Since the interaction between atmospheric synoptic eddy （SE） （2-8 days） activity and low-frequency （LF） （monthly） flow （referred to as SELF） plays an essential role in generating and maintaining dominant cli...Since the interaction between atmospheric synoptic eddy （SE） （2-8 days） activity and low-frequency （LF） （monthly） flow （referred to as SELF） plays an essential role in generating and maintaining dominant climate modes, an evaluation of the performance of BCC_CSMI.I（m） in simulating the SE feedback onto the LF flow is given in this paper. The model captures well the major spatial features of climatological eddy vorticity forcing, eddy-induced growth rate, and patterns of SELF feedback for the climate modes with large magnitudes in cold seasons and small magnitudes in warm seasons for both the Northern and Southern Hemisphere. As in observations, the eddy-induced growth rate and SELF feedback patterns in the model also show positive SE feedback. Overall, the relationships between SE and LF flow show that BCC_CSM1. l（m） satisfactorily captures the basic features of positive SE feedback, which demonstrates the simulation skill of the model for LF variability. Specifically, such an evaluation can help to find model biases of BCC_CSM1.1 （m） in simulating SE feedback, which will provide a reference for the model＇s application.展开更多
基金supported by the National Science Foundation of China(Grant No.41375062)the National Basic(973)Research Program of China(Grant No.2015 CB453203)+1 种基金a China Meteorological Administration(CMA)Special Project(Grant No.GYHY201406022)a CMA Key Project of Meteorological Prediction[Grant No.YBGJXM(2017)05]
文摘Since the interaction between atmospheric synoptic eddy （SE） （2-8 days） activity and low-frequency （LF） （monthly） flow （referred to as SELF） plays an essential role in generating and maintaining dominant climate modes, an evaluation of the performance of BCC_CSMI.I（m） in simulating the SE feedback onto the LF flow is given in this paper. The model captures well the major spatial features of climatological eddy vorticity forcing, eddy-induced growth rate, and patterns of SELF feedback for the climate modes with large magnitudes in cold seasons and small magnitudes in warm seasons for both the Northern and Southern Hemisphere. As in observations, the eddy-induced growth rate and SELF feedback patterns in the model also show positive SE feedback. Overall, the relationships between SE and LF flow show that BCC_CSM1. l（m） satisfactorily captures the basic features of positive SE feedback, which demonstrates the simulation skill of the model for LF variability. Specifically, such an evaluation can help to find model biases of BCC_CSM1.1 （m） in simulating SE feedback, which will provide a reference for the model＇s application.
