A performance evaluation of various physics schemes on the predictions of precipitation and temperature over the Tibet Autonomous Region of China

The WRF model has become an important tool for numerical weather prediction. However, the mechanism of different physics schemes in WRF for air temperature and precipitation predictions over the Tibet Autonomous Region of China is still uncertain. In this study, WRF experiments with distinct physics schemes are conducted on a rainfall event that occurred during the last two days of June 2021 in Tibet. The predictions of air temperature and precipitation from WRF are compared against observational data and the ECMWF forecast, and explained by the land-atmosphere interaction. Results confirm that WRF produces more accurate temperature and precipitation predictions than the widely used ECMWF forecast product. These analyses also reveal large differences in WRF performance in predicting the intensity and spatial patterns of rainfall and diurnal variations of temperature due to the use of different physics schemes. Among the selected physics schemes, the RRTMG scheme yields the highest accuracy forecasts for light rain to rainstorms. The other schemes give an ambiguous performance in relation to predicting various rainfall intensities. In addition, WRF applying the Noah-MP, Mellor-Yamada-Janjic, and RRTMG schemes contributes to alleviating the predicted cold air bias from the ECMWF and WRF control experiment, which is closely related to the surface net radiation overprediction, near-surface energy accumulation and the relatively accurate estimates of ground temperature. The RRTMG scheme shows the strongest capacity for predictions of diurnal variation of temperature, with the lowest RMSE of 3.18 °C and mean error of 2.05 °C. These values are 1.69 °C and 2.03 °C lower, respectively, compared to the ECMWF. The capacity of different schemes to relieve the mode's cold bias is ranked from high to low as RRTMG > Mellor-Yamada-Janjic > Grell 3D/Noah-MP.