Use of vegetation properties from EOS observations for land-climate modeling in East Africa

Abstract

Land use/cover change has been recognized as a key component in global climate change. Information on land surface biophysical properties and climatic variables based on in situ data fail to resolve the fine-scale variability that exists in many parts of the world, including East Africa. In this study, we used the NASA's Earth Observing System (EOS) products to improve the representation of the land surface in a regional climate model as well as assess the model performance. The Moderate Resolution Imaging Spectroradiometer (MODIS) data of leaf area index (LAI) and vegetation fractional cover (VFC) were directly incorporated in the Regional Atmospheric Modeling System (RAMS). The model was validated in terms of the land surface temperature (LST), utilizing the MODIS LST data from both Terra and Aqua satellites. Compared with the built-in land surface, the ingested MODIS LAI and VFC greatly improved the spatial and temporal dynamics of vegetation in East Africa. Three experiments were carried out for the year of 2003 to test the impacts of land surface conditions. The results showed that the spatial, seasonal, and diurnal characteristics of the RAMS simulated LST were improved because of MODIS LAI and VFC. Specifically, the Intertropical Convergence Zone (ITCZ)-related migration, bimodal temporal variation, and monthly averaged diurnal cycles of LST were more realistically reproduced. The need to realistically represent the spatial and temporal distribution of vegetation is thus highlighted, and the value of the EOS observations for the land-climate modeling is demonstrated. Copyright 2008 by the American Geophysical Union.