Divergent Transformation of Wet to Cold Bias on the Tibetan Plateau in Climate Models During Snow Season

Author:

Miao Xin12ORCID,Guo Weidong1ORCID,Hu Xinyun1,Wang Le1,Li Yizhuo1,Li Wenkai3ORCID

Affiliation:

1. School of Atmospheric Sciences Nanjing University Nanjing China

2. Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing China

3. School of Atmospheric Sciences Nanjing University of Information Science and Technology Nanjing China

Abstract

AbstractWet and cold biases on the Tibetan Plateau (TP) commonly exist in global and regional climate simulations. Previous studies have explored the possible causes of wet and cold biases and contributed to reducing these biases. However, the connection between wet and cold biases remains insufficiently addressed. Our research indicates that the TP wet bias converts into positive snow amount bias not continually but efficiently and concentratedly, under the control of snow phenology in different regions. Furthermore, the complex relationship between snow amount, snow coverage and surface albedo restricts the transformation of snow amount to surface albedo bias, and thus to cold bias. Our research highlights the spatio‐temporally divergent transformation of wet to cold bias on the TP during snow season, providing a novel perspective to understand the intrinsic connection between wet and cold biases and improve climate simulations on the TP.

Funder

National Natural Science Foundation of China

Nanjing University

Publisher

American Geophysical Union (AGU)

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