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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.

MIMO: Microscale Model

General information

Model name and version

short nameMIMO
full nameMicroscale Model
revisionVersion 91
dateJuly 2003
last change

Responsible for this information

nameNicolas Moussiopoulos
instituteAristotle University Thessaloniki, Laboratory of H
addressP.O.Box 483, Aristotle University Thessaloniki
zipGR-54124
cityThessaloniki
countryGreece
phone+30 2310 996011
fax+30 2310 996012
e-mailmoussio(belongs-to)vergina.eng.auth.gr

Additional information on the model

Contact person for model code

same as person above
nameNicolas Moussiopoulos
instituteAristotle University Thessaloniki, Laboratory of H
divisionsP.O.Box 483, Aristotle University Thessaloniki
streetP.O.Box 483
zipGR-54124
cityThessaloniki
countryGreece
phone+30 2310 996011
emailmoussio(belongs-to)vergina.eng.auth.gr
fax+30 2310 996012

Model developer and model user

developer and userInstitut fuer Technische Thermodynamik Fakultaet fuer Maschinenbau Universitaet Karlsruhe Kaiserstr.12 D-76128 Karlsruhe Germany Laboratory of Heat Transfer and Environmental Engineering (LHTEE), Aristotle University Thessaloniki P.O. Box 483, Aristotle University Thessaloniki, GR-54124, Thessaloniki, Greece

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?no
more detailsThe model is not a public domain programme. Information on the conditions for obtaining MIMO can be provided by the contact person.

Minimum computer resources required

typeSufficient experience on a Pentium II PC and on POWERPC; extensive use on various workstation platforms (mainly IBM/RISC, but also Hewlett Packard and DEC Alpha); enough experience on IBM SP2, Siemens VP400EX and several CRAYs.
time needed for runFor a typical grid 200x60x4 without dispersion of pollutants, only wind field, 8 hours in real time. (On an IBM RS/6000 3BT, specfp95~ 7.5).
storageFor the same typical case: 20 Mbytes RAM. Disk space: 50-120 Mbytes needed for the output files

Further information

documentationJournal publications available, but no manual available.
model referencesEhrhard, J., Ernst, G., Goetting, J., Khatib, A., Kunz, R., Moussiopoulos and Winkler, C. (1999) The microscale model MIMO: Development and Assessment. Goetting, J., Winkler, C., Rau, M., Moussiopoulos and Ernst, G. (1997) Dispersion of a passive pollutant in the vicinity of a U-shaped building, Int. J. Environment and Pollution, Vol. 8, Nos. 3-6, pp. 718-726. Kunz, R., Khatib, I. and Moussiopoulos, N. (1998), Coupling of Mesoscale and Microscale models-An approach to simulate scale interaction.
webpagehttp://aix.meng.auth.gr/lhtee/projects/
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 iair motion near complex building structures
other variables iiconcentrations
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 gases
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivity
2nd radioactivity
3rd radioactivity
remarks

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarksNon-hydrostatic

Parametrizations

Meteorology

turbulence schemeOptionally one- and two-equation schemes linear and non-linear turbulence models
deep convection
surface exchange
surface temperature
surface humidity
radiation
unresolved orographic drag
radiation in vegetation
radiation between obstacles
treatment of obstaclesBuildings and other microscale obstacles resolved in a non-equidistant grid spacing which is allowed in all directions.
clouds / rain
remarks

Chemistry & transport

photolysis rate
dry deposition
wet deposition
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
otherFast chemistry
gas phase chemistry (give details)NO-NO2-O3 cycle
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 & transport
meteorologyInitialisation is performed using either prognostic or diagnostic methods. In the former case the model is coupled with the mesoscale model MEMO. In the latter case the initial wind field is calculated from measured data or by the power law. Temperature is initialised diagnostically on the basis of measured profiles or by a constant gradient. Initialisation of the pressure follows the thermal stratification according to the hydrostatic equation.

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

orography
land use
obstaclesBuilding inventory provided by a grid generation programme.
vegetation
meteorologyOne dimensional profile of wind velocity, turbulent kinetic energy and dissipation rate, or MEMO-results.
concentrations
emissionsThe emissions are provided in kg/h/cell area for each grid location.
remarks

Data assimilation

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

Boundary conditions

MeteorologyChemistry & transport
surfaceLaw of the wall
topDirichlet boundary conditions are imposed for all main quantities except for pressure, which is of Neumann type
lateral inflowAt lateral inflow Dirichlet boundary conditions are imposed for all main quantities except for pressure, which is of Neumann type.
lateral outflowHomogeneous Neumann boundary conditions

Nesting

MeteorologyChemistry & 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 methodCoupled to MEMO model using extended radiation conditions or relaxation scheme
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
remarksCell height: 1 - 100 m (varying with height), total height: up to about 1000 m.

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
otherTime step: 0.1 - 1 second

Spatial discretisation

momentum equationsThe conservation equations for mass, momentum are solved.
scalar quantitiesThe conservation equations for scalar quantities as potential temperature, turbulent kinetic energy and specific humidity are solved.
additional informationFast elliptic solver, which is based on fast Fourier analysis in both horizontal directions and Gaussian elimination in the vertical direction.
other

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
other

Spatial discretisation

scalar quantities
additional information
other
chemistry solver

Model resolution

Meteorology

HorizontalVertical
max100
min0,000020,02

Chemistry & transport

HorizontalVertical
max
min

Domain size

Meteorology

HorizontalVertical
max11000
min0,11

Chemistry & transport

HorizontalVertical
max
min

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 examplesGoetting, J., Winkler, Ch., Rau, M., Moussiopoulos, N. and Ernst, G. (1997) Dispersion of a passive pollutant in the vicinity of a U-shaped building, Int. J. Env. Poll., 8, No. 3-6, 718-726. Louka P. and N. Moussiopoulos (2003), Optimisation of CFD modelling methods for traffic pollution in streets within TRAPOS research network, Proceedings of the 4th International Exhibition and Conference on Environmental Technology (HELECO 03), Athens, Greece, 30 January-2 February, Vol. 1, 69-77.

Participation in specific model evaluation exercises

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