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A Brief Introduction to CMAQ
Serena H. ChungBioEarth Working Group 1 Seminar
May 21, 2012
Outline
• Chemical Transport Models (CTMs)• CMAQ Model Components• CMAQ Output• Parallel Programming in CMAQ• WRF and CMAQ Linkages
Chemical Transport Models (CTMs)
• Transport: – Same physics as numerical weather model, but different numerical methods
are needed
• Chemistry– Focuses on criteria pollutants which negatively affect human health
• Ozone (O3): plant stresser ecosystem impact
• Particular Matter (PM) in air quality community or aerosols in climate science community
– Consists of hundreds if not thousand of chemical species– Climate impact: scatter and absorb radiation; affects cloud formation
• NOx (=NO + NO2): most of which eventually deposits as nitrate ecosystem impact
• SO2 : forms, sulfate aerosol, contributes to acidification ecosystem impact
• Mercury and other air toxics
Chemical Transport Model Equation
• Solves for species concentration Cs using mass conservation equation for each grid cell and time step:
• Input or derived from numerical weather model (e.g., WRF, MM5) Wind fields: u, v, w Eddy diffusivity (turbulent diffusion) coefficients: Kx=Ky, Kz
Temperature, Pressure, (& Radiation Fields): To calculate reaction rates Emissions rate can also be temperature and/or light dependent
Clouds & Precipitation: Aqueous-phase reactions Removal rate by wet deposition
Dry deposition velocities vd,s, where Ds = vd,s Cs,layer 1
change in concentration
horizontal advection
vertical advection
horizontaldiffusion
vertical diffusion
chemical reaction
deposition
emission
Chemical Mechanisms• A chemical mechanism is a condensed set of chemical reactions
– Chosen to represent conditions of interest, .e.g, O3 in polluted environment, stratospheric O3
• Example - University of Leeds Master Chemical Mechanism– Thousands of species and >10,000 chemical reactions
• Options in CMAQ v5.0– CB05: ~72 species, ~187 reactions– SAPRC99: ~88 species, ~144 reactions– SAPRC07: ~150 species, ~413 reactions
NO NO2
O3
RO2 or HO2
NOx (NO+NO2)
PAN
HNO3
OH
NO3
O3 HNO3
N2O5
NO2 + Aer H2O
DMS or VOC
AtmosphericDeposition
hn
● ●
●
●
R can be lots of stuff with carbon and hydrogen atoms
Nitrogen cycle in the troposphere is tightly
coupled to O3 & aerosol chemistry
Aerosol Size Distribution
Based on Whitby, Atmos. Environ., 1978
Num
ber
Dist
ributi
onVo
lum
eD
istrib
ution
Typical Urban Conditions
Aerosol Size Distribution & Composition
Based on Whitby, Atmos. Environ., 1978
Num
ber
Dist
ributi
onVo
lum
eD
istrib
ution
Typical Urban Conditions
Aerosol Size Distribution
Based on Whitby, Atmos. Environ., 1978
Num
ber
Dist
ributi
onVo
lum
eD
istrib
ution
Typical Urban Conditions
Aerosol Size Distribution
Based on Whitby, Atmos. Environ., 1978
Num
ber
Dist
ributi
onVo
lum
eD
istrib
ution
Typical Urban Conditions
Aerosol Size Distribution:Number vs Surface vs Volume
• Number– Affects the number of cloud
droplets that form• Surface Area
– Affects the amount of radiation that is scatter or absorbed
• Volume– Portional to mass, used by the
National Ambient Air Quality Standards (NAAQS)
– PM10 & PM2.5 standards designed to distinguish coarse and fine particles.
