Statistical verification of numerical weather prediction models for quantitative precipitation forecast

In this study, the potential of two numerical weather prediction (NWP) models in quantitative precipitation forecasting over a tropical region is examined. The precipitation forecasts produced from the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) models are statistically verified with the observed rain in Kelantan River Basin, Malaysia. The statistical verification indicates that the root mean squared error (RMSE) increases for higher rainfall rate, though the models have performed quite satisfactorily in certain cases during heavy rainfalls that cause flood. It is also shown that the longer the rainfall forecast duration, the higher the probability of detection (POD) and the lesser probability to be the false alarm ratio (FAR).