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GESIMA: Geesthacht Simulation Model of the Atmosphere

General information

Model name and version

short nameGESIMA
full nameGeesthacht Simulation Model of the Atmosphere
revision
date2005-03
last change

Responsible for this information

nameHartmut Kapitza
instituteHelmholtz-Zentrum Geesthacht
addressMax-Planck-Str. 1
zip21502
cityGeesthacht
countryGermany
phone+49 (0)4152 871846
fax
e-mailhartmut.kapitza(belongs-to)hzg.de

Additional information on the model

Contact person for model code

same as person above
name
institute
divisions
street
zip
city
country
phone
email
fax

Model developer and model user

developer and userHelmholtz-Zentrum Geesthacht (Geesthacht) MPIfM (Hamburg) GMD-FIRST (Berlin) FU Berlin University of Kiel University of Leipzig TU Chemnitz Institute for Tropical Meteorology (Puna, India) University of Nairobi (Kenia) Institute of Low Temperature Science (Hokkaido, Japan) Puertos del Estades (Madrid, Spanien)

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarksAdding customized parameterization modules requires advanced knowledge. Running the model on different data/scenarios requires basic knowledge.

Model use at your institution

operational
for research
other use

Model code available?

is available?yes
more detailsLicense required (free of charge for scientific purposes)

Minimum computer resources required

typeLinux PC
time needed for run1 h CPU for 24 h simulation
storage100 MB

Further information

documentationavailable from the author on request
model referencesKAPITZA, H., and D.P. EPPEL, 1992: The Non-Hydrostatic Mesoscale Model GESIMA. Part I: Dynamical Equations and Tests. Beitr. Phys. Atmosph. 65, 129-146 EPPEL, D.P., H. KAPITZA, M. CLAUSSEN, D. JACOB, W. KOCH, L. LEVKOV, H.-T. MENGELKAMP, and N. WERRMANN, 1995: The Non-Hydrostatic Mesoscale Model GESIMA. Part II: Parameterizations and Applications. Beitr. Phys. Atmosph. 68, 15-41
webpage
additional informationa) an additional chemistry module is available (see BAUER, S.E., 2000: Photochemical Smog in Berlin-Brandenburg: An Investigation with the Atmosphere-Chemistry Model GESIMA. MPI Examensarbeit Nr. 81, 108 p.) b) an MPI-parallelized version is available (see ASHWORTH, M., F. FOELKEL, V. GUELZOW, K. KLEESE, D.P. EPPEL, H. KAPITZA and S. UNGER, 1997: Parallelization of the GESIMA Mesoscale Atmospheric Model. Parallel Computing 23, 2201-2213)

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 ipassive constituents concentrations
other variables iitracers
other variables iii

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Meteorology

turbulence schemechoice of a) constant b) algebraic c) Mellor-Yamada Level 2.5
deep convectionimplemented
surface exchangeenergy balance with stability functions from Louis
surface temperaturefrom energy balance
surface humidityforce-restore method
radiationoptions: a) SW: simple transmission. LW: 2-stream-method with broad-band approximation (Bakan) b) detailed line-model (Schmetz)
unresolved orographic dragnot considered
radiation in vegetation
radiation between obstacles
treatment of obstacles
clouds / rainKessler-type scheme with extensions. Options: a) bulk parameterization b) quasi-spectral parameterization c) quasi-spectral with log-normal distributions
remarks

Initialization & boundary treatment

Initialization

chemistry & transport
meteorologystart from 3D synoptic fields without diastrophy (allow 2-3 hours for adjustment)

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

orographyany source
land useany source
obstacles
vegetation
meteorologyseveral options: a) 1D profiles b) analytical 3D fields c) external synoptic fields
concentrations
emissions
remarks

Data assimilation

Meteorology
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailsa) nudging of u,v,T,q,p(top) with adjustable form of coefficients b) the adjoint version is experimental (see KAPITZA, H., 1991: Numerical Experiments with the Adjoint of a Nonhydrostatic Mesoscale Model. Monthly Wea. Rev. 119, 2993-3011)

Boundary conditions

Meteorology
surfaceno-slip, energy-budget, land-use parameters
toprigid lid with sponge layer
lateral inflowspecified values from synoptic background fields
lateral outflowOrlanski-type radiating b.c.

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 exchangeadjustable
explain methoduses same logic as for data assimilation with nudging method
variables nestedu,v,T,q,p(top)
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
remarks

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
otherclouds with smaller time steps

Spatial discretisation

momentum equationsMcCormack scheme (predictor/corrector) with alternating upstream/downstream discretization
scalar quantitiesSmolarkiewicz-Scheme
additional informationvertical diffusion terms semi-implicit; implicit pressure gradient terms by solving a Helmholtz-Equation with preconditioned conjugate gradient method
other

Model resolution

Meteorology

HorizontalVertical
max101000
min0.11

Domain size

Meteorology

HorizontalVertical
max50020000
min51000

Model Validation and Application

Validation & evaluation

Used validation & evaluation methods

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

Analytic solutions

Meteorology

u
v
w
T
qv
qlc
qsc
qlr
zi
other
testcase descriptionmountain lee waves (hydrostatic and non-hydrostatic)
testcase referencesKAPITZA, EPPEL, 1992: The Non-Hydrostatic Model GESIMA. Part I: Dynamical Equations and Tests. Beitr. Phys. Atmosph. 65, 129-146
used data setanalytical solutions
reference for evaluation
remarks

Evaluated reference dataset

Meteorology

u
v
w
T
qv
qlc
qsc
qlr
zi
other
testcase description
testcase references
used data set
reference for evaluation
remarks
remarks

Application examples

application examplesDEVANTIER, R., and A. RAABE, 1996: Application of a Quasispectral Cloud Parameterization Scheme to a Mesoscale Snowfall Event over the Baltic Sea. Contributions to Atmospheric Physics 69, 375-384 MOELDERS, N., and A. RAABE, 1996: Numerical Investigations on the Influence of Subgrid-Scale Surface Heterogeneity on Evapotranspiration and Cloud Processes. J. Appl. Meteor. 35, 782-795

Participation in specific model evaluation exercises

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