Welcome guest. Please login.

List, classification & detail view

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.

SILAM: System for Integrated modeLling of Atmospheric coMposition

General information

Model name and version

short nameSILAM
full nameSystem for Integrated modeLling of Atmospheric coMposition
revisionversion 5.0
date28.1.2011
last change

Responsible for this information

nameSofiev Mikhail
instituteFinnish Meteorological INstitute
addressErik Palmenin Aukio 1, 00561 Helsinki FInland
zip00561
cityHelsinki
countryFinland
phone+358-9-1929-5433
fax+358-9-19295403
e-mailmikhail.sofiev(belongs-to)fmi.fi

Additional information on the model

Contact person for model code

same as person above
nameSofiev Mikhail
instituteFinnish Meteorological INstitute
divisionsErik Palmenin Aukio 1, 00561 Helsinki FInland
street
zip00561
cityHelsinki
countryFinland
phone+358-9-1929-5433
emailmikhail.sofiev(belongs-to)fmi.fi
fax+358-9-19295403

Model developer and model user

developer and userSILAM development team: M.Sofiev (leader), M.Ilvonen, P.Siljamo, J.Soares, J.Vira, M.Prank, J-P.Jalkanen SILAM exploitation team includes the whole development team plus: I.Valkama, FMI production department, Finnish Radiation Protection Authority, FMI and University of Helsinki students, University of Tartu (M.Kaasik et al), (Estonia), University of Vilnius, etc.

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarksLargely depends on task. Via graphical interface, the model can be run with minor prior knowledge, while sophisticated setups might require extensive understanding of both theory and implementation of the specific processes

Model use at your institution

operational
for research
other use

Model code available?

is available?yes
more detailsFree for scientific use, agreement with FMI is needed for other purposes

Minimum computer resources required

typeworkstation/server under UNIX/Windows/Linux
time needed for runfrom minutes to weeks depending on setup
storagefrom 100 MB to 100 GB

Further information

documentation- Scientific model description and validation (Sofiev et al, 2006); - User's guides - operational instructions - model technical description See the model Web site for some documents: http://silam.fmi.fi
model referencesSofiev M., Siljamo, P., Valkama, I., Ilvonen, M., Kukkonen, J. (2006) A dispersion modelling system SILAM and its evaluation against ETEX data. Atmosph.Environ., 40, 674-685, DOI:10.1016/j.atmosenv.2005.09.069. 9. Sofiev, M., Siljamo, P., Ranta, H., Rantio-Lehtimäki, A. (2006) Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study. Int J. on Biometeorology, DOI 10 1007/s00484-006-0027-x, 50, 392-402 Sofiev, M., Atlaskin E. (2004) An example of application of data assimilation technique and adjoint dispersion modelling to an inverse dispersion problem based on the ETEX experiment. In Air Polution Modelling and its Applications XVII (in press.), also in pre-prints of 27-th Int. Technical Meeting on Air Pollution Modelling and its Applications, Banff, 23-30.10.2004, Canada, pp. 405-412.
webpagehttp://silam.fmi.fi
additional information

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 gasesprobabilities
1st radioactivity
2nd radioactivity
3rd radioactivity
Cd
Pb
other heavymetals
pesticides
1st radioactivityup to 496 nuclides with decay chains
2nd radioactivity
3rd radioactivity
remarksTotally, 8 types of chemical species considered: basic chemical cycle, linear sulphur cycle, radioactive, sea salt, inert primary aerosol, bioaerosol, persistent toxic pollutants, passive tracer

Approximations

Boussinesq
anelastic
hydrostatic
flat earth
remarksFor Lagrangian dynamics, a well-mixing assumption for the boundary layer, fixed mixing in the free troposphere are taken. Eulerian dynamics computes full 4D physics and chemistry

Parametrizations

Chemistry & transport

photolysis rateFor NO2, NO3, HONO, H2O2, HNO3, CH3OOH, HCHO(->H2 and ->HO2)
dry depositionresistive analogy plus sedimentation for aerosols
wet deposition3D scavenging coefficient accounting for: in/sub cloud, rain/snow, convective/large-scale precipitation
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)Basic SOx-NOx-NHx-O3 cycle, with CH4 branch, reservoir species PAN, HONO, CH3O2NO2, HO2NO2
wet phase chemistry (give details)SO2 -> SO4 (gas to particles) parameterised after the DMAT model (Sofiev, 2000, Atmosph. Environ.) HNO3+NH3 <-> NH4NO3 after Finlaison-Pitts & Pitts, 2000
more information

Aerosol chemistry

passive aerosol
dry aerosol
wet aerosol
sectional approach
modal approach
other
nucleationunder testing
coagulationyes
condensationyes
aerosol mixinginternal
aerosol ageing
primary aerosol formation
aerosol-gas phase interactionsammonium nitrate
optical properties6 types of aerosols
give details

Initialization & boundary treatment

Initialization

chemistry & transportZero or prescribed initial concentrations
meteorology

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

orographyfrom the meteo files
land useown compilation, Ecoclimap is gradually replacing other sources
obstacles
vegetation
meteorologyECMWF - operational and ERA-40 HIRLAM any other GRIB-formatted meteo input data
concentrationsAs initial conditions
emissionsAny source. Currently the used sets are from EMEP, GEIS, national inventories, etc.
remarks

Data assimilation

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

Boundary conditions

Chemistry & transport
surfacedry deposition
topclosed for Eulerian, open for Lagrangian dynamics
lateral inflowzero or prescribed concentration
lateral outflowopen

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 exchangearbitrary
explain methodNested fine-scale domain is computed with boundary conditions taken from the coarse grid.
variables nestedconcentrations
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
remarksFor Lagrangian core, the particles use lat-lon coordinates horizontally and pressure system vertically (all axes are continuous, no grid). Input and output are independent from each other and from the internal model routines. Eulerian core uses one of the above grids in projection tied to that of meteorological data (not the grid size, though)

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
other

Spatial discretisation

scalar quantities
additional information
other
chemistry solverManually programmed implicit scheme; also standard solvers suggested by KPP - for the gas-phase chemistry

Model resolution

Chemistry & transport

HorizontalVertical
max2003000
min110

Domain size

Chemistry & transport

HorizontalVertical
max10000same as meteodata
min50same as meteodata

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 examples1. Operational evaluation within GMES MACC project over Europe: daily, several hundreds of the sites (http://www.gmes-atmosphere.eu) 2. Operational (automatic, 4 times a day) for radiaactive emergency preparedness (http://silam.fmi.fi) 3. ETEX 4. Allergenic episodes forecasting (http://pollen.fmi.fi) 5. PM distribution over Europe and Fennoscandia (in progress) 6. Numerous small-scale applications for observational campaigns, source apportionment for the episodes, etc.

Participation in specific model evaluation exercises

AQMEII
List experiments (AQMEII)Europe-2006
Cost728
List experiments (COST728)All
HTAP
List experiments (HTAP)
MEGAPOLI
List experiments (MEGAPOLI)Europe_2005 Paris_2009_winter Paris_2009_summer