Study land use effect on boundary layer meteorological characteristics

In order to predict local atmospheric conditions, it is required that meteorological modeling contains fine resolution land use coverage input. One of the common concerns was the limited resolution and accuracy of the critical input data such as the land use coverage data. For example, the current USGS 25-category Land Use (LU) data and Land Cover (LC) data linked with the MM5 meteorological modeling system is roughly at 1-km resolution data elements but somewhat out-dated (with the reference year 1990). One of the problems with the data is that it uses only one urban category that does not distinguish among the built-up urban, residential areas, planted trees, road and pavement areas. Recently, with the support of the Texas Forest Service (TFS), Global Environmental Management (GEM) has generated highly accurate land use and land cover datasets separately for the Houston and the surrounding eight county areas using the 30 meter resolution LANDSAT satellite imagery and ancillary datasets of varying spatial resolutions for the reference year 2000.

The primary goal of this research is to derive a better understanding of how land cover data differences affect boundary layer meteorological characteristics. The secondary goal is to demonstrate the effects of modified meteorological inputs on the changes of temperature, wind transport, PBL height structure and surface flux field that are essential factors for air quality simulation. To fully exploit the advantage of the new LULC dataset, a comprehensive land surface model (NOAH LSM) in MM5 mesoscale meteorological model was utilized. The change of the LULC data modifies the surface heat flux structure and local wind transport. The modification is consistent with the land use type characteristics. In addition, the detailed and accurate LULC map provides the realistic surface information for meteorological modeling. This study demonstrates that MM5 simulations can be improved with the use of high resolution LULC data. The present study will be used to support the understanding of the meteorological effects due to LULC changes on air quality modeling.