Effect of the better representation of the cloud ice-nucleation in WRF microphysics schemes: A case study of a severe storm in India

Abstract

In the present study, the Weather Research and Forecasting (WRF) model was used to simulate the features associated with a severe thunderstorm over India while examining the sensitivity of the simulation to three microphysical (MP) schemes (WDM6, Thompson and Morrison). The model simulated results (e.g., surface temperature, relative humidity, pressure, reflectivity and rainfall) for all sensitivity experiments are compared with observations (e.g., AWS, TRMM and DWR). There are major differences in the simulations of the thunderstorm among the MP schemes. The Morrison scheme simulates CAPE, surface properties, wind speed, vertical velocity, reflectivity and precipitation reasonably well, compared to other MP schemes, though there are some uncertainties. Therefore, an attempt is made to improve the simulation through modifications in the Morrison scheme. Different heterogeneous ice nucleation formulations have been tested into the Morrison double-moment bulk cloud MP scheme. We hypothesize that the improvement in cloud ice generation and its subsequent influence in cloud microphysics and dynamics through latent heat release may eventually lead to an improvement in thunderstorm simulation. The results demonstrate that the modification in the microphysical scheme better reproduces CAPE, wind speed, maximum reflectivity, vertical velocity and cloud hydrometeors (ice and mixed-phase processes) than the default Morrison and other schemes and compared to observations. The modified MP-scheme produces greater latent heating due to deposition in the upper troposphere and gives rise to increased updraft. This seems to be one of the most responsible processes that enhance the intensity of the storm compared to existing microphysical schemes. This study therefore provides a framework for the improvement of thunderstorm simulation through the modification of the cloud ice parameterization of the model.