Figure 7.6Seinfeld & Pandis
Number
Surface Area
Volume
10 mm2.5 mm
Aerosol Size Representations
• No size representation, simulate only aerosol mass• Use few lognormal distributions (e.g, CMAQ uses 3), each characterized by
– Total particle number concentrations– Median diameter– Geometric standard deviation
• Use sectional bins– Track aerosol mass only, or– Track aerosol number and mass
• Mixtures– Internally mixed – all particles within a bin or lognormal distribution have the same
chemical composition– Externally mixed – each particle contains one “species”, so species are not mixed– Combination of the two
• Effective number of species Neff for sectional bins with number and mass: Neff = (1 + Nspecies) Nmixture Nbin
Nspecies = ~ 20 Nmixture = 1-5 Nbin = 4-30
Chemical Tranport Model
• Operator splitting -- the equation is split into parts and solved separately:
1) vertical diffusion, emission, & dry deposition 2) horizontal advection3) vertical advection 4) horizontal diffusion5) cloud processes (includes aqueous chemistry)6) gas-phase chemistry7) aerosol chemistry
change in concentration
horizontal advection
vertical advection
horizontaldiffusion
vertical diffusion
chemical reaction
deposition
emission
Horizontal Discretization in CMAQ
Dx
Dy
East
North
i i+1i-1
j+1
j-1
j
Ci,j,s ui+1,j
vi,j+1
Arakawa C Grid
AIRPACT-3 Example:12-km x 12-km grids in
Lambert Conformal Conic Projection
Vertical Discretization in CMAQ
Dx
Dh
East
Up
i i+1i-1
k+1
k-1
k
Ci,k,sui+1,j
wi,k+1
WRF Example: Terrain-Following, Hydrostatic Pressure Grid
Figure not to scaleAdapted from Figure 2.1 of Skamarock et al., 2008
Pressure at model top: pht ~ 10,000 Pa (~ 15 km)
~30-40 levels with first layer height at ~ 40 m
where Ph = hydrostatic pressure
Vertical Discretization AIRPACT-4 Example
CMAQ Grid Cell in 3-Dimension
wi,j,k
wi,j,k+1
ui,j,k
ui+1,j,k
vi,j/2,k
vi,j+1,k
East
NorthUp
• Air density• Temperature• Pressure• Water mixing ratios
(vapor, rain, snow, ice)• Gas- and aerosol-phase
chemical species mixing ratios
Why does CMAQ take so long to run?• The nature of chemical transport models:
– Gas phase: ~ 100 chemical species– Particle phase: ~20 species, 3-16 size bins
effectively ~60-320 species minimum
• ODEs governing the chemical reactions:– Nonlinear– Stiff -- eigenvalues of Jacobian : negative; min/max ratio is ~ 109
Figure from Gustafason et al. (2005) (http://www.mmm.ucar.edu/wrf/users/workshop/WS2005/presentations/sessions8/4-Gustafson.pdf
Model Time Steps
• WRF: – Physics: recommendation is 6 seconds per km of Dx, i.e., 72 seconds for 12-km x 12-km grids
– Radiation: recommendation is 1 minute per km of Dx, i.e., 12 minutes for 12-km x 12-km grids
• CMAQ: – Synchronization between all processes: ~ 1-3 min – Adaptive time step within each process
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
Meteorology
• Meteorological fields from a numerical weather model
• Usually MM5 or WRF, though other models can also be used
http://www.atmos.washington.edu/mm5rt
Example of Layer 1 Temperature and Wind
Fields from WRF
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
• Converts WRF or MM5 output files into CMAQ-ready files
• Calculates/diagnoses parameters not provided by WRF (e.g., Monin-Obukhov length)
• Calculates dry deposition velocities (depends on land-use type and turbulence characteristics)
• Keeps the same horizontal grid cell size
• Collapses WRF layers into fewer layers if desired
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
Emissions: Various models/processors, e.g.,
TransportationIndustrial
ResidentialPower Plants
FireBiogenic
etc
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
