HR: 1330h
AN: H32C-0579    [PDF]
TI: Use of Satellite-Based Precipitation Observation in Improving the Parameterization of Canopy Hydrological Processes in Land Surface Models
AU: * Wang, D
EM: dagang.wang@uconn.edu
AF: Department of Civil & Environmental Engineering, University of Connecticut, 261 Glenbrook Road, Storrs, CT 06269 United States
AU: Wang, G
EM: gwang@engr.uconn.edu
AF: Department of Civil & Environmental Engineering, University of Connecticut, 261 Glenbrook Road, Storrs, CT 06269 United States
AU: Anagnostou, E
AF: Department of Civil & Environmental Engineering, University of Connecticut, 261 Glenbrook Road, Storrs, CT 06269 United States
AB: Precipitation demonstrates significant spatial variability at scales much smaller than the typical size of a climate model grid cell. Lack of representation for such sub-grid scale variability in climate models causes severe errors in the simulated water balance over vegetated land. Here we address this issue by incorporating satellite-based precipitation observation data into land surface models. We first derive statistics of precipitation climatology on the basis of over three years of rain retrievals from passive microwave sensors aboard TRMM (TMI), DMSP (SSM/I) and other platforms. This information is then used to improve the parameterization of canopy hydrological processes in the Community Land Model. We will demonstrate the impact of observation-enhanced parameterization using results from two tropical regions, the Amazon and the tropical Africa. The errors caused by the lack of representation of sub-grid rainfall variability are most severe in these two regions because of the dense vegetation canopy and the dominant convective processes occurring in these two major continental convective chimneys.
DE: 1833 Hydroclimatology
SC: Hydrology [H]
MN: 2003 Fall Meeting