Paper
5 May 2016 Evaluation of multi-satellite rainfall products over India during monsoon
Ashis K. Mitra, Satya Prakash, D. S. Pai, A. K. Srivastava
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Abstract
Simulation and prediction of Indian monsoon rainfall at scales from days-to-season is a challenging task for numerical modelling community worldwide. Gridded estimates of daily rainfall data are required for both land and oceanic regions for model validation, process studies and in turn for model development. Due to recent developments in satellite meteorology, it has become possible to produce realistic near real-time gridded rainfall datasets at operational basis by combining satellite estimates with rain gauge values and other available in-situ observations. Microwave and space based radar based estimates of rainfall has revolutionised the preparation of rainfall datasets especially for tropics. However, a variety of multi-satellite products are available over Indian monsoon region from a variety of sources. Popular products like TRMM TMPA3B42 (RT and V7), GsMaP, CPC/RFE, GPCP and GPM are available to end users in various space/time scales for applications and model validation. In this study, we show the representation and skill of monsoon rainfall from a variety of multi-satellite products over the Indian region. The bias and skill of multi-satellite rainfall are evaluated against gauge based observations. It was found that the TRMM based TMPA was one of the best dataset for Indian monsoon region. Attempt is made to compare the latest GPM based data with other products. The GPM based rainfall product is seen to be superior compared to TRMM.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ashis K. Mitra, Satya Prakash, D. S. Pai, and A. K. Srivastava "Evaluation of multi-satellite rainfall products over India during monsoon", Proc. SPIE 9876, Remote Sensing of the Atmosphere, Clouds, and Precipitation VI, 987607 (5 May 2016); https://doi.org/10.1117/12.2223311
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Cited by 1 scholarly publication.
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KEYWORDS
Data modeling

Satellites

Meteorology

Atmospheric modeling

Meteorological satellites

Process modeling

Ions

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