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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.

SAIMM: SYSTEMS APPLICATIONS INTERNATIONAL MESOCALE MODEL

General information

Model name and version

short nameSAIMM
full nameSYSTEMS APPLICATIONS INTERNATIONAL MESOCALE MODEL
revision1995
dateOCTOBER
last change

Responsible for this information

nameAna Isabel Miranda
instituteUniversidade de Aveiro
addressUniversidade de Aveiro, Dept. Ambiente e Ordenamento
zip3810
city193 Aveiro
countryPortugal
phone00351234370200
fax00351234429290
e-mailaicm(belongs-to)dao.ua.pt

Additional information on the model

Contact person for model code

same as person above
nameAna Isabel Miranda
instituteUniversidade de Aveiro
divisionsUniversidade de Aveiro, Dept. Ambiente e Ordenamento
street
zip3810
city193 Aveiro
countryPortugal
phone00351234370200
emailaicm(belongs-to)dao.ua.pt
fax00351234429290

Model developer and model user

developer and userMODEL DEVELOPER: SYSTEMS AAPLICATIONS INTERNATIONAL, lUCAS VALLEY ROAD, SAN RAFAEL, CALIFORNIA MODEL USER: GEMAC

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 details

Minimum computer resources required

typeunix workstation
time needed for run1 hour
storage100 Mb

Further information

documentationUSER'S GUIDE TO THE SYSTEMS APPLICATIONS INTERNATIONAL MESOSCALE MODEL- version 3.1 (1995). Systems Applications International, SYSAPP-95/070.
model referencesT. Matsuno and H. Kida (2001). Regional Warming Related with Land Use Change during Past 135 Years in Japan. Future of Modeling Global Environmental Change: Toward Integrated Modeling,Eds., pp. 433–440. J. Keller, N. Ritter, S. Andreani-Aksoyoglu, M. Tinguely, André S. H. Prévôt: Unexpected vertical profiles over complex terrain due to the incomplete formulation of transport processes in the SAIMM/UAM-V air quality model. 747-762.
webpage--
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 schemefirst order closure sheme
deep convection-
surface exchangelocal-K scheme (first order)
surface temperaturepredicted by assuming a net heat-flux divergence across a thin, isothermal slab of soil reference: Tremback, C. and R.C. Kessler. 1985. A surface temperature and moisture parameterization for use in mesoscale numerical models. Proceedings of the seventh conference on numerical weather prediction, June 17-20, Montreal Quebec, Canada.
surface humidity
radiationLongwave radiation emitted by the surface is calculated assuming that the surface emits as a blackbody. Above the surface, the longwave radiative transfer equation is simplified by the Sasamori approximation: Sasamori, T., 1972. A linear harmonic analysis of atmospheric motion with radiative dissipation. J. Met. Soc. Japan, 50:505-517.
unresolved orographic dragthe model use coordinates terrain following
radiation in vegetation
radiation between obstacles
treatment of obstacles
clouds / rain--
remarks

Initialization & boundary treatment

Initialization

chemistry & transport
meteorologyThe SAIMM can be initialized using either static or dynamic initialization. Using the static initialization technique, the model is initialized with objectively analyzed fields of wind and potential temperature. Dynamic initialization makes use of the model's inherent adjustments mechanism to bring the wind and temperature fields into balance prior to the initial simulation time.

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

orographyhttp://snig.igeo.pt/
land usecorine land cover
obstacles
vegetation
meteorologyRADIOSOUNDS web site: http://weather.uwyo.edu/upperair/sounding.html
concentrations
emissions
remarks

Data assimilation

Meteorology
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailsthe model employs the Newtonian relaxation or 'nudging' technique in which one or more of the time-dependent variables are relaxed or 'nudged' toward observed values during the course of the simulation. Reference: Sauffer, D.R. and N.L. Seaman. 1990. Use of four-dimensional data assimilation in a limited-area mesoscale model. PartI:experiments with synoptical-scale data. Mon. Wea. Rev., 118: 1250-1277.

Boundary conditions

Meteorology
surfaceno-slip condition (u=v=0) is specified for the horizontal velocities. For the vertical velocity, the lower boundary condition is always w*=0. The temperature at the ground surface is predicted from an energy balance through a Newton-Raphson iterative technique.
topthe upper boundary is an isentropic surface with no horizontal velocity perturbation from the basic state.
lateral inflowzero-gradient lateral boundary conditions are imposed on all prognostic variables
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 exchange
explain methodthere is no nesting capabilities
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
remarksthe model tranform the cartesian coordinates to terrain-following coordinates

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
other

Spatial discretisation

momentum equations
scalar quantities
additional information
other

Model resolution

Meteorology

HorizontalVertical
max51000
min210

Domain size

Meteorology

HorizontalVertical
max200200
min100100

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 description
testcase references
used data set
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

Model intercomparison

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 examplesBORREGO, C.; TCHEPEL, O.; MONTEIRO, A.; MIRANDA, A.I. and BARROS, N. - Influence of traffic emissions estimation variability on urban air quality modelling. Water, Air and Soil Pollution: Kluwer Academic Publishers, Focus 2 (2002), p. 487-499. MONTEIRO, A. - Poluição atmosferica na regiao de Aveiro: modelação de mesoscala e sua validação. Master thesis presented at the University of Aveiro, 2003.

Participation in specific model evaluation exercises

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