Assessing the performance of cloud microphysical parameterization over the Indian region: Simulation of monsoon depressions and validation with INCOMPASS observations
This study validates the performance of four different cloud microphysics parameterization (CMP) with the INCOMPASS aircraft observations during monsoon 2016 and assesses its impact on simulations of two monsoon depressions (MDs) using the Weather Research and Forecasting (WRF) model. The simulations are carried out with a lead time up to 96 h. It is found that the Aerosol Aware Thompson (AAT) scheme showed better result in terms of wind and the WRF Double Moment Six Class microphysical scheme (WDM6) showed better correlations for temperature and dew point temperature compared to aircraft measurements. It is noted that the choice of CMP significantly impacts the key characteristics of the MDs such as rainfall, wind, temperature, hydrometeors and associated convective processes (e.g. moist static energy, moisture convergence). In general, CMPs have overestimated the rainfall compared to satellite estimates Tropical Rainfall Measuring Mission (TRMM), with WDM6 producing the least errors. Therefore, inter-comparisons of simulations of CMPs are carried out using WDM6 as the benchmark. Inter-comparison results suggest that there is a substantial reduction in rainfall for the Morrison due to drier lower and middle troposphere leading to subdued convective activity compared to others. Further, WDM6 has produced the least errors in the distribution of frozen hydrometer compared to ERA5. By examining the water budget, it is found that moisture convergence is the major driver for the rainfall, and the magnitude of moisture convergence is strongly affected by the choice of CMPs. Additionally, the local and advection terms of the moisture budget equation provide minimal contributions towards rainfall generation.