Monthly changes in the influence of the Arctic Oscillation on surface air temperature over China
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Partial Least Squares Regression (PLSR) is used to study monthly changes in the influence of the Arctic Oscillation (AO) on spring, summer and autumn air temperature over China with the January 500 hPa geopotential height data from 1951 to 2004 and monthly temperature data from January to November at 160 stations in China. Several AO indices have been defined with the 500-hPa geopotential data and the index defined as the first principal component of the normalized geopotential data is best to be used to study the influence of the AO on SAT (surface air temperature) in China. There are three modes through which the AO in winter influences SAT in China. The influence of the AO on SAT in China changes monthly and is stronger in spring and summer than in autumn. The main influenced regions are Northeast China and the Changjiang River drainage area.
Key wordsarctic oscillation temperature field monthly changes partial least squares regression
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