Note:
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 name  SAIMM 
full name  SYSTEMS APPLICATIONS INTERNATIONAL MESOCALE MODEL 
revision  1995 
date  OCTOBER 
last change  
Responsible for this information 
name  Ana Isabel Miranda 
institute  Universidade de Aveiro 
address  Universidade de Aveiro, Dept. Ambiente e Ordenamento 
zip  3810 
city  193 Aveiro 
country  Portugal 
phone  00351234370200 
fax  00351234429290 
email  aicm(belongsto)dao.ua.pt 
Additional information on the model 
Contact person for model code 
same as person above  
name  Ana Isabel Miranda 
institute  Universidade de Aveiro 
divisions  Universidade de Aveiro, Dept. Ambiente e Ordenamento 
street  
zip  3810 
city  193 Aveiro 
country  Portugal 
phone  00351234370200 
email  aicm(belongsto)dao.ua.pt 
fax  00351234429290 
Model developer and model user 
developer and user  MODEL 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 
type  unix workstation 
time needed for run  1 hour 
storage  100 Mb 
Further information 
documentation  USER'S GUIDE TO THE SYSTEMS APPLICATIONS INTERNATIONAL MESOSCALE MODEL version 3.1 (1995). Systems Applications International, SYSAPP95/070. 
model references  T. 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. AndreaniAksoyoglu, M. Tinguely, André S. H. Prévôt: Unexpected vertical profiles over complex terrain due to the incomplete formulation of transport processes in the SAIMM/UAMV air quality model. 747762.

webpage   
additional information   


Model properties 
Model type 
2D  
3D  
meteorology  
chemistry & transport  
Model scale 
microscale  
mesoscale  
macroscale  
short term  
long term  
Meteorological variables 
 Prognostic  Diagnostic 

u   

v   

w   

ζ   

pv   

T   

θ   

θ_{l}   

p   

Gph   

ρ   

q_{v}   

q_{t}   

q_{lc}   

q_{f}   

q_{sc}   

q_{lr}   

q_{sh}   

q_{sg}   

q_{ss}   

N   

E   

ε   

K   

z_{i}   

other variables i   

other variables ii   

other variables iii   


Approximations 
Boussinesq  
anelastic  
hydrostatic  
flat earth  
remarks  
Parametrizations 
Meteorology 
turbulence scheme  first order closure sheme 
deep convection   
surface exchange  localK scheme (first order) 
surface temperature  predicted by assuming a net heatflux 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 1720, Montreal Quebec, Canada. 
surface humidity  
radiation  Longwave 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, 50:505517. 
unresolved orographic drag  the model use coordinates terrain following 
radiation in vegetation  
radiation between obstacles  
treatment of obstacles  
clouds / rain   
remarks  


Initialization & boundary treatment 
Initialization 
chemistry & transport  
meteorology  The 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) 
orography  http://snig.igeo.pt/ 
land use  corine land cover 
obstacles  
vegetation  
meteorology  RADIOSOUNDS
web site: http://weather.uwyo.edu/upperair/sounding.html 
concentrations  
emissions  
remarks  
Data assimilation 
 Meteorology 

nudging technique  

adjoint model  

3DVAR  

4DVAR  

OI  

details  the model employs the Newtonian relaxation or 'nudging' technique in which one or more of the timedependent 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 fourdimensional data assimilation in a limitedarea mesoscale model. PartI:experiments with synopticalscale data. Mon. Wea. Rev., 118: 12501277. 


Boundary conditions 
 Meteorology 

surface  noslip 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 NewtonRaphson iterative technique. 

top  the upper boundary is an isentropic surface with no horizontal velocity perturbation from the basic state. 

lateral inflow  zerogradient 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 method  there 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  

remarks  the model tranform the cartesian coordinates to terrainfollowing coordinates 
Numeric 
Meteorology 
Grid 
Arakawa A  
Arakawa B  
Arakawa C  
Arakawa D  
Arakawa E  
uniform grid  
nonuniform grid  
Euler  
Time integration 
explicit  
splitexplicit  
semiimplicit  
other  
Spatial discretisation 
momentum equations  
scalar quantities  
additional information  

other  

Model resolution 
Meteorology 
 Horizontal  Vertical 

max  5  1000 

min  2  10 



Domain size 
Meteorology 
 Horizontal  Vertical 

max  200  200 

min  100  100 




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  
q_{v}  
q_{lc}  
q_{sc}  
q_{lr}  
z_{i}  
other  
testcase description  
testcase references  
used data set  
reference for evaluation  
remarks  

Evaluated reference dataset 
Meteorology 
u  
v  
w  
T  
q_{v}  
q_{lc}  
q_{sc}  
q_{lr}  
z_{i}  
other  
testcase description  
testcase references  
used data set  
reference for evaluation  
remarks  

Model intercomparison 
Meteorology 
u  
v  
w  
T  
q_{v}  
q_{lc}  
q_{sc}  
q_{lr}  
z_{i}  
other  
testcase description  
testcase references  
used data set  
reference for evaluation  
remarks  


remarks  
Application examples 
application examples  BORREGO, 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. 487499.
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)  
