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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.

CMAQ(GKSS): Community Multiscale Air Quality Model

General information

Model name and version

short nameCMAQ(GKSS)
full nameCommunity Multiscale Air Quality Model
revision4.5
date09/2005
last change

Responsible for this information

nameVolker Matthias
instituteGKSS Research Center
addressMax-Planck-Strasse 1
zip21502
cityGeesthacht
countryGermany
phone+49-4152-872346
fax+49-4152-872332
e-mailvolker.matthias(belongs-to)gkss.de

Additional information on the model

Contact person for model code

same as person above
name
instituteCommunity Model and Analysis System
divisions
street
zip
city
countryUSA
phone
emailcmas@unc.edu
fax

Model developer and model user

developer and userCMAQ was developed as community chemistry transport model by US EPA and University of North Carolina. It is mainly used in the US but in the mentime also by several groups in Europe and Asia.

Level of Knowledge needed to operate model

basic
intermediate
advanced
remarksCurrently runs with MM5 or WRF meteorological input data

Model use at your institution

operational
for research
other use

Model code available?

is available?yes
more detailscan be downloaded (www.cmascenter.org)

Minimum computer resources required

typelinux PC
time needed for run40 min. for one day (54 km domain) on a single processor. Can be run much faster in parallel mode (approx. 5 min./day on 12 processors)
storage2.5 GB/day for both domains

Further information

documentationByun, D.W. and Ching, J.K.S., 1999. Science Algorithms of the EPA Models-3 Community Multiscale Air Quality Modeling System, EPA/600/R-99/030, US Environmental Protection Agency, Office of Research and Development, Washington DC see www.cmascenter.org
model referencesByun and Schere: Review of the governing equations, computational algorithms and other components of the Community Multiscale Air Quality (CAMQ) Modeling System, Applied Mechanics Reviews 59, 2006
webpagewww.cmascenter.org
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 gasesOH, H2O2, HONO,
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 rateThe actinic flux is calculated with a delta-Eddington two-stream radiative transfer model. The precalculated clear sky photolysis rates are derived from look-up tables and then corrected for cloud cover.
dry depositionresistance approach considering aerodynamic resistance, canopy resistance, sub layer resistance.
wet depositionGas scavenging depends on Henry's law constants, dissociation constants and cloud water pH. Wahout time depends on total cloud water and the precipitation rate. Acccumulation and coarse mode aerosols are assumed to be completely absorbed by cloud and rain water.
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)CB4 algorithm (Gery et al, 1987) including aerosols
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 & transportconstant fields are applied at the beginning of each simulation. The simulation is run 5 days before the period of interest (which is typically one month), to allow for concentrations which are almost independent on initial conditions.
meteorology

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

orographyfrom MM5 TERRAIN files
land usefrom MM5 TERRAIN files
obstacles
vegetation
meteorologyInput fields from MM5 are preprocessed to be used in CMAQ. MM5 calculations are done in the same group.
concentrationsboundary conditions from MOZART have been testes but are not used on a routine basis.
emissionsHourly resolution fields for 2000 from IER Stuttgart on the 54 km and 18 km grids over Europe and the North Sea. Variables NOx, SO2, CO, NH3, several NMVOCs (RADM speciation) PM10, PM2.5. Terpenes and Isoprene are taken from RETRO archives. BaP emissions are from TNO for 2000 and from Pacyna et al. for earlier years.
remarks

Data assimilation

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

Boundary conditions

Chemistry & transport
surfacewet and dry deposition, emissions
top
lateral inflowEither constant average profiles or BC are taken from a global chemistry model (e.g. MOZART). zero flux divergence
lateral outflowzero flux divergence

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 exchangetyp. one hour
explain methodThe concentrations and fluxes are taken from the coarse grid and used as boundary conditions for the fine grid.
variables nestedall gas and aerosol species (82 in total)
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
remarksdepends on the prescribed meteorology grid. CMAQ runs on the same grid.

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 solverdifferent solvers can be chosen. At GKSS the MEBI solver for the CB iV algorithm is used.

Model resolution

Chemistry & transport

HorizontalVertical
max54300
min1837

Domain size

Chemistry & transport

HorizontalVertical
max400015000
min100015000

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 examplesV. Matthias, A. Aulinger, M. Quante: ADAPTING CMAQ TO INVESTIGATE AIR POLLUTION IN NORTH SEA COASTAL REGIONS, submitted to Environmental modelling and software, 2006 I. Bewersdorff, A.Aulinger, V. Matthias and M. Quante (2006): The effect of temporal resolution of PAH emission data on transport and deposition patterns simulated with the Community Multiscale Air Quality modelling system (CMAQ), submitted to Meteorologische Zeitschrift

Participation in specific model evaluation exercises

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