Research Of Relationship Between Winter Air Temperature In Northeast China And SST Anomaly Mode

By using the monthly mean data at 92 observational stations of China North East, and NCAR/NCEP reanalysis data, HadISST OI monthly mean data, application of the generalized equilibrium feedback assessment (GEFA) method, maximum covariance analysis (MCA), combined with the methods of EOF analysis, correlation analysis and composite analysis to explore the different influence of SST on the winter temperature in North East China, and analyze its possible mechanism. The main conclusions are the following:(1) The winter air temperature same mode in Northweast China is closely related to the corresponding sea surface temperature anomalies (SSTA) and its related atmospheric circulation anomalies. The low or warming air temperature mode exhibit that the lower or high temperature trend are greater in northern Northeast China, which are significantly forced by the Tropical Atlantic SSTAs in "plus-minus-plus" three-pole mode (TA3) and the North Atlantic SSTAs in "plus-minus-plus" three-pole mode (NA3). Under the influences of Tropical Atlantic SSTAs, through the "plus-minus-plus" wave train in the Northern Hemisphere the East Asia major trough is moved to the Lake Baikal eventually facilitates the lower temperature than normal in Northeast China. The direct response to the North Atlantic SSTAs in "plus-minus-plus" three-pole mode (NA3) shows that the East Asia major trough is weaken even vanishes and the polar cold air had been entrenched, resulting in Northeast China warmer than normal.(2) According to the analysis of the temperatures of Northeast China in 2000/2001, it is found that the 2000/2001 winter temperature anomaly is significantly influenced by the North Atlantic SSTA mode NA3, warm tropical northwest Indian ocean mode TI1 and warm tropical northwest Indian ocean mode TI2.(3) when the winter air temperature lags North Atlantic SSTA 2 months, the winter temperature air in the same year would be influenced and could be a forecasting factor in the climate prediction.