85th AMS Annual Meeting

Thursday, 13 January 2005: 4:46 PM
Land Surface Water Cycles Observed with Satellite Sensors(Formerly paper j6.6)
S. V. Nghiem, JPL and California Institute of Technology, Pasadena, CA; and E. G. Njoku, G. R. Brakenridge, Y. Kim, and G. Neumann
Poster PDF (1.8 MB)
Satellite data acquired by multiple earth-orbiting sensors are used to detect and monitor surface water changes on land. These sensors include the NASA SeaWinds Scatterometer on the QuikSCAT satellite (QSCAT), the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and the Moderate Resolution Imaging Spectroradiometer (MODIS). QSCAT can detect precipitation water on land surfaces with nearly daily coverage over continental scales. Wet surface maps derived from QSCAT data compare well in timing and in spatial pattern with surface measurements of precipitation. QSCAT results can also serve as an independent dataset for the inter-comparison of NLDAS (North American Land Data Assimilation System) and GLDAS (Global Land Data Assimilation System) results. QSCAT summer results (mid-May to mid-September) in the last half-decade over the conterminous United States reveal a highly recurrent precipitation pattern over the Midwest with the wettest condition in year 2000 and a severe drought in 2003. In the New England states, summer 2001 experienced the most frequent precipitation-induced surface wetness. QSCAT clearly delineates wet surface areas caused by Hurricane Ivan (September 2004) in southwestern states (Alabama, Mississippi, Georgia, and Florida) and by recent storms (October 2004) in western states (California, Oregon, and Washington). Patterns of surface soil moisture measured by AMSR-E and QSCAT wetness maps are consistent with surface weather analysis. QSCAT results for wetland monitoring over the lower Mississippi floodplain in 2002 show a seasonal expansion of wet surface area in the winter months and a reduction in summer months. The water cycle over this region in 2002 exhibits a clear pattern with expanded surface water, probably coupled with wetter soils, that is correlated with and leading river discharge increases by as much as 2 months. Finally, the combination of QSCAT, AMSR-E, and MODIS data collected over pre-selected river gaging reaches reveals the utility of satellite sensors to detect and monitor floods. Monsoon flood cycles are observed in India with multi-year times-series satellite data. Whereas much research is necessary to fully understand and calibrate satellite data to determine accurate hydrologic parameters, surface water mapping results have found useful applications in flood/drought monitoring and mitigation. Data from possible future satellite missions such as the US HYDROS, the Canadian RADARSAT-2, the Japanese ALOS, and the Indian Oceansat-2 (carrying QSCAT-like scatterometer, launch in 2006) will be useful for long-term scientific studies of land surface water cycles and for practical applications in flood/drought monitoring.

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