set up
storagevery extensive

Further information

documentation'documentations' at http://clm-community.eu
model referencesSteppeler, J., Doms, G., Schättler, U., Bitzer, H.W., Gassmann, A., Damrath, U., Gregoric, G.: Meso-gamma scale forecasts using the nonhydrostatic model LM. Meteorology and Atmospheric Physics, 82 (1 - 4), 75 - 96, 2003. Böhm, U., M. Kücken, W. Ahrens, A. Block, D. Hauffe, K. Keluer, B. Rockel, and A. Will, 2006: Clm - the climate version of lm: Brief description and long-term applications. COSMO Newsletter, 6.
webpagehttp://www.clm-community.eu
additional information

Model properties

Model type

2D
3D
meteorology
chemistry & transport

Model scale

microscale
mesoscale
macroscale
short term
long term

Meteorological variables

PrognosticDiagnostic
u
v
w
ζ
pv
T
θ
θl
p
Gph
ρ
qv
qt
qlc
qf
qsc
qlr
qsh
qsg
qss
N
E
ε
K
zi
other variables i
other variables ii
other variables iii

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Meteorology

turbulence schemebased on a second-order closure at hierarchy level 2.0 (Mellor and Yamada (1974)
deep convectionTiedtke (1989) mass-flux convection scheme with equilibrium closure based on moisture convergence. Option for the Kain-Fritsch (1992) convection scheme with non-equilibrium CAPE-type closure.
surface exchangerefined surface layer scheme incl. laminar BL (roughness layer) based on TKE equation
surface temperaturefrom multi-layer prognostic soil model, heat conduction equation (Schrodin and Heise (2001) in C0SMO Tech. Rep. 2
surface humidityfrom multi-layer prognostic soil model, incl. freeze and thaw of soil moisture.
radiationdelta-two-stream radiation scheme after Ritter and Geleyn (1992) for short and longwave fluxes (employing eight spectral intervals); full cloud-radiation feedback.
unresolved orographic dragorographic drag considered in TKE scheme
radiation in vegetation
radiation between obstacles
treatment of obstacles
clouds / rainElaborate Kessler-type scheme incl. cloud water and ice, rain water and snow. Cloud water condensation and evaporation by saturation adjustment. Precipitation formation by a bulk microphysics parameterization including water vapour, cloud water, rain and snow with column equilibrium for the precipitating phases. Option for a new bulk scheme including cloud ice. Option for 3-d precipitation transport. Subgrid-scale cloudiness is interpreted by an empirical function depending on relative humidity and height. A corresponding cloud water content is also interpreted.
remarks

Initialization & boundary treatment

Initialization

chemistry & transport
meteorologydigital filter after Lynch (1997)

Input data (name sources for data, e.g. website)

orographyGTOPO30
land useGlobal ecosystems V2.0 / ECOCLIMAP
obstacles
vegetation
meteorologyInterpolated initial data from various coarse-grid driving models (ECMWF,NCEP, CLM) or from the continuous CLM data assimilation stream. Option for user-specified idealized initial fields.
concentrations
emissions
remarkssoil: FAO climatological deep soil temperature: CRU (2 metre temperature)

Data assimilation

Meteorology
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailscontinuous 4D nudging assim. after Schraff (1996), for horizontal wind, Tpot, rel. hum. on all model levels and surface pressure. Plus variational soil moisture analysis and SST analys. and snow height analysis.

Boundary conditions

Meteorology
surfaceDigital-Filter initialization of unbalanced initial states (Lynch et al., 1997) with options for adiabatic and diabatic initialization.
topOptions for rigid lid condition and Rayleigh damping layer.
lateral inflow1-way nesting by Davies-type lateral boundary formulation. Data from several coarse-grid models can be processed (GME, IFS, LM). Option for periodic boundary conditions.
lateral outflow

Nesting

Meteorology
one way
two way
other
variables nested
nesting online
nesting offline
data exchange by array
data exchange by file
time step for data exchange1 hour
explain method
variables nested
other

Solution technique

Coordinate system and projection

Horizontal

cartesian
Lambert conformal
latitude / longitude
rotated lat. / long.

Vertical

z coordinate
surface fitted grid
pressurecoordinate
sigma coordinate
remarkshybrid pressure(at top of atmos.) and sigma coordinate

Numeric

Meteorology

Grid

Arakawa A
Arakawa B
Arakawa C
Arakawa D
Arakawa E
uniform grid
nonuniform grid
Euler

Time integration

explicit
split-explicit
semi-implicit
otherSecond-order leapfrog HE-VI (horizontally explicit, vertically implicit)

Spatial discretisation

momentum equationsSecond-order finite differences
scalar quantitiesSecond-order finite differences
additional information
other

Model resolution

Meteorology

HorizontalVertical
max~50km2800m = top layer
min~7 km20m = bottom layer

Domain size

Meteorology

HorizontalVertical
max8000 km
min5000 km~22 km

Model Validation and Application

Validation & evaluation

Used validation & evaluation methods

analytic solutions
evaluated reference dataset
model intercomparison
additional validation & evaluation efforts
remarks

Application examples

application examplessee 'projects' at http://www.clm-community.eu i.e. Consortial Simulations (see http://sga.wdc-climate.de) period: 1960-2100 hor. res.: 0.165º no of pixel: 255/241

Participation in specific model evaluation exercises

AQMEII
List experiments (AQMEII)
Cost728
List experiments (COST728)
HTAP
List experiments (HTAP)
MEGAPOLI
List experiments (MEGAPOLI)