Meteorology-Chemistry Interface Processor MCIP

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Meteorology-Chemistry Interface Processor MCIP

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3. MCIP Functions: Data Extraction Reads meteorological model output files Extracts met. data for CMAQ domain Interpolates coarse horizontal grid output for finer grid Collapses met. profile data for coarse vertical resolution if needed

4. MCIP Functions: Parameters Incorporates landuse data Computes or passes through surface, PBL, and radiation parameters Diagnoses cloud parameters Computes species-specific dry deposition velocities

5. MCIP Functions: Dynamics Meteorological data for generalized coordinate system incorporates many coordinate-related functions traditionally treated in CTM helps maintaining modularity of CMAQ provides a mass-consistent interpolation methods and routines

6. MCIP Functions: Output Data Outputs meteorological data in Models-3 I/O API format MCIP files for different data types Time independent: GRID_(CRO/DOT)_(2D/3D) Time dependent: MET _(CRO/DOT)_(2D/3D) Boundary files: (GRID/MET)_BDY_(2D/3D)

9. Computational Structure GETMET: reads and extract data from standard MM5 output for CCTM window domain converts variables into SI units, and process special files PBLPKG/PBLSUB: computes PBL parameters using diagnostic method BCLDPRC_AK: diagnoses convective cloud parameters

10. Computational Structure SOLAR: computes solar radiation parameters PBLPKG/PBLSUB: computes PBL parameters using diagnostic method BCLDPRC_AK: computes diagnostic convective cloud parameters

11. Computational Structure RADMDRY/M3DRY: computes dry deposition velocities METCRO_OUT & METDOT_OUT: computes additional meteorology data required for the generalized CTM interpolates mean profile data into finer grid resolution if needed output Models-3 I/O API meteorology files

12. Data Types and CMAQ Grid System

13. Grid Points: Cross, Dot, Flux

15. Dimensions for MCIP Grids

16. MCIP Data Types

17. Windowing

18. Horizontal Interpolation To test impact of high-resolution emissions data Is not a replacement for high resolution meteorology model run Needs high-resolution landuse data to be useful Surface parameters and profiles (T, U,V, Q) are bi-linearly interpolated Possible consistency problems exist Example: NDX=3 (odd number recommended) to match flux points for interpolation

19. Vertical Layer Collapsing To reduce resource requirements in CMAQ Sensible layer structure design is a necessity High resolution PBL and Capture cloud layer, Represent transport in upper atmosphere Maintain vertical fluxes across the layer interfaces Will modify aerodynamic resistance (deposition velocities), diagnosed surface and cloud parameters Collapsing is automatic given COORD.EXT with smaller number of layers.

21. Linking Land use Data

24. Physical Parameters PBL Parameters Stability parameters (M-O length, Rib) Heat, momentum, moisture fluxes Temperatures at 1.5m and 10 m PBL height, aerodynamic resistance Cloud and solar radiation parameters Cloud coverage, cloud bottom & top heights Precipitation, liquid water content Surface albedo, incident & absorbed shortwave radiations

25. Deposition Velocities RADM method Highly parametrized Wesely (1989) method Uses fractional landuse information Models-3 CMAQ method Requires an improved land-surface algorithm in meteorology model (e.g., MM5 Pleim-Xiu version) Grid-averaged surface parameters including surface resistances are used Coupling to the land-surface model for describing stomatal pathways

26. Met. Data for CMAQ CTM with Generalized Coordinate System

27. Building MCIP: Modules

28. Building MCIP: Modules

29. Environmental Variables for MCIP

30. Environmental Variables for MCIP

31. MCIP2 See the release description

32. The End…. Happy MCIP’ing

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