Linkage between WRF/NMM and CMAQ Daewon Byun (PI) C.K. Song & P. Percell University of Houston...
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Transcript of Linkage between WRF/NMM and CMAQ Daewon Byun (PI) C.K. Song & P. Percell University of Houston...
Linkage between WRF/NMM and CMAQ
Daewon Byun (PI)C.K. Song & P. PercellUniversity of Houston
Institute for Multidimensional Air Quality Studies (IMAQS)
Coauthors:Jon Pleim, Tanya Otte, Jeff Young, Rohit Mathur
ASMD, Air Resources Laboratory, NOAAIn partnership with U.S. EPA
and many others…Hsin-Mu Lin, David Wong, etc…
Consistent governing set of equations & state variables
Consistent coordinates and grid structures
Consistent numerics & physics, and parameterizations
Flexible: able to help diverse stake holders (research – regulatory application – use of different emissions inputs)
Allow studying effects of using different basic input data (e.g., Land Use/Land Cover, topography, emissions, etc) separately
Same (*) numerics & physics, and parameterizations
Same (*) coordinates and grid structures
Same (*) governing set of equations & state variables
What are the main science issues of the NWP & AQM coupling?
Off-line
On-line* Need to check how closely the dynamics variables and trace species are matched
WRF/nmm
WRF/nmm Postprocessors
(vertical/horizontal)
PREMAQ* (consistent vertical coordinate)
CMAQ
Loose coupling Tight coupling
WRF/nmm
WRF-CMAQ Interface Processor
CMAQ/E-grid
Components of Off-line Coupled system
Spatial interpolation
Lambert conformal projection C-grid
On rotated lat/long E-grid coordinateConsistent vertical coordinate
zszs
zzs
szs Jf
s
vJ
m
Jm
t
JVτ
VV
VV
3
32 ˆ
ˆ)(
)(sss
sss J
s
p
z
s
g
mJp
mJ F̂
(Jsw)
tm2s
JswVz
m
(Jsw ˆ v 3 )
sJs
m
pss
sz Js F3
wQ
(Js )
tm2s
Jsˆ V s
m2
(Jsˆ v 3 )
sJsQ
QJs
vJ
m
Jm
t
Js
ssss
s
)ˆ(ˆ)( 3
22 V
(i Js )
tm2s
iJsˆ V s
m2
( i Jsˆ v 3 )
sJsQ i
)ln()ln(oo
doo
vd RT
TC
o
do p
Rpp
Fully Compressible Atmosphere (OOyama, 1990) used for CMAQ
•Follow coordinates/grid of met model
•Reproduce Jacobian
•Couple state variables consistently
Proper Coupling Requires
WRF/NMMhttp://www.dtcenter.org/wrf-nmm/users/
Nonhydrostatic Mesoscale Model (NMM) core of the Weather Research andForecasting (WRF) system was developed by NOAA/NCEP
ARW (Advance Research WRF)
+ Terrain following hydrostatic P coord. or Terrain following sigma (ARW)+ Arakawa-C+ Conserves mass, momentum, dry entropy, and scalar
WRF/NMM
+ Hybrid sigma-pressure coord.+ Arakawa-E+ Conserves mass, momentum, enstrophy, TKE and scalar
WRF (ARW core) WRF (NMM core)
Hybrid Sigma-Pressure Coordinate
leveltoptheinpressureP
partsigmaofdifferencepressurethicknessPD
partpressureofdifferencepressurethicknessPD
PtyxPDetaPDetatyxP
T
TOP
TTOPhydro
)|,()()()|,,( 21
kx 1ˆ3
kc
TOPx
kcx
PD
gx
p
p
z
x
zJPartUpper
