A regional atmosphere-ocean coupled model, RegCM3-POM, was developed by coupling the regional climate model （RegCM3） with the Princeton Ocean Model （POM）. The performance of RegCM3-POM in simulating a persistent s...A regional atmosphere-ocean coupled model, RegCM3-POM, was developed by coupling the regional climate model （RegCM3） with the Princeton Ocean Model （POM）. The performance of RegCM3-POM in simulating a persistent snow storm over southern China and the impact of the Madden Julian oscillation （MJO） on this persistent snow storm were investigated. Compared with the stand-alone RegCM3, the coupled model performed better at reproducing the spatial-temporal evolution and intensity of the precipitation episodes. The power spectral analysis indicated that the coupled model successfully captured the dominant period between 30 and 60 days in the precipitation field, leading to a notable improvement in simulating the magnitude of intraseasonal precipitation variation, and further in enhancing the intensity of the simulated precipitation. These improvements were mainly due to the well-simulated low-frequency oscillation center and its eastward propagation characteristics in each MJO phase by RegCM3-POM, which improved the simulations of MJO-related low-frequency vertical motions, water vapor transport, and the deep inversion layer that can directly influence the precipitation event and that further improved the simulated MJOprecipitation relationship. Analysis of the phase relationship between convection and SST indicated that RegCM3-POM exhibits a near-quadrature relation between the simulated convection and SST anomalies, which was consistent with the observations. However, such a near-quadrature relation was not as significant when the stand-alone RegCM3 was used. This difference indicated that the inherent coupled feedback process between the ocean and atmosphere in RegCM3-POM played an important part in reproducing the features of the MJO that accompanied the snow storm.展开更多
基金supported by grants from the National Basic Research Program of China (973 Program,Grant Nos.2012CB955901 and 2011CB952002)the National Science and Technology Support Program of China (Grant No.2009BAC51B03)the National Natural Science Foundation of China (Grant Nos. 41105044 and 41105045)
文摘A regional atmosphere-ocean coupled model, RegCM3-POM, was developed by coupling the regional climate model （RegCM3） with the Princeton Ocean Model （POM）. The performance of RegCM3-POM in simulating a persistent snow storm over southern China and the impact of the Madden Julian oscillation （MJO） on this persistent snow storm were investigated. Compared with the stand-alone RegCM3, the coupled model performed better at reproducing the spatial-temporal evolution and intensity of the precipitation episodes. The power spectral analysis indicated that the coupled model successfully captured the dominant period between 30 and 60 days in the precipitation field, leading to a notable improvement in simulating the magnitude of intraseasonal precipitation variation, and further in enhancing the intensity of the simulated precipitation. These improvements were mainly due to the well-simulated low-frequency oscillation center and its eastward propagation characteristics in each MJO phase by RegCM3-POM, which improved the simulations of MJO-related low-frequency vertical motions, water vapor transport, and the deep inversion layer that can directly influence the precipitation event and that further improved the simulated MJOprecipitation relationship. Analysis of the phase relationship between convection and SST indicated that RegCM3-POM exhibits a near-quadrature relation between the simulated convection and SST anomalies, which was consistent with the observations. However, such a near-quadrature relation was not as significant when the stand-alone RegCM3 was used. This difference indicated that the inherent coupled feedback process between the ocean and atmosphere in RegCM3-POM played an important part in reproducing the features of the MJO that accompanied the snow storm.
