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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.

MICTM: Mikroskaliges Chemie, Transportmodell

General information

Model name and version

short nameMICTM
full nameMikroskaliges Chemie, Transportmodell
revision
dateDezember 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 - Forschungszentrum Jülich, Abt. Sicherheit und Strahlenschutz, Germany - Division of Environmental Health and Risk Management, School of Geography, Earth and Enivonmental Sciences, University of Birmingham, UK

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 detailsFull model code for research purposes, model code with reduced features (see METRAS PC) public domain

Minimum computer resources required

typelarge frame computer (e.g. NEC), workstation, PC (linux)
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, 13, No.5,387-394.
webpage
additional informationparallisation with openMP

Model properties

Model type

2D
3D
meteorology
chemistry & transport

Model scale

microscale
mesoscale
macroscale
short term
long term

Meteorological variables

Input data
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

Chemical substances

PrognosticDiagnosticDry depositionWet depositionInput data
SO2
NO
NO2
NOX
NH3
HNO3
O3
CH4
DMS
H2O2
VOC
C6H6
HCHO
CO
CO2
POP
PM 10
PM 2.5
PPM10
PM 0.1
PM 1
NH4
SO4
dust
sea salt
BC
POM
SOA
NO3
Other gasespassive tracers
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivity
2nd radioactivity
3rd radioactivity
remarks

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarks

Parametrizations

Chemistry & transport

photolysis rateSTAR
dry depositionResistance model
wet deposition
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)RADM2
wet phase chemistry (give details)
more information

Aerosol chemistry

passive aerosol
dry aerosol
wet aerosol
sectional approach
modal approach
other
nucleation
coagulation
condensation
aerosol mixing
aerosol ageing
primary aerosol formation
aerosol-gas phase interactions
optical properties
give details

Initialization & boundary treatment

Initialization

chemistry & transportuse values of larger scale model and start with homogeneous distribution
meteorologyDynamic initialisation: calculation of balanced fields with pre-processors based on METRAS and decreasing nudging, cold run starts with flat terrrain, restart uses METRAS results to continue

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

orographyhigh resolution maps
land usehigh resolution maps
obstacleshigh resolution maps
vegetationhigh resolution maps
meteorologyMITRAS results received on same grid
concentrationsmeasured data or coarse resultution model results
emissionsdependent on vegetation (pollen, biogenic); positions prescribed (emission cartaster)
remarks

Data assimilation

Chemistry & transport
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
details

Boundary conditions

Chemistry & transport
surfacegradient zero or constant flux or fixed values or deposition flux
topgradient zero or constant flux or fixed values
lateral inflowgradient zero or constant flux or fixed values
lateral outflowgradient zero or constant flux or fixed values

Nesting

Chemistry & transport
one way
two way
other
variables nested
nesting online
nesting offline
data exchange by array
data exchange by file
time step for data exchange
explain method
variables nestedall prognostic
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
remarksblocking approach for buildings

Numeric

Chemistry & transport

Grid

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

Time integration

explicit
split-explicit
semi-implicit
time step same as meteorology
othertime splitting for the different processes

Spatial discretisation

scalar quantitiesupstream for advection with large Courant number; centred for diffusions
additional information
other
chemistry solverMüller F., Schlünzen K.H. and Schatzmann M. (2000): Test of numerical solvers for chemical reaction mechanisms in 3D air quality models. Environmental Modelling & Software, 15, 639-646. Müller F., Schlünzen K.H., Schatzmann M. (2001): Evaluation of the chemistry transport model MECTM using TRACT-measurements - effect of different solvers for the chemical mechanism. Air pollution modeling and its application; Gryning, Schiermeier (eds.);New York, 2001; XIV, 583-590

Model resolution

Chemistry & transport

HorizontalVertical
max0.0151000
min0.0011

Domain size

Chemistry & transport

HorizontalVertical
max110000
min0.1500

Model Validation and Application

Validation & evaluation

Used validation & evaluation methods

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

Analytic solutions

Chemistry & transport

SO2
NO
NO2
NOX
NH3
HNO3
O3
VOC
C6H6
HCHO
CO
CO2
POP
other
testcase description
testcase references
used data set
reference for evaluation
remarks

Evaluated reference dataset

Chemistry & transport

SO2
NO
NO2
NOX
NH3
HNO3
O3
VOC
C6H6
HCHO
CO
CO2
POP
other
testcase description
testcase references
used data set
reference for evaluation
remarksTRACT, BERLIOZ, FLUMOB
remarks

Application examples

application examplesurban pollution, biogenic emissions, trasnport weithin the urban vcanopy layer and within forests

Participation in specific model evaluation exercises

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