PD
gx
p
p
z
x
zJPartLower
1ˆˆ
:
1
1ˆˆ
:
33ˆ
33ˆ
3
3
)(2
11ˆ:
))(
1(2
11ˆ:
2
)1()1(ˆ
0,:
)(,1:
3
3
213
21
21
21
TOP
T
TTOP
TOP
T
TTOP
TTOP
PD
PPxPartUpper
PD
PPDPxPartLower
etaetax
etaPD
PPetaPartUpper
PD
PPDPetaetaPartLower
PetaPDetaPDP
)2(1
:
)2(1
:
ˆ
3
3
3
ˆ
ˆ
3ˆ
topx
x
x
PDg
JPartUpper
PDg
JPartLower
x
zJ
tops
topkk pp
pp
Initial Terrain-Following Hydrostatic Sigma coordinate
Method 1
Method 2
kc : sigma interface of the lower and upper layersPD: pressure of top of lower layer
Define J for the Generalized Vertical Coordinate
Vertical Jacobian Discontinuity Problem & Solution
For example,
SIGMA LEVELS = 1.0000, .9976, .9948, .9920, .9890, .9858, .9825, .9790, .9754, .9718, .9679, .9637, .9590, .9538, .9480, .9415, .9340, .9251, .9144, .9020, .8883, .8736, .8582, .8420, .8253, .8079, .7900,.7714, .7523, .7326, .7124, .6915, .6699, .6477, .6248, .6015, .5779, .5540, .5300, .5057, .4812, .4566, .4319, .4070, .3822,.3576, .3333, .3100, .2881, .2679, .2494, .2316, .2135, .1936,.1707, .1445, .1159, .0863, .0569, .0282, .0000,
Case 1) Surface pressure = 101300 Pa & sigma(kc)=0.3822,
Pkc PD PDtop Js(lower) Js(upper)
JP method
41806 59494 36806
118988/ρg
73612/ρg
UH method
96300/ρg 96300/ρg
Case 2) Surface pressure = 70000 Pa & sigma(kc)=0.3822,
Pkc PD PDtop Js(lower) Js(upper)
JP method
41806 28194 36806
56388/ρg 73612/ρg
UH Method
45636/ρg 96300/ρg
g
zJ
PdRTk
hydrovk )(ln)()(11
One way to remove discontinuity
Horizontal E-Grid System of WRF/nmm:Rotated lat./long & Arakawa-E grid -> C-grid for CMAQ
If we use diamond gridC(C,R,L,S) -> C*(CR, L,S)
Dynamics with Semi-Staggered Arakawa E gridThe E grid is essentially a superposition of two C grids.
When only the adjustment terms in the equations of motion and continuity are considered, two large-scale solutions from each C grid may exist independently, and a noisy total solution results.
So, employ the forward-backward time differencing scheme to prevents gravity wave separation and thereby precludes the need for explicit filtering (Mesinger 1973: Mesingerand Arakawa 1976; Janji´c 1979).
(1,1) (2,1)
(1,2) (2,2)
(223,501)
(223,500)
(222,501)
(222,500)
dx
dy
dx dx
dx = 0.0534521 deg. (rotated Lon.)
dy = 0.0526316 deg. (rotated Lat.)
2dx
scalarvector
Advantages of usingE-grid with dynamicssolution
Dimension for Grid Point
Dot-Point Cross-Point Flux-Point
For MM5 (MCIP) (NCOL+1 , NROW+1) (NCOL , NROW)X-dir (NCOL+1 , NROW)Y-dir (NCOL , NROW+1)
For WRF/ARW (WCIP)
(NCOL+1 , NROW+1) (NCOL , NROW)X-dir (NCOL+1 , NROW)Y-dir (NCOL , NROW+1)
For WRF/NMM (NCOL , NROW) (NCOL , NROW) (NCOL , NROW)
Consistent coordinates and grid structuresWRF/EM & CMAQ utilize Arakawa-C Grid
Arakawa-B Grid (MM5) is linearly interpolated onto Arakawa-C Grid (CMAQ)
What to do with NMM E-grid data?
How to Utilize Arakawa-E for CMAQ?
