The Sensitivity of Extreme Rainfall Simulations to WRF Parameters During Two Intense Southwest Monsoon Events in the Philippines

Abstract

The Weather Research and Forecasting (WRF) model has numerous model parameters that significantly affect rainfall forecasts. However, the multitude of parameters makes it challenging to identify which of these are critical for rainfall forecasting and optimization. This study utilizes the Morris One-At-a-Time (MOAT) Global Sensitivity Analysis (GSA) to ascertain the sensitivity of the simulated rainfall and other key atmospheric variables to 23 tunable model parameters across seven physics schemes in the WRF model. The MOAT mean and standard deviation were used as sensitivity measures and calculated for two Tropical Cyclone (TC)-enhanced southwest monsoon events in August 2012 and 2013 that resulted in catastrophic flooding over Metro Manila, Philippines. Results show that of the 23 model parameters, the ones more critically important to simulating rainfall are parameters that are related to cumulus schemes such as the multiplier for downdraft mass flux rate (P3), multiplier for entrainment mass flux rate (P4), starting height of downdraft over updraft source layer (P4), and mean consumption time of convective available potential energy (P6). To investigate the optimum parameter for the simulation of rainfall for each of the two events, the root mean square error (RMSE) is computed between the simulated rainfall over Metro Manila and observed data from the Global Satellite Mapping of Precipitation (GSMaP). The best performing set of parameters was able to reduce the RMSE of rainfall over Metro Manila by about 42% and 27% for the 2012 and 2013 enhanced monsoon events, respectively, relative to the default runs. For the first time, this study provides insight into which model parameters in the WRF model are critically important to the simulation of enhanced monsoon events. The results of this study may serve as a basis for future optimization studies of extreme weather events over the Philippines.