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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.

GEM-AQ: Global Environmental Multiscale - Air Quality model

General information

Model name and version

short nameGEM-AQ
full nameGlobal Environmental Multiscale - Air Quality model
revision1.0
dateOctober 10, 2006
last change

Responsible for this information

nameJacek W. Kaminski
instituteYork University
address4700 Keele Street
zipM3J1P3
cityToronto, Ontario
countryCanada
phone+1-416-822-6940
fax
e-mailjwk(belongs-to)wxprime.com

Additional information on the model

Contact person for model code

same as person above
nameAlex Lupu
instituteYork University
divisionsCRESS
street4700 Keele Street
zipM3J1P3
cityToronto, Ontario
countryCanada
phone+416-736-2100 x 77701
emailalexlupu@yorku.ca
fax+416-736-5817

Model developer and model user

developer and userRecherche en Prévision Numérique (RPN) division of the Meteorological Service of Canada (MSC), Environment Canada; The Multiscale Air Quality Modelling Network (MAQNet); York University, Toronto, Canada; Warsaw University of Technology, Warsaw, Poland

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

typeLinux PC
time needed for rundepends on physics and chemistry, dt, dx
storageany subset of fields on any subdomain

Further information

documentationhttp://collaboration.cmc.ec.gc.ca/science/rpn.comm/wiki/doku.php?id=gem
model referencesKaminski, J. W., Neary, L., Struzewska, J., McConnell, J. C., Lupu, A., Jarosz, J., Toyota, K., Gong, S. L., Côté, J., Liu, X., Chance, K., and Richter, A.: GEM-AQ, an on-line global multiscale chemical weather modelling system: model description and evaluation of gas phase chemistry processes, Atmos. Chem. Phys., 8, 3255-3281, 2008. www.atmos-chem-phys.net/8/3255/2008/
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

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 gaseshttp://www.yorku.ca/lori/howtos/speciation_new.htm
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

Meteorology

turbulence schemePrognostic equation for turbulent kinetic energy [Benoıt et al., 1989]. Shallow convection is simulated using a method described by Mailhot (1994) and is treated as a special case of the turbulent planetary boundary layer to include the saturated case in the absence of precipitation.
deep convectionKuo-type convective parameterization [Kuo, 1974; Mailhot et al., 1989]; Kain-Fritsch (1990, 1993)
surface exchangeForce-restore [Deardorff, 1978; Benoıt et al., 1989], ISBA, CLASS
surface temperature
surface humidity
radiationThe infrared radiation scheme [Garand, 1983; Garand and Mailhot, 1990; Yu et al., 1997] includes the effects of water vapour, carbon dioxide, ozone, and clouds. The solar radiation scheme follows the method described by Fouquart and Bonnel (1980).
unresolved orographic dragGravity wave drag parameterization based on a simplified linear theory for vertically propagating gravity waves generated in statically stable flow over mesoscale orographic variations [McFarlane, 1987; McLandress and McFarlane, 1993]
radiation in vegetation
radiation between obstacles
treatment of obstacles
clouds / rain
remarks

Chemistry & transport

photolysis rateMESSy-J [Landgraf and Crutzen, 1998; Joeckel et al., 2006]. Radiative transfer calculations are done using a delta-two stream approximation for 8 spectral intervals in the UV and visible applying precalculated effective absorption cross sections. This method also allows for scattering by cloud droplets and for clouds to be present over a fraction of a grid cell.
dry deposition'Big leaf' multiple resistance model [Wesely, 1989; Zhang et al., 2002] with aerodynamic, quasi-laminar layer, and surface resistances acting in series.
wet depositionOnly below-cloud scavenging of gas phase species is considered. The efficiency of the rainout is assumed to be proportional to the precipitation rate and a species-specific scavenging coefficient.
remarks

