Evaluation of the WRF model for a heavy rainfall event over the complex mountainous topography of Mandi, India

Cumulus convection clouds can produce a lot of rain in a short duration of time over a constrained area. Severe natural disasters like cloudbursts are regularly experienced as heavy rainfall events (HREs) in the North-West Himalayan region and during the Indian Summer Monsoon Rainfall season (June–September). These events cause significant losses in terms of life, infrastructure, crops, etc. Therefore, it is crucial to understand and predict such events in order to minimize costs. This study simulates an HRE that occurred in Mandi, India, on August 7, 2015, for a period of 24 h using the Weather Research and Forecasting (WRF) model, a numerical weather prediction system. To study the key elements of HRE, various cloud microphysics (CMP) methods are subjected to a sensitivity analysis. Ten CMP systems (CAM, Goddard, Lin, Milbrandt-Yau, Morrison, Thompson, WDM6, WSM3, WSM5, and WSM6) are taken into account in the sensitivity analysis. To ascertain how well the WRF model with each scheme represents such extreme localized heavy rainfall episodes, the model output is examined. The Indian Monsoon Data Assimilation and Analysis (IMDAA) reanalysis and the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPMIMERG) Final run (V06B) satellite estimate datasets are used to create the observation proxies, which have horizontal resolutions of 12 km and 10 km, respectively. The output examination of the coarser and higher resolutions revealed that the WSM3 method performed very closely to the observation. Additionally, the bias in the simulated rainfall distributions of the Morrison and WSM3 schemes is evaluated for both domains; the WSM5 schemes showed the least error. Several meteorological variables that are connected to rainfall patterns, such as cloud fraction, maximum reflectivity, convective available potential energy, and wind flow field, are also thoroughly examined.