Abstract
The impact of two cumulus convective schemes on the simulation of the precipitation over China is investigated using the Weather Research and Forecasting (WRF) model. Simulations for the period of 1982–2004 are performed at a horizontal resolution of 30 km and forced by NCEP Reanalysis II data. Results show precipitation simulated with the WRF model is quite sensitive to the choice of Kain–Fritsch and Grell cumulus schemes. Both the schemes have distinct skills in predicting the seasonal mean pattern, annual cycle and interannual variation in precipitation. The results show that the Kain–Fritsch scheme tends to overestimate the magnitude of the summer and annual mean precipitation over the main rain-belts, while the Grell scheme tends to underestimate these effects, particularly the simulation of the summer extreme precipitation. However, the Kain–Fritsch scheme is more skilful in capturing the seasonal mean pattern and annual cycle with higher spatial correlations in the main rain-belts. The Grell scheme shows some advantages for northern China and the Tibetan Plateau, especially in representing the interannual variation. The optimal ensemble approach is used to determine the best combination of the two schemes, with the results giving a better overall performance than the individual schemes alone in predicting summer precipitation. The temporal correlation coefficient of precipitation for the ensemble is significantly higher, while the root mean square error of extreme precipitation is reduced compared with the Kain–Fritsch and Grell results. This shows that the ensemble approach based on the optimal ensemble weight combines the advantages of the two cumulus schemes efficiently.
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