Chemical reactions

Gas & wet phase chemistry

chemical transformations calculated
chemical transformations neglected
other
gas phase chemistry (give details)Based on a modification of version II of the Acid Deposition and Oxidants Model (ADOM) [Venkatram et al., 1988], derived from the condensed mechanism of Lurmann et al. (1986). 49 species (34 advected), 118 chemical reactions, 19 photolysis reactions. All species are solved using a mass-conserving implicit time stepping discretization, with the solution obtained using Newton’s method. Heterogeneous hydrolysis of N2O5 is calculated using the on-line distribution of aerosol.
wet phase chemistry (give details)Simplified aqueous-phase reaction module for oxidation of SO2 to sulphate.
more informationhttp://www.atmos-chem-phys-discuss.net/7/14895/2007/

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 detailsFive size-resolved aerosols types, viz. sea salt, sulphate, black carbon, organic matter, and dust. The microphysical processes which describe formation and transformation of aerosols are calculated by a sectional aerosol module [Gong et al., 2003]. The particle mass is distributed into 12 logarithmically spaced bins from 0.005 to 10.24 microns radius. The following aerosol processes are accounted for in the aerosol module: nucleation, condensation, coagulation, sedimentation and dry deposition, in-cloud oxidation of SO2, in-cloud scavenging, and below-cloud scavenging by rain and snow.

Initialization & boundary treatment

Initialization

chemistry & transportfields from previous runs
meteorology

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

orographyhttp://collaboration.cmc.ec.gc.ca/science/rpn.comm/wiki/doku.php?id=gengeo
land usehttp://collaboration.cmc.ec.gc.ca/science/rpn.comm/wiki/doku.php?id=gengeo
obstacles
vegetation
meteorologyCMC analysis
concentrations
emissionsEDGAR 2.0; GEIA; GFEDv2; other
remarks

Data assimilation

MeteorologyChemistry & transport
nudging technique
adjoint model
3D-VAR
4D-VAR
OI
detailsCanadian Meteorological centre operation 4D-Var3D-Var for chemical species - experimental

Boundary conditions

MeteorologyChemistry & transport
surfaceland-sea mask, roughness length, sea surface temperature, land surface temperature, deep soil temperature, soil wetness, snow fraction on the ground, sea ice, surface albedosurface emissions and dry deposition included in the vertical diffusion equation
topin tropospheric mode: O3, NOx, HNO3 replaced with climatological values above 100 hPa
lateral inflow
lateral outflow

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 exchangespecified by the userspecified by the user
explain method
variables nestedall met & chemistry
otherglobal variable resolution

Solution technique

Coordinate system and projection

Horizontal

cartesian
Lambert conformal
latitude / longitude
rotated lat. / long.

Vertical

z coordinate
surface fitted grid
pressurecoordinate
sigma coordinate
remarkssigma-pressure hybrid vertical coordinate

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

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
otherImplicit Newton, Rosenbrook 2 & 3

Spatial discretisation

scalar quantities
additional information
other
chemistry solverMass-conserving implicit time stepping discretization, with the solution obtained using Newton’s method. Optimized code is generated by a preprocessor.

Model resolution

Meteorology

HorizontalVertical
maxanyany
minanyany

Chemistry & transport

HorizontalVertical
maxanyany
minanyany

Domain size

Meteorology

HorizontalVertical
maxglobal0.1hPa
min

Chemistry & transport

HorizontalVertical
maxglobal0.1hPa
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 examplesO’Neill, N. T., Campanelli, M., Lupu, A., Thulasiraman, S., Reid, J. S., Aubé, M., Neary, L., Kaminski, J. W., and McConnell, J. C.: Evaluation of the GEM–AQ air quality model during the Québec smoke event of 2002: Analysis of extensive and intensive optical disparities, Atmos. Environ., 40, 3737–3749, 2006. Struzewska, J. and Kaminski, J. W.: Formation and transport of photooxidants over Europe during the July 2006 heat wave – observations and GEM–AQ model simulations, Atmos. Chem. Phys. Discuss., 7, 10 467–10 514, 2007.

Participation in specific model evaluation exercises

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