87th AMS Annual Meeting

Tuesday, 16 January 2007: 9:15 AM
Validation Results for Daily Precipitation Estimates Over Del Plata Basin
211 (Henry B. Gonzalez Convention Center)
Daniel A. Vila, Earth System Science Interdisciplinary Center, College Park, MD; and E. H. Berbery and R. R. Ferraro
Rainfall is one of the most important atmospheric variables of the hydrological cycle. However, due to the high temporal and spatial variability of this parameter, the use of conventional methods (rain gauge measurements) makes your monitoring very difficult. Particularly over large regions in South America, where the scarcity of real time rain gauge data and the existence of large unpopulated regions, make satellite based approaches an excellent tool to investigate the spatial distribution of precipitation. To optimally use these data for forecasting and research applications, it is important to evaluate the errors in satellite-based rainfall estimates.

In 2003 the International Precipitation Working Group (IPWG) began a project to validate operational and semi-operational satellite rainfall estimates over Australia and the US in near real time. A European verification page was added in 2004. On June 2006, the Cooperative Institute of Climate Studies (CICS) at the University of Maryland started a new validation page devoted to the South American region (http://cics.umd.edu/~dvila/web/SatRainVal/dailyval.html).

This study is focused on the results of large-scale validation of daily rainfall estimates over Del Plata basin for 2005. The retrieval of nine different satellite precipitation estimates, based on IR, passive MW and merging techniques, are compared against daily accumulations on 0.25 x 0.25 areas (accumulation period starting at 12:00Z) using a gauge analysis for this region. A masking scheme was applied to the resulting grids based on a minimum distance threshold to the nearest gauge. For comparison purposes, 1-day forecasts from a limited number global and regional numerical weather prediction models are also included in the statistical analysis.

Supplementary URL: