Development and Preliminary Development and Preliminary Results of Image Processing Tools Results of Image Processing Tools

for Meteorology and Air Quality for Meteorology and Air Quality ModelingModeling

Limei RanLimei RanCenter for Environmental Modeling for Policy DevelopmentCenter for Environmental Modeling for Policy Development

Institute for the Environment, UNC-Chapel HillInstitute for the Environment, UNC-Chapel Hill

Jonathan Pleim and Robert GilliamJonathan Pleim and Robert GilliamAtmospheric Modeling and Analysis DivisionAtmospheric Modeling and Analysis Division

USEPA/ORD/NERL, RTP, NCUSEPA/ORD/NERL, RTP, NC

Outline of the PresentationOutline of the Presentation

• Spatial Allocator (SA) – Raster Tools

• GOES, OMI, and MODIS Tools

• WRF and CMAQ Outputs, 08/2006

• Conclusions and Future Work

• Acknowledgements

Raster tools in Spatial Allocator (SA) Raster tools in Spatial Allocator (SA)

• The SA Raster tools are developed to compute image/satellite data on model grids

• The tools can process:• 2001 30m NLCD and 1km MODIS land cover data• GOES satellite data (new)• OMI Level 2G and 3 data (new)• MODIS Level 2 cloud product (under development)

• SA Web site: http://www.ie.unc.edu/cempd/projects/mims/spatial/

• Plan to release new SA: 11/2009

Model Grid Satellite Data ComputationModel Grid Satellite Data Computation

Three steps in computing model grid satellite data

1. Create model grid shapeFile or raster file

2. Rasterize model grids

3. Compute model grid satellite value: average or total

3b.Project grid cells to Sat. data projection

3a. Project sat. points to grid cells

3a

3b

GOES Satellite DataGOES Satellite Data• GOES satellite data from National Space Science

and Technology Center (NSSTC) at Huntsville, ALhttp://satdas.nsstc.nasa.gov/index.html

• GOES data contain two types of hourly data:– GOES Imager 4km

• Cloud Albedo, Insolation, Surface Albedo, Cloud Top Pressure, Infrared Temperature

– GOES Sounder 10km• Cloud Top Pressure, Skin Temperature, Total Precipitable Water

– Data are in GRIB format

• Two script files– Compute GOES data on model grids and create a WRF-

ready NetCDF file (1 hour time step)– Convert NetCDF file into WRF data assimilation format

GOES Imager Surface AlbedoGOES Imager Surface Albedo

GOES Data East US 12km Domain

(%) (%)

GOES Sounder Skin TemperatureGOES Sounder Skin Temperature

GOES Data East US 12km Domain

OMI Level 2G and 3 Product ToolOMI Level 2G and 3 Product Tool

• Aura OMI daily global data from NASA GIOVANNI web site: http://disc.sci.gsfc.nasa.gov/giovanni/overview/instances_atmospheric.html– Level 3: ozone, aerosol, and cloud (0.25 or 1

degree resolution)

– Level 2G: ozone, aerosol, SO2 and NO2 (0.125 or 0.25 degree resolution)

– Data are in HDF4 format

• One script file to compute grid OMI data

OMI L2G NOOMI L2G NO22 Tropospheric Column Density Tropospheric Column Density

10^15 molec/cm^210^15 molec/cm^2

MODIS L2 Cloud ProductsMODIS L2 Cloud Products

• Each MODIS L2 cloud product file (one granule) contains:– 39 cloud variables in 5X5km or 1X1km arrays (at nadir) – five-minute time interval data for area ~1354X2030km – Data are in HDF4 format http://modis-atmos.gsfc.nasa.gov/MOD06_L2/index.htmlhttp://ladsweb.nascom.nasa.gov/data/search.html

• Two tools:– Compute model grid one cloud variable from one MODIS

L2 cloud product file– Compute model grid multiple cloud variables from given

period’s MODIS L2 cloud product files (under development)

NLCD and GLCC Evergreen ForestNLCD and GLCC Evergreen Forest

East US 12km Domain Texas 4km Domain Houston 1km Domain

US Eastern 12km Grid Domain: small differenceUS Eastern 12km Grid Domain: small difference

GLCC

Difference in NH4 aerosol concentration error for August 2006

NLCD MAE – GLCC MAE

Houston 4km ComparisonsNLCD versus USGS

Example of how the more finely resolved NLCD landuse represents areas along complex coastlines more accurately. The NLCD simulation represents diurnal temperature better than the 1-km base USGS. Landmask to the right is more refined when NLCD is used.

NLCD USGS

2-m Temperature Time Series Average of all sites around Houston

Mean absolute error (MAE) for NLCD simulation is 0.69 K and the USGS is 0.83 K. Mean BIAS is near zero for NLCD and -0.18 for USGS. Index of Agreement (IOA) is 0.94 versus 0.91.

2-m Temperature and 10-m Winds Aug 5, 2006 at 21 UT (4 PM LT)NLCD LU data

Fine scale effects of urban heat islandBay breeze from Galveston Bay

Houston area 1-km grid resolution WRF model simulation

ConclusionsConclusions

• WRF runs: – Preliminary comparisons show small

differences at 12-km grid resolution– Improved results from NLCD runs at 4-km and

1-km grid resolutions, particularly near coastlines

• CMAQ runs: – Largest difference is in the bi-directional NH3

surface flux because it is closely related to landuse, especially crops.

Future WorkFuture Work

• Run CMAQ for 4-km and 1-km Texas domains

• Compare results with WRF MODIS landuse data

• Use BELD4 from 2001 NLCD and MODIS land cover, FIA, and NASS for biogenic emission

• Develop tools to process and analyze A-Train satellite products (MODIS Aqua, Aura, PARASOL, CALIPSO, and CloudSAT) for aerosol and cloud interaction in air quality and regional climate chemistry research

AcknowledgementsAcknowledgements

• This project is funded by:– US EPA under the Contract No. EP-W-095-023,

“Operation of the Center for Community Air Quality Modeling and Analysis”.

– NASA ROSE Grants: UAH and NNX08AL28G

• We gratefully acknowledge the support of:– Arastoo Pour Biazar and Bill Crosson from the

National Space Science and Technology Center at UA Huntsville, AL

– Aijun Xiu, Uma Shankar from IE, UNC-Chapel Hill – William Benjey, Ellen Cooter, and Wyat Appel from

US EPA