Improving Optimal Fingerprinting Methods Requires a Viewpoint beyond Statistical Science  

作　　者：Jianhua LU 

机构地区：[1]School of Atmospheric Sciences,Sun Yat-sen University(SYSU),&Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China

出　　处：《Advances in Atmospheric Sciences》2024年第10期1869-1872,共4页大气科学进展（英文版）

基　　金：support from the National Natural Science Foundation of China(Grant No.42175070)。

摘　　要：While being successful in the detection and attribution of climate change,the optimal fingerprinting method(OFM)may have some limitations from a physics-and-dynamics-based viewpoint.Here,an analysis is made on the linearity,noninteraction,and stationary-variability assumptions adopted by OFM.It is suggested that furthering OFM needs a viewpoint beyond statistical science,and the method should be combined with theoretical tools in the dynamics and physics of the Earth system,so as to be applied for the detection and attribution of nonlinear climate change including tipping elements within the Earth system.

关 键 词：optimal fingerprinting detection and attribution NONLINEARITY interaction between climate change and variability non-stationary climate variability 

分 类 号：P467[天文地球—大气科学及气象学]