MeteorologyChemistry Interface Processor MCIP

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Meteorology-Chemistry Interface Processor (MCIP)
CMAQ Training Course July 9, 2002
Daewon W. Byun
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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

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MCIP Functions Parameters

• Incorporates landuse data
• Computes or passes through surface, PBL, and
  radiation parameters
• Diagnoses cloud parameters
• Computes species-specific dry deposition
  velocities

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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

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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)

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Flow Chart
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Flow Chart
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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

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Computational Structure

• SOLAR
• computes solar radiation parameters
• PBLPKG/PBLSUB
• computes PBL parameters using diagnostic method
• BCLDPRC_AK
• computes diagnostic convective cloud parameters

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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

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Data Types and CMAQ Grid System
Arakawa C- and E-grids
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Grid Points Cross, Dot, Flux
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Dimensions for MCIP Grids
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MCIP Data Types
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Windowing
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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 NDX3 (odd number recommended) to match
  flux points for interpolation

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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.

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Vertical Layer Collapsing Example
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Linking Land use Data

• From TERRAIN (binary file)
• Dominant land use data in MM5 category
• From MM5 Output directly
• Dominant land use MM5 category
• Preprocessed land use (ASCII)
• Fractional land use data
• LUPROC output
• Fractional land use data from USGS database

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Matching Land use Categories
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Matching Landuse Categories
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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

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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

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Met. Data for CMAQ CTM with Generalized
Coordinate System

• Thermodynamic Varaibles
• Pressure, Entropy (or potential temperature)
• Density of air, density of water vapor
• Parameters for dynamic consistency

Total Jacobian Density Jacobian, entropy
Jacobian Contravariant wind components
Jacobiandensity
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Building MCIP Modules
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Building MCIP Modules
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Environmental Variables for MCIP
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Environmental Variables for MCIP
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MCIP2

• See the release description

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The End.

• Happy MCIPing