摘要
By using the NCAR CCM1 model, we have designed six sensitive experiments, which are increased and decreased SST (sea surface temperature) by 1℃ each in the SCS (South China Sea) and in the West Pacific warm pool, increased and decreased SST by 1℃ in the warm pool with increased SST by 1℃ in the SCS. All experiments are integrated from April to July. Comparing with the control experiment, we have analyzed the anomalies of the wind field at the upper and lower layers, the anomalies of the seasonal variability of the monsoon and precipitation for each experiment. In the result, we have found that the SST anomaly (SSTA) in the SCS greatly affects the seasonal variability of the SCS monsoon and precipitation in China, especially during the cold period of SST in the SCS. The impact of SSTA in the warm pool on SCS monsoon is also found. but is weak as compared to the effect of SST anomaly in the SCS. Besides, its impact on rainfall in China is uncertain.
By using the NCAR CCM1 model, we have designed six sensitive experiments, which are increased and decreased SST (sea surface temperature) by 1℃ each in the SCS (South China Sea) and in the West Pacific warm pool, increased and decreased SST by 1℃ in the warm pool with increased SST by 1℃ in the SCS. All experiments are integrated from April to July. Comparing with the control experiment, we have analyzed the anomalies of the wind field at the upper and lower layers, the anomalies of the seasonal variability of the monsoon and precipitation for each experiment. In the result, we have found that the SST anomaly (SSTA) in the SCS greatly affects the seasonal variability of the SCS monsoon and precipitation in China, especially during the cold period of SST in the SCS. The impact of SSTA in the warm pool on SCS monsoon is also found. but is weak as compared to the effect of SST anomaly in the SCS. Besides, its impact on rainfall in China is uncertain.
基金
The paper is jointly supported by the National Natural Science Foundation of China under the Program of 49375245
by the Monsoon Fund of China Meteorological Administration
