Simulation of the 1998 East Asian Summer Monsoon using Purdue Regional Model

This study used the Purdue Regional Model to simulate the 1998 EASM to assess the model performance. The results indicated that the model was capable of simulating the overall characteristics of the 1998 EASM on the seasonal, intraseasonal, onset, and daily time scales. On the seasonal time scale, the model tended to produce more precipitation over the land and less precipitation over the ocean. This land-sea contrast in the model performance was consistent with the stronger-than-observed Pacific anticyclone in the simulation. It appears that the over simulated anticyclone was also found in other models, and is not a unique problem to the PRM. Future studies are needed to tackle this seemingly fundamental problem in several regional models. The model simulated the seasonal march of the EASM well, characterized by northward-propagating rain bands. Intraseasonal oscillation events propagating northward were also well reproduced. These results confirm that the model is capable of producing realistic sub-seasonal variability in the inner domain, once the proper lateral boundary forcing is provided. The model correctly simulated the onset timing and dramatic changes before and after the onset. However, the model incorrectly simulated the circulation and precipitation during the onset, because it failed to simulate the rapid development of a weak trough in the northern South China Sea. After the onset period, the model performance became reliable again. This indicates that the model is capable of fixing the existing large biases, with the proper lateral boundary forcing. This model was able to simulate the gross fluctuation in the regional-averaged daily precipitation, although it missed some extreme events that resulted in flooding in China. The incorrect simulation of these extreme events was partially responsible for the biases in the simulated seasonal precipitation. It is suggested that a regional model should be able to simulate the multi-scale features from the daily to seasonal time scales and their mutual interaction to correctly simulate the monthly and seasonal mean fields.