Incorporation of MODIS landcover data to improve land surface parameterization in the COAMPS numerical weather prediction model

被引：0

作者：

Anantharaj, VG ^{[1
]}

Fitzpatrick, PJ ^{[1
]}

King, RL ^{[1
]}

Wasson, L ^{[1
]}

机构：

[1] Mississippi State Univ, GeoResources Inst, Mississippi State, MS 39762 USA

来源：

IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET | 2004年

关键词：

COAMPS; MODIS; landuse; landcover; land surface parameterization;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

The vegetation and soil properties at the land surface exert significant influence mer short-term weather forecasts of numerical weather prediction (NWP) models. The Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) derives the necessary land surface properties from the USGS 1-km global land-use/land-cover (LULC) database, which is based on historical AVHRR data. A methodology has been developed to incorporate the LULC data, derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, into the COAMPS model, running on nested domains - centered over Mississippi Gulf Coast.

引用

页码：4095 / 4098

页数：4

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