Evaluation of WRF Microphysics Schemes for Precipitation Forecasting in an Arid Region: A Case Study Over Kuwait

Abstract

In this study was investigated three different microphysics schemes on the rainfall patterns over Kuwait on 02 January 2022. The primary objective is to improve precipitation predictions using the Weather Research and Forecasting (WRF) high resolution 4 km model, which has been dynamically downscaled from the Community Climate Model version 4 (CCM4). The performance of three selected microphysics schemes—Lin, WSM6, and Thompson was evaluated using the ERA5 reanalysis dataset. ERA5 has been previously validated in this region and has consistently provided reliable results, making it a suitable dataset for such studies. Three numerical simulations were conducted using the WRF model, each incorporating one of the three microphysics schemes. The simulations were assessed by comparing the model outputs against the ERA5 data to determine the accuracy of the rainfall forecasts. The results revealed that the WRF Single-Moment 6-class microphysics scheme (WSM6) outperformed the other microphysics schemes, including Lin and Thompson, in forecasting rainfall patterns during the storm. The Lin scheme was found to be the least reliable, providing less accurate rainfall predictions compared to the Thompson and WSM6 schemes. This study highlights the critical role of selecting appropriate microphysics schemes for accurate precipitation prediction, particularly in extreme weather events like the 2022 storm in Kuwait. The findings suggest that the WSM6 scheme is a more effective choice for rainfall forecasting in this region, whereas the Lin scheme may not be as suitable for this particular type of storm event. Further research is recommended to extend this analysis to different regions and storms for more comprehensive results.