Local and urban scale modeling - Air Pollution Modeling and Its Application - page 2

1.1 Impact of High Resolution Land-Use Data
in Meteorology and Air Quality Modeling Systems

Limei Ran 1 , Jonathan Pleim 2 , and Robert Gilliam 2

1

Institute for the Environment, University of North Carolina, Chapel Hill, NC, USA
2
United States Environmental Protection Agency, Atmospheric Model Development Branch,
Atmospheric Modeling and Analysis Division USEPA/ORD/NERL Research Triangle Park,
NC 27711

Abstract Accurate land use information is important in meteorology for land
surface exchanges, in emission modeling for emission spatial allocation, and in air
quality modeling for chemical surface fluxes. Currently, meteorology, emission, and
air quality models often use outdated USGS Global Land Cover Characterization
(GLCC) 30-s (around 1 km) resolution land cover data. With the release of the
2001 National Land Cover Data (NLCD) products at 30 m cell resolution for the
United States and 2001 NASA Moderate Resolution Imaging Spectroradiometer
(MODIS) land cover data at 1 km cell resolution for the globe, meteorology and
air quality modelers want to use these more current and accurate land cover data
sets. In the Spatial Allocator, C++ programs were developed with the Geospatial
Data Abstraction Library (GDAL) to compute modeling domain gridded land
cover information based on input image data of the 2001 NLCD and MODIS land
cover data. The programs output gridded fractional coverage of each land category
for use in the Weather Research and Forecast (WRF) and Community Multiscale
Air Quality (CMAQ) models. The land use data are used to specify vegetation and
surface related parameters that are needed in land surface models (LSM) and dry
deposition models. We have incorporated the gridded 2001 NLCD and MODIS

land cover data in the WRF and CMAQ modeling for the CONUS and east US
12 km resolution domains. Preliminary WRF results show slight improvement and

CMAQ runs show largest difference in the bi-directional NH 3 surface flux. We
believe that these new land cover data should have more effects on both meteoro-
logical and air quality model simulations for higher resolution modeling.

Keywords NLCD, MODIS, WRF, CMAQ, LSM, landuse, land surface model,
meteorology model, air quality model