Initial Conditions:• Usually from a previous run• Only ~ 2-3 days for spin-up
required
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
Boundary Conditions Using:• “Idealized’ profile, • Results from a coarser,
bigger domain CMAQ simulation, or
• Results of global CTMs
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
Photolysis Rate Calculations• Using look-up table for
clear-sky conditions and adjusted “online” based on cloud conditions
CMAQ Model Components
http://www.airqualitymodeling.org/cmaqwiki/index.php?title=File:Figure5-1.png
Solves
CMAQ Output
• Hourly, 3-dimensional concentrations (.e.g, parts per billion or mg m-3) of chemical species
• Hourly accumulated wet and dry deposition (.e.g, kg ha-1 hr-1) for relevant species
• netCDF files – same as WRF, but different conventions for date/time– read/write easier with use of Models-3 I/O API library
• Examples:– http://lar.wsu.edu/airpact– http://lar.wsu.edu/airpact/gmap/testC.html
CMAQ Output : AIRPACT Example
• Lots of stuff at:– AIRPACT-3: http://lar.wsu.edu/airpact– AIRPACT-4: http://lar.wsu.edu/airpact/gmap/testC.html
12-km, Surface-Layer, Hourly Concentrations of
Secondary Organic Aerosl (SOA)
CMAQ Output: Vertical DistributionAIRPACT-4 Output for
10AM PST on Feb 23, 2011O3 Concentation
Parallel Progamming in CMAQ
• Distributed Memory using Message Passing Interface (MPI) (WRF supports OpenMP and MPI)
• Divide and conquer by horizontal domain decomposition– Similar to WRF, but specifics are different
• For I/O, each processor gets the data for its subdomain by extracting the data from the full domain. However, only one processor is responsible for writing to the output data files; thus, gathering full domain data is required before writing
0 1 2
4
3
65 7
8 9 10 11
12 13 14 15
WRF-CMAQ Soft Link
Meteorological Fields
Static Geographical Data
Global Data
Geographical & Large-scale Meteorological Data
Interpolated to simulation grids
Initial & Boundary Conditions
METGRIDGEOGRID
UNGRIB
REAL
WRF
MCIP
ICON
BCON
JPROC
CCTM
EmissionModels
Coupled WRF-CMAQ
Meteorological Fields
Static Geographical Data
Global Data
Geographical & Large-scale Meteorological Data
Interpolated to simulation grids
Initial & Boundary Conditions
METGRIDGEOGRID
UNGRIB
REAL
WRF
call aqprepcall cmaq_driver
call feedback_read
MCIP
ICON
BCON
JPROC
CCTM
EmissionModels
Speciated Aerosol Size
Distributions, &O3
Concentrations
WRF-CMAQ Domains
WRF Domain
Max CMAQ Domain
CMAQ Domain5 columns
5 rows
delta_x
delta_y
CMAQ_COL_DIM
CMAQ_ROW_DIM
Adapted from Figure 2 of Wong et al., Geosci. Model Dev., 2012
Coupled WRF-CMAQ Computaional Performance
Execution timeCAM RRTMG
WRF only MCIP Offline CMAQLoose couple system, Total time
0:19:590:02:311:18:28
1:40:58
0:18:500:02:311:19:051:40:26
Coupling system w/o feedback and call frequency ratio 5:1 1:41:12 1:48:59Coupling system w/ feedback and call frequency ratio 5:1 1:43:39 2:54:25
Table 1 of Wong et al., Geosci. Model Dev., 2012
Processor
configuration
CAM RRTMGw/o
feedbackspeedup w/
feedbackspeedup w/o
feedbackSpeedup w/ feedback speedup
4x8 2:05:06 2:08:21 2:13:17 3:19:258x8 1:19:46 1.57 1:21:57 1.57 1:24:12 1.58 1:58:21 1.68
8x16 0:55:28 2.26 0:55:12 2.33 0:56:38 2.35 1:14:14 2.69
Table 2 of Wong et al., Geosci. Model Dev., 2012
Based on 24-hour simulations for a 12-km eastern US domain
Some resources
• http://cmaq-model.org• http://cmascenter.org/• Seinfeld, J.H. and S.N. Pandis, Atmospheric Chemistry and Physics: From Air
Pollution to Climate Change, John Wiley & Sons, 2006.• Jacob, D.J., Introduction to Atmospheric Chemistry, Princeton University Press,
1999.• Jacobson, M.Z., Fundamentals of Atmospheric Modeling, Cambridge University
Press, 1999