Seasonal Modulation of MJO’s Impact on Precipitation in China and Its Dynamical-Statistical Downscaling Prediction
Based on the China regional grid precipitation dataset CN05.1 and EAR-Interim reanalysis data, the seasonal modulation of the impact of Madden-Julian Oscillation (MJO) on China’s precipitation anomaly is studied, and a dynamical-statistical downscaling model which focuses on extended-range precipitation forecast is established based on the MJO prediction by numerical model. The results show that the impact of MJO on precipitation anomaly is modulated by seasonal cycle obviously. When the MJO convection is active in tropical Indian Ocean, the above normal precipitation area advance northward along with the changes of seasons. When the MJO convection is active in the maritime continent, precipitation in eastern China and Tibet Plateau is abnormally less in autumn and winter, but this situation is gradually weakened or even reversed in spring and summer. The position and amplitude variation of MJO convection and basic state (especially the subtropical westerly jet) lead to different extra-tropical circulation responses, which are the main causes for these seasonal variations. The model verification suggests that the prediction skill of target pentad RMM index based on BCC_AGCM2.2 can extend to 18 days. In addition, a seasonal rol-ling MJO dynamical-statistical downscaling precipitation prediction model is established based on the forecasted RMM indices by dynamical model. The independent sample tests show that the dynamical-statistical model achieves higher skills in predicting the low-frequency precipitation anomaly than the direct output of BCC_AGCM2.2 in MJO high impact area during long lead time (10-20 d). The improvement is more obvious in the MJO active period. These findings could provide new thoughts for the MJO interpretation.