1 / 29

Linkage between WRF/NMM and CMAQ

Linkage between WRF/NMM and CMAQ. Daewon Byun (PI) C.K. Song & P. Percell University of Houston Institute for Multidimensional Air Quality Studies (IMAQS) Coauthors: Jon Pleim, Tanya Otte, Jeff Young, Rohit Mathur ASMD, Air Resources Laboratory, NOAA In partnership with U.S. EPA

armine
Download Presentation

Linkage between WRF/NMM and CMAQ

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Linkage between WRF/NMM and CMAQ Daewon Byun (PI) C.K. Song & P. Percell University of Houston Institute for Multidimensional Air Quality Studies (IMAQS) Coauthors: Jon Pleim, Tanya Otte, Jeff Young, Rohit Mathur ASMD, Air Resources Laboratory, NOAA In partnership with U.S. EPA and many others… Hsin-Mu Lin, David Wong, etc…

  2. What are the main science issues of the NWP & AQM coupling? Off-line • 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 On-line * Need to check how closely the dynamics variables and trace species are matched

  3. Components of Off-line Coupled system WRF/nmm Spatial interpolation WRF/nmm WRF/nmm Postprocessors (vertical/horizontal) WRF-CMAQ Interface Processor PREMAQ* (consistent vertical coordinate) CMAQ/E-grid CMAQ On rotated lat/long E-grid coordinate Consistent vertical coordinate Lambert conformal projection C-grid Loose coupling Tight coupling

  4. Fully Compressible Atmosphere (OOyama, 1990) used for CMAQ Proper Coupling Requires • Follow coordinates/grid of met model • Reproduce Jacobian • Couple state variables consistently

  5. WRF (ARW core) WRF (NMM core) WRF/NMM http://www.dtcenter.org/wrf-nmm/users/ Nonhydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system was developed by NOAA/NCEP WRF/NMM + Hybrid sigma-pressure coord. + Arakawa-E + Conserves mass, momentum, enstrophy, TKE and scalar ARW (Advance Research WRF) + Terrain following hydrostatic P coord. or Terrain following sigma (ARW) + Arakawa-C + Conserves mass, momentum, dry entropy, and scalar

  6. Hybrid Sigma-Pressure Coordinate

  7. Define J for the Generalized Vertical Coordinate Initial Terrain-Following Hydrostatic Sigma coordinate Method 1 : sigma interface of the lower and upper layers PD: pressure of top of lower layer Method 2

  8. Vertical Jacobian Discontinuity Problem & Solution One way to remove discontinuity 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, Case 2) Surface pressure = 70000 Pa & sigma(kc)=0.3822,

  9. Horizontal E-Grid System of WRF/nmm:Rotated lat./long & Arakawa-E grid -> C-grid for CMAQ If we use diamond grid C(C,R,L,S) -> C*(CR, L,S)

  10. (222,501) (223,501) (222,500) (223,500) dy (1,2) (2,2) dx = 0.0534521 deg. (rotated Lon.) dy = 0.0526316 deg. (rotated Lat.) (1,1) (2,1) scalar vector dx dx dx 2dx Dynamics with Semi-Staggered Arakawa E grid The E grid is essentially a superposition of two C grids. Advantages of using E-grid with dynamics solution • 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).

  11. Consistent coordinates and grid structures WRF/EM & CMAQ utilize Arakawa-C Grid Arakawa-B Grid (MM5) is linearly interpolated onto Arakawa-C Grid (CMAQ) Dimension for Grid Point What to do with NMM E-grid data?

  12. 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

  13. 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

  14. Bookkeeping issues Grid geometry changes depending on whether the number of columns or rows is even or odd Partitioning for parallelization

  15. Jagged Boundary Effect rotated B-grid then on C-grid Boundary values propagate into the domain because boundaries are angled 45 degree

  16. Comparison between regular CMAQ and Option 1 Option 1: rotated B-grid then on C-grid CMAQ C-grid

  17. Calculation Flow of WCIP/NMM Mapping Variables 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 GRIDOUT derive dynamic fld. METCRO/DOTOUT continue END

  18. TEST Run • Target Period : 00Z June 28 - 06Z June 30, 2006 • Horizontal Resolution : ~ 12 km

  19. Model Configuration C-Grid E-Grid ----------------------------------------------------------------------------------------- Met. MM5 v3.6.1 WRF/NMM v2.1 (w/ Eta forecast) (w/ Eta forecast) MCIP MCIP v3.0 WCIP/NMM v1.0 BCON BCON/Standard BCON/E-grid v1.0 ICON ICON/ Standard ICON/ E-grid v1.0 CMAQ 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

  20. Domain Configuration C-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)

  21. 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

  22. CMAQ Results No emissions, Transport & Chemistry Only 12Z (06 CST) June 28, 2006 (12 hrs after initial time)

  23. C-Grid E-Grid Wind PBLHCO O3

  24. C-Grid E-Grid Wind PBLHCO O3 hr18

  25. C-Grid E-Grid ZH JabobianAir temp. U-wind ---- 13000 m ---- 13000 m discontinuity

  26. C-Grid E-Grid CO CO

  27. C-Grid E-Grid O3 O3

  28. 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 performed Results 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

More Related