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METRAS: Mesoskaliges Chemie, Transport- und Strömungsmodell

General information

Model name and version

short nameMETRAS
full nameMesoskaliges Chemie, Transport- und Strömungsmodell
revision6.x
date11-02-2005
last change

Responsible for this information

nameHeinke Schlünzen
instituteKlimaCampus, Meteorological Institute, University
addressBundesstr. 55
zip20146
cityHamburg
countryGermany
phone+49-40-42838 5082
fax+49-40-42838 5452
e-mailheinke.schluenzen(belongs-to)zmaw.de

Additional information on the model

Contact person for model code

same as person above
nameHeinke Schlünzen
instituteKlimaCampus, Meteorological Institute, University
divisionsBundesstr. 55
streetBundesstr. 55
zip20146
cityHamburg
countryGermany
phone+49-40-42838 5082
emailheinke.schluenzen(belongs-to)zmaw.de
fax+49-40-42838 5452

Model developer and model user

developer and user- Meteorologisches Inst., Univ. Hamburg - Alfred Wegener-Inst. f. Polar und Meeresforschung, Bremerhaven - Forschungszentrum Jülich, Abt. Sicherheit und Strahlenschutz, Germany - Institut für Physik und Meteorologie, Universität Hohenheim, Stuttgart, Germany - Division of Environmental Health and Risk Management, School of Geography, Earth and Enivonmental Sciences, University of Birmingham, UK - Ocean University of Qingdao, PR China

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarksexperience with numerical models is essential to change the program. To run the model basic knowledge is sufficient. To receive reliable model answers and avoid \'garbige in garbige out\' simulations an intermidiate experience with numerical models is necessary.

Model use at your institution

operational
for research
other useteaching

Model code available?

is available?yes
more detailsFull model code for research purposes, model code with reduced features (see METRAS PC) public domain

Minimum computer resources required

typePC, problem dependent
time needed for runProblem dependent
storageA few tens MWords for full model

Further information

documentationSchlünzen K.H., Bigalke K., Lüpkes C., Niemeier U. and von Salzen K. (1996): Concept and realization of the mesoscale transport- and fluid-model \'METRAS\', Meteorologisches Institut, Univerität Hamburg, METRAS Techn. Rep. 5, 156 Schlünzen K.H., Bigalke K., Lüpkes C., Niemeier U. and von Salzen K. (1996): Hint for using the mesoscale model \'METRAS\', Meteorologisches Institut, Univerität Hamburg, METRAS Techn. Rep. 6, 52
model referencesTrukenmüller A., Grawe D. and Schlünzen K. H. (2004): A model system for the assessment of ambient air quality conforming to EC directives. Meteorol. Zeitschrift,Vol.13,No.5,387-394. Schlünzen K.H. (1997): On the validation of high-resolution atmospheric mesoscale models , J. Wind Engineering and Industrial Aerodynamics, 67 & 68 , 479-492. Schlünzen, K.H. (1990): Numerical studies on the inland penetration of sea breeze fronts at a coastline with tidally flooded mudflats, Beitr. Phys. Atmosph., 63, 243-256.
webpagehttp://www.mi.uni-hamburg.de/metras
additional informationparallisation with openMP in test phase

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 iconcentrations
other variables iiparticles
other variables iiipassive tracers

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Meteorology

turbulence schemeSeveral schemes (TKE-l, counter gradient scheme; mixing length approach..)
deep convectionresolved with km grid; vertical averaging for devergence of radiative fluxes
surface exchangeConstant flux layer; surface energy /humidity budget over land, constant temperature/humidity with Charnock (1955) for roughness over water, subgrid scale land use with flux aggregation
surface temperatureEnergy budget (force restore method)
surface humidityhumidity budget (force restore method)
radiationShort and long wave radiative fluxes: 2 way scheme; vertical averaging for devergence of radiative fluxes
unresolved orographic dragnot considered
radiation in vegetation
radiation between obstacles
treatment of obstacles
clouds / rainKessler-type
remarks

Initialization & boundary treatment

Initialization

chemistry & transport
meteorologyDynamic initialisation: calculation of balanced fields with 1D pre-processors based on METRAS, cold run starts with flat terrrain and constant large nudging, which decreases during the initialisation phase, restart uses METRAS results to continue

