Evaluation of rain and cloud microphysical properties of monsoon depressions at a hyperlocal scale from simulations and observations

Abstract

The study investigates the characteristics of localized rainfall and associated convective processes using observations and model data sets for three different monsoon low-pressure systems that occurred over the Bay of Bengal and moved inland. The performance evaluation of five microphysics parameterization schemes (WSM6, WDM6, THOM, MORR and AA_THOM) are carried out for a location-specific rainfall event up to a lead time of 72�h. The model forecast results are validated against available observations over the study location (i.e. Argul, Odisha, 85.7�E 20.17�N). The results suggested that both MORR and THOM are relatively better performers among all schemes in terms of timing, evolution and intensity of hyperlocal rainfall events. The WDM6 has better performance in terms of predicting 2-m temperature. In general, the results suggest a robust and coherent relationship among moisture convergence, diabatic heating and rainfall peaks with better estimates in MORR. Further, it is noted that upper-level heating and lower level cooling pattern is distinct in all the cases and AA_THOM has the lowest heating rate as compared to others. It is also found that snow and ice hydrometeors are playing a key role in better rainfall estimates in MORR. It is demonstrated that factors (i.e., moisture convergence, vertical motion, hydrometeors and diabatic heating) highly modulated by choice of cloud microphysical parameterizations are dominantly influencing the localized rainfall and associated convection. In addition, the robust impact of cloud microphysical parameterization schemes in modulating the evolution, amount and distribution of hydrometeors and intensity of diabatic heating is evident. The findings of this study have also provided valuable clues about adopting a particular cloud microphysical parameterization for the hyperlocal forecast with special reference to moderate to heavy rainfall events. The results of the study have significant implications for operational forecasting agencies to optimize their model configuration for predicting location-specific heavy rainfall events, which are on the rise due to climate change scenarios over the Indian region. � 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.