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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 MCIPing