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Extremes in summer monsoon precipitation over India during 2001–2009 using CPC high-resolution data

Preethi, B., Revadekar, J. V., Munot, A. A.
International journal of remote sensing 2011 v.32 no.3 pp. 717-735
climate, climate change, climate models, correlation, data collection, drought, monsoon season, rain, remote sensing, satellites, seasonal variation, summer, India
High-resolution Climate Prediction Center (CPC) merged daily precipitation estimates based on satellite and raingauge data, available for the period 2001–2009, were analysed to determine the spatiotemporal variability of various indices of precipitation extremes during the summer monsoon season of the Indian subcontinent. Evaluation of the CPC 0.1° latitude × 0.1° longitude resolution merged precipitation data was carried out for the monsoon season by comparison with India Meteorological Department (IMD) 1° latitude × 1° longitude resolution gridded data for the common period of three years (2001, 2002 and 2003). Day-to-day variation in rainfall activity over the central Indian region obtained from these data sets was highly correlated, with a correlation coefficient of 0.62 (significant at the 0.1% level). The study showed that, over most of India, the mean and extremes in rainfall are captured well by the CPC data. However, the CPC data underestimate rainfall activities over the west coast and the northeastern part of the country, where heavy rainfall activity occurs throughout the season. Over the southeastern part of the subcontinent, where rainfall activity is lower, the CPC data overestimate the number of rainy days.The spatial and temporal variation of the summer monsoon rainfall (SMR) was examined by computing various indices of precipitation extremes using CPC data for all the available years (from 2001 to 2009). The spatial pattern of the rainy days and heavy precipitation indices follows the spatial pattern of the seasonal rainfall. Large interannual variability is observed in the spatial distribution of the indices of precipitation extremes. The precipitation indices over central India show low values during drought years compared to normal years (statistically significant at the 1% level). This indicates that a monsoon drought is associated with a drastic reduction in heavy rainfall activities compared to a normal monsoon year. The study shows that remote sensing plays an important role in monitoring climate change by providing continuous datasets at high resolution and also in studying the climate of data-sparse regions.