Monthly changes in the influence of the Arctic oscillation on surface air temperature over China

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 a...

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Bibliographic Details
Published in:Advances in Atmospheric Sciences
Main Authors: Huang, Jiayou, Tan, Benkui, Suo, Lingling, Hu, Yongyun
Other Authors: Huang, JY (reprint author), Peking Univ, Sch Phys, Dept Atmospher Sci, Beijing 100871, Peoples R China., Peking Univ, Sch Phys, Dept Atmospher Sci, Beijing 100871, Peoples R China.
Format: Journal/Newspaper
Language:English
Published: 大气科学进展英文版 2007
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Online Access:https://hdl.handle.net/20.500.11897/149037
https://doi.org/10.1007/s00376-007-0799-x
Description
Summary: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. Meteorology & Atmospheric Sciences SCI(E) 中国科学引文数据库(CSCD) 0 ARTICLE 5 799-807 24