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K. Krishna Kumar, K. Rupa Kumar, and G. B. Pant


The location of the 500-hPa ridge axis during April over India is one of the most important long-range predictors for the summer monsoon rainfall. This paper presents a comprehensive analysis on its space-time variability during the premonsoon season and its relation with the monsoon rainfall. Data on the daily latitudinal locations of the 500-hPa ridge axis along three longitudes during March, April, and May, as well as all-India rainfall and subdivisional monsoon rainfall for the period 1967–90, have been used.

The analysis involves correlations between the running means of the premonsoon ridge locations over windows of 15, 21, and 31 days, and the subsequent monsoon rainfall. The ridge location in March shows negative correlation with the all-India summer monsoon rainfall, while that in April shows positive correlation. The anticorrelation of the March ridge was more dominant with the monsoon rainfall of the peninsular India, while the positive correlation of the April ridge was more dominant with the monsoon rainfall of northern India. Regression equations for the prediction of the monsoon rainfall have also been developed.

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B. Parthasarathy, K. Rupa Kumar, and A. A. Munot


Detailed correlation analysis of the all-India monsoon rainfall and mean sea-level seasonal pressure at Bombay (19°N, 73°E) up to three lags on either side of the monsoon wren during the last 30 years (1951–80) indicates a systematic relationship. The winter-to-premonsoon (March, April, May–Deceinber, January, February; MAM–DJF) seasonal pressure tendency at Bombay shows a correlation coefficient (CC) of −0.70 (significant at 0.1% level) with the Indian monsoon rainfall.

Further examination of this relationship over a long period of 144 years (1847–1990), using sliding correlation analysis, reveals some interesting features. The sliding CCs were positive before 1870, negative during 1871–1900, positive in the years 1901–40, and again negative later on, showing systematic turning points around the years 1870, 1900, and 1940. In light of other corroborative evidence, these climatic regimes can be identified as “meridional monsoon” periods during 1871–1900 and after 1940, and as “zonal monsoon” periods before 1870 and during 1901–40, similar to the observation of Fu and Fletcher. It is also observed that the relationship between Bombay pressure and Indian monsoon rainfall becomes dominant when the ENSO variance in Bombay pressure is high and falls apart when the ENSO variance is small.

The paper contains a listing of the long homogeneous data series on all-India monsoon rainfall and monthly MSL pressure at Bombay for the period 1847–1990.

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D. B. Stephenson, K. Rupa Kumar, F. J. Doblas-Reyes, J-F. Royer, F. Chauvin, and S. Pezzulli


The Indian summer monsoon rainfall is the net result of an ensemble of synoptic disturbances, many of which are extremely intense. Sporadic systems often bring extreme amounts of rain over only a few days, which can have sizable impacts on the estimated seasonal mean rainfall. The statistics of these outlier events are presented both for observed and model-simulated daily rainfall for the summers of 1986 to 1989. The extreme events cause the wet-day probability distribution of daily rainfall to be far from Gaussian, especially along the coastal regions of eastern and northwestern India. The gamma and Weibull distributions provide good fits to the wet-day rainfall distribution, whereas the lognormal distribution is too skewed. The impact of extreme events on estimates of space and time averages can be reduced by nonlinearly transforming the daily rainfall amounts. The square root transformation is shown to improve the predictability of ensemble forecasts of the mean Indian rainfall for June 1986–89.

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