Develop a horizontal advection algorithm in CMAQ for Arakawa E-grids Split 2-D horizontal advection operator into 1-D operators and use
CMAQ-proven 1-D schemes, such as PPM, with alternation between appropriate X and Y directions
Work directly with meteorological variables on the E-grid - avoid spatial interpolation
Use rotated square cells (rotated B-grid then on C-grid)
Spatial distribution of dependent variables for a uniformly spaced Arakawa E-Grid
E-Grid with rotated square cells. Scalar variables are considered to be constant on each grid
Advantages Makes the E-Grid look like a B-grid whose “rows” and
“columns” are along diagonal SW→NE and SE→NW lines Can use 1-D algorithm, e.g. PPM, along these lines CMAQ (and preprocessors) are familiar with turning B-grid
data into C-grid flux point data
Disadvantages
Diagonal lines of cells have variable lengths, which requires non-trivial extra book-keeping (in EGRID_MODULE.F)
Requires interpolation of wind velocities to get flux point values Jagged boundary effect Parallelization could be more difficult
Grid geometry changes depending on whether thenumber of columns or rows is even or odd
Bookkeeping issues
Partitioning for parallelization
Jagged Boundary Effect
Boundary values propagate into the domain because boundaries are angled 45 degree
rotated B-grid then on C-grid
Option 1: rotated B-grid then on C-gridCMAQ C-grid
Comparison between regular CMAQ and Option 1
START
get env./IOAPI variables
define grid/coord.- rotated Lat./Lon coord.- E-grid structure- calculate Dx & Dy- allocate memory xgrid and cgrid
get met. data
calculation for WRF/NMM- Eta1 & Eta2- geopotential height- hydrostatic pressure- hydrometeor
derive dynamic fld.
GRIDOUT
METCRO/DOTOUT
continue
END
Calculation Flow of WCIP/NMM Mapping Variables
TEST Run
- Target Period : 00Z June 28 - 06Z June 30, 2006- Horizontal Resolution : ~ 12 km
Model ConfigurationC-Grid E-Grid
-----------------------------------------------------------------------------------------Met. MM5 v3.6.1 WRF/NMM v2.1
(w/ Eta forecast) (w/ Eta forecast)
MCIP MCIP v3.0 WCIP/NMM v1.0BCON BCON/Standard BCON/E-grid v1.0ICON ICON/ Standard ICON/ E-grid v1.0CMAQ CMAQ v4.4 CMAQ/ E-grid v1.0-----------------------------------------------------------------------------------------+ I.C. C-Grid UH-AQF/CMAQ 12km resolution output
00Z June 28, 2006 + B.C. C-Grid UH -AQF /CMAQ 36km resolution output
00Z June 28 – 06Z June 30, 2006 + Emisson None+ Chem. Mech. CB-IV
Domain ConfigurationC-Grid E-Grid
-----------------------------------------------------------------------------------------
Met. (MM5) (WRF/NMM)+ nx(dx) 100(12 km) 85(0.0780 deg.*)+ ny(dy) 100(12 km) 135(0.0724 deg.)+ nz 43 sigma 44 hybrid sigma-P
CMAQ+ nx(dx) 89** 57***+ ny(dx) 89 113+ nz 23 (see COORD_23L.EXT) 23 (JP & Dis.)
-----------------------------------------------------------------------------------------* ds=sqrt(dx**2+dy**2) ~ 12 km** As for DOT case of MCIP, nx and ny should be 90** As for CRO/DOT case of WCIP/NMM, nx(ny) should be 59(115)
Recommended Model Physics for WRF/NMM Microphysics : Ferrier Cumulus Convection : Betts-Miller-Janjic Shortwave Radiation : GFDL Longwave Radiation : GFDL Lateral diffusion : Smagorinsky PBL, free atmosphere : Mellor-Yamada-Janjic Surface Layer : Janjic Scheme Land-Surface : 4-layer soil model
CMAQ ResultsNo emissions,
Transport & Chemistry Only
12Z (06 CST) June 28, 2006(12 hrs after initial time)
C-Grid E-Grid Wind PBLHCO O3
C-Grid E-Grid Wind PBLHCO O3
hr18
C-Grid E-Grid ZH JabobianAir temp. U-wind
---- 13000 m---- 13000 m
discontinuity
C-Grid E-Grid
CO CO
C-Grid E-Grid
O3 O3
Conclusion+ Presented a method to cast the WRF meteorological data on CMAQ grid & coordinate structures to represent transportation of pollutants.
+ Developed WCIP/NMM, BCON/E-grid, ICON/E-grid, and CMAQ/E-grid
+ Performed simulation (WRF/NMM -> CMAQ/E-grid) was successfully done
+ A simple evaluation with transport and chemistry was performedResults of CMAQ/E-grid simulation is generally consist with CMAQ/C-grid but reveal properly the discrepancy of meteorological fields
Future Work+ To solve some unsolved problems (WRF/NMM IOAPI, etc)+ More Evaluations & Documentation+ Deliver the developed codes to NOAA/EPA for National AQF