Assessment of WRF Model Parameter Sensitivity for High‐Intensity Precipitation Events During the Indian Summer Monsoon

Default values for many model parameters in Numerical Weather Prediction models are typically adopted based on theoretical or experimental investigations by scheme designers. Short-range forecasts substantially affected the specification of Research and Forecasting (WRF) model. The presence a multitude several output variables WRF renders appropriate parameter value identification quite challenging. objective current study is to reduce uncertainty outcomes through recognition that strongly influence performance using Global Sensitivity Analysis (GSA) method. Morris one-step-at-a-time (MOAT), GSA method, used identify sensitivities 23 chosen tunable corresponding seven physical parameterization schemes sensitivity measures (MOAT mean standard deviation) evaluated eleven variables, out which some surface meteorological remaining atmospheric simulated with different parameters. Twelve high-intensity four day precipitation events during Indian summer monsoon (ISM) years 2015, 2016, 2017 over core region India considered study. Six have high MOAT case almost all indicating these considerable effect outcome simulations. few noticeably small thus associated them has negligible performance. also presents insights into trends sensitivity.