文章基本信息

标题：Estimation of Precipitation over India and Associated Oceanic Regions by Combined Use of Gauge andMulti-satellite Sensor Observations at Fine Scale
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作者：Anoop Misra ; Rakesh GAIROLA ; Akiyo YATAGAP 等
期刊名称：Global Environmental Research
印刷版ISSN：1343-8808
出版年度：2011
卷号：15
期号：2
语种：English
出版社：国际环境研究会
摘要：The present study focuses on estimating rainfall (daily accumulated) using gauge and satellite observa- tions over land and ocean regions of South Asia (30°S-50°N, 40°E-120°E) at a 0.25° × 0.25° spatial resolution for the period 2007-2010 (four years). The study utilizes observations from rain gauges, the Special Sensor Microwave/Imager (SSM/I) onboard the Defense Meteorological Satellite Program (DMSP), Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) and geo-stationary satellite Meteosat from Eumetsat. The present study makes use of rainfall estimates by synergistic use of multi-satellite sensors using Meteosat Infrared and Water Vapor absorption channels and PR observations (Mishra et al., 2009b, 2010) and SSM/I-derived microwave estimates using a regional scattering index developed by Mishra et al., (2009a). The pixels over the land portion of the study area are filled with available rain gauge observations over the southern part (around 14°N and 78°E) of the study area, which has a dense network of Automatic Weather Station (AWS) rain gauges operated by the Indian Space Research Organization (ISRO). Pixels over the other part of the study area are filled with available microwave observations first, but if microwave observations are unavailable then these pixels are filled with microwave-calibrated infrared observations over the land and oceanic regions of the study area. The precipitation estimates from the present approach are vali- dated against rain gauge observations and other available standard rainfall products like TRMM-3B42V6 and Global Precipitation Climatology Project (GPCP) version 2.1. The validation results show that the present approach of precipitation estimation is able to estimate rainfall with high accuracy.