Role of cumulus parameterization schemes in simulating heavy rainfall episodes off the coast of Maharashtra state during 28 June–4 July 2007

Abstract

Indian summer monsoon gives on an average 250 cm of rainfall due to mesoscale/synoptic scale systems over west coast of India; now-a-days, MM5 model plays a very crucial role in simulating such heavy rainfall episodes like Mumbai (India) on 26 July 2005, which caused devastation through flash floods. The main aim of this study is to simulate such heavy rainfall episodes using three different cumulus parameterization schemes (CPS) namely Kain–Fritsch-1, Anthes–Kuo and Grell and to compare their relative merits in identifying the characteristics of mesoscale systems over 14 stations in coastal Maharashtra state during 28 June–4 July 2007. MM5 control experiment results are analysed for the fields of mean sea level pressure, wind, geopotential height at 850 hPa and rainfall with the above schemes. It is interesting to note that Kain–Fritsch-1 scheme simulates heavy rainfall amount of 48 cm for an observed rainfall of 51 cm in 24 h. The Grell scheme underestimates heavy rainfall episodes, while the Anthes–Kuo scheme is found to over predict rainfall on both temporal and spatial scales. The reason for better performance of KF-1 scheme may be due to inclusion of updrafts and downdrafts. Later the simulated rainfall quantities at 14 stations over study region are validated with both 3B42RT and observed rain gauge data of India Meteorological Department (IMD) and the results are promising. Finally, for the heavy rainfall prediction cases, the best threat score is at 0.25 mm threshold for three CPSs. Thus, this study is a breakthrough in pointing out that the KF-1 experiment has the best skill in predicting heavy rainfall episodes.