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On some aspects of precipitation over the tropical Indian Ocean using satellite data

Pages 1717-1728 | Received 10 Feb 2004, Accepted 06 Oct 2004, Published online: 22 Feb 2007
 

Abstract

The annual and inter‐annual variability of precipitation over the tropical Indian Ocean is studied for the period 1979–1997, using satellite data from a variety of sensors. The Climate Prediction Center Merged Analysis Precipitation (CMAP), Microwave Sounding Unit (MSU) estimates of rainfall had better correlation with the island rainfall data than the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NRA) estimates. A comparison of the mean annual rainfall by different estimates (CMAP, MSU, NRA and GPCP (Global Precipitation Climatology Programme)) showed significant differences with the CMAP, GPCP and MSU estimates depicting maximum off the Indonesian Islands whilst the NRA exhibited maximum in the southern part of the Bay of Bengal and equatorial Indian Ocean. A study of the inter‐annual variability of the monsoon rainfall using the monthly CMAP data over the tropical Indian Ocean for different study areas, namely, Arabian Sea (AS), Bay of Bengal (BB), south Indian Ocean (SIO) and Indian Ocean (IO) showed significant differences during deficit years (1979, 1982, 1986 and 1987), excess monsoon years (1983 and 1988) and also during El Nino Southern Oscillation (ENSO) years (1982, 1987, 1992 and 1997). An analysis of the rainfall anomalies showed positive and negative anomalies in the north‐eastern Bay of Bengal during the summer season of deficit (1986) and excess (1988) monsoon years respectively, whilst the eastern equatorial Indian Ocean showed large positive and negative rainfall anomalies during the autumn season of El Niño years, 1987 (deficit monsoon) and 1997 (normal monsoon) respectively.

Acknowledgments

The GPCP data were obtained from the Global Precipitation Climatology Project of the World Data Center for Meteorology, Asheville, USA. Ferret software was used for the analysis of the various datasets. The authors are grateful to an anonymous reviewer for his useful suggestions in improving the manuscript. This is NIO contribution number 3911.

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