Abstract

An accurate seasonal prediction of Indian summer monsoon rainfall (ISMR) is intriguing as well as the most challenging job for monsoon meteorologists. As there is a cause and effect relationship between clouds and precipitation, the modulation of cloud formation in a dynamical model affects profoundly on ISMR. It has already been established that the critical relative humidity (CRH) plays a crucial role on the realistic cloud formation in a general circulation model. Hence, it may be hypothesized that the proper choice of CRH can be instrumental in driving the large scale Indian monsoon by modulating the cloud formation in a global climate model. An endeavor has been made for the first time to test the above hypothesis on the NCEP-CFSv2 model in the perspective of seasonal prediction of ISMR by modifying the CRH profile. The model sensitivity experiments have been carried out for two different CRH profiles along with the existing profile during the normal (2003) and deficient (2009) monsoon years. First profile is the constant CRH following the existing one but with increased magnitude and the second one is the variable CRH at different cloud levels based on the observations and MERRA reanalysis. The ensemble mean of model runs for four initial conditions of each year has revealed that the variable CRH profile in CFSv2 represents seasonal ISMR and its variability best among the three CRH experiments linking with the thermodynamical and dynamical parameters like precipitable water, tropospheric temperature and its gradient, cloud structure and radiation, water vapour flux, systematic error energy with its nonlinear error growth and the length of the rainy seasons during the contrasting years. It has also been shown that the improved depiction of seasonal ISMR has been achieved without disturbing much the forecast biases at other global tropical regions. The indigenous part of this paper is that the CRH modification can play a seminal role in modulating the large scale system like Indian monsoon by representing the realistic variability of cloud formation in CFSv2 and that proves the hypothesis. This work creates an avenue for further development of CFSv2 approaching towards an accurate seasonal forecast of ISMR.

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