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

orographyGLOBEFILE (1 km resolution); higher resolution if available
land useSmiatek data (based on CORINE data set and satellite images)
obstacles
vegetation
meteorologyGerman Weather Service or other larger scale model results or METRAS results or measurement analyses with pre-processor consistent with METRAS model physics
concentrationsmeasured data
emissionsdependent on vegetation (pollen); positions prescribed
remarks

Data assimilation

Meteorology
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
details

Boundary conditions

Meteorology
surfaceSeveral options (constant values, surface energy budgets, constant fluxes)
toprigid lid, damping layers; towards forcing data
lateral inflowTowards forcing data (relaxation area) or modified radiation boundary condition
lateral outflowTowards forcing data (relaxation area) or modified radiation boundary condition

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 exchangeAccording to the resolution, in typical applications once per hour
explain methodDavies scheme
variables nestedall prognostic
othernonuniform horizontal grid

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
othervertical dffusion semi-implicit, all aother explicit fisrt and second order

Spatial discretisation

momentum equationscentered differences or (W)ENO
scalar quantitiesupstream or (W)ENO
additional informationcentered differences; values interpolated to other grid points by linear or higher order interpolation
other

Model resolution

Meteorology

HorizontalVertical
max161000
min0,0320

Domain size

Meteorology

HorizontalVertical
max250014000
min107000

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
otherpotential temperature
testcase descriptionLong solution (flow over mountain) with different stratification and flow speed
testcase referencesLong, R. R. 1953 Some aspects of the flow of stratified fluids. I: A theoretical investigation. Tellus, 5, 42–58. Lilly D.K. und Klemp J.B. (1979): The effects of terrain shape on nonlinear hydrostatic mountain waves. J. Fluid Mech., 95, 241 - 261. Schumann U., Hauf T., Höller H., Schmidt H. und Volkert H. (1987): A mesoscale model for the simulation of turbulence, clouds and flow over mountains: formulation and validation examples. Beitr. Phys. Atmosph., 60, 413 - 446.
used data setanalytic solution
reference for evaluationSchlünzen K.H. (1996): Validierung hochauflösender Regionalmodelle, Ber. aus dem Zentrum f. Meeres- und Klimaforschung, Meteorologisches Institut, Universität Hamburg, A23, 184: http://www.bis.zmaw.de/fileadmin/Bib/Volltexte/ZMK-A23.pdf Schlünzen K.H. (1997): On the validation of high-resolution atmospheric mesoscale models , J. Wind Engineering and Industrial Aerodynamics, 67 & 68 , 479-492. Schröder G., Schlünzen K.H., Schimmel F. (2006): Use of (weighted) essentially non-oscillating advection shemes in the mesoscale model. Quarterly Journal Roy. Met. Soc. 132, 1509-1526; DOI: 10.1256/j.04.191.
remarkstestcase suitable for detecting prinipial model errors
remarks

Application examples

application examplespolar cold air outbreaks, orographic influences, sea breeze, polar cyclones, land use impacts Lüpkes C. and Schlünzen K.H. (1996): Modelling the Arctic convective boundary-layer with different turbulence parameterizations, Boundary-Layer Meteorol., 79, 107-130. Niemeier U. and Schlünzen K.H. (1993): Modelling steep terrain influences on flow patterns at the Isle of Helgoland, Beitr. Phys. Atmosph., 66, 45-62. Sheng L., Schlünzen K.H. and Wu Z. (2000): Three dimensional numerical simulation of the mesoscale wind structure over Shadong peninsula. Acta Meteorl. Sinica, 1, 97 - 107. Dierer S., Schlünzen K.H., Birnbaum G., Brümmer B. & Müller G. (2005): Atmosphere – sea ice interactions during a cyclone passage investigated by using model simulations and measurements. Accepted for publication, Monthly Weather Review. Schlünzen K.H. and Katzfey J.J. (2003) : Relevance of sub-grid-scale land-use effects for mesoscale models. Tellus, 55A, 232-246.

Participation in specific model evaluation exercises

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