A simple method to forecast the frequency of depressions and cyclones over Bay of Bengal during summer monsoon season
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In this study, an attempt has been made to develop a simple multiple regression model to forecast the total number of depressions and cyclones (TNDC) over Bay of Bengal during summer monsoon (June–September) season using the data for the period, 1995–2016. Four potential predictors (zonal wind speed at 850 hPa in May and April SST in the North Australia–Indonesia region, 05°S–15°S; 120°E–160°E; March NINO 3.4 SST and geopotential height at 200 hPa in the region, 0°N–10°N; 80°E–100°E) have been identified to forecast TNDC. A remarkably high multiple correlation coefficient of 0.92 has been observed with the TNDC which explains 85% variability. The methodology has been tested for the recent 5 years (2012–2016) and found a good agreement between the observed and forecast values of TNDC except in 2015 in which the observed and predicted TNDC were 2 and 0, respectively. It is interesting to see high and significant correlations between the above predictors and the genesis potential parameter (GPP) during summer monsoon season. This GPP depends on the relative vorticity at 850 hPa, mid troposphere relative humidity, thermal instability between 850 and 500 hPa, and vertical wind shear between 200 and 850 hPa. It is inferred that the above predictors are influencing the environmental conditions over Bay of Bengal which, in turn, influencing the genesis of cyclones during summer monsoon season. The impact of ENSO (El-Nino-Southern Oscillation) and La-Nina in TNDC is examined and found that the vertical wind shear and relative vorticity are high and the GPP was almost double in ENSO compared with that in La-Nina which favoured high (low) TNDC under ENSO (La-Nina).
The authors thank Dr. S. W. A. Naqvi, Director, CSIR-NIO, Goa and Dr. V. S. N. Murty, Scientist-in-Charge, CSIR-NIO Regional centre, Visakhapatnam, for providing the facilities. They thank all the project teams of NOAA, Bureau of Meteorology, Australia, and IMD, New Delhi for making the data sets available on the Websites. Senior author (YS) would like to thank CSIR, New Delhi, for providing funds under Emeritus Scientist scheme. One of the authors K. Maneesha duly acknowledges financial support received from DST SERB under young scientist scheme. Thanks to both the reviewers for their valuable suggestions/comments which helped to improve the original version of the manuscript. This is NIO contribution number 5989.
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