Changes in temperature extremes on the Tibetan Plateau and their attribution

• Published in: Environmental research letters Vol. 14; no. 12; pp. 124015 - 124026
• Main Authors: Yin, Hong, Sun, Ying, Donat, Markus G
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.12.2019
• Subjects: Anthropogenic factors; anthropogenic forcing; Climate models; detection and attribution; extreme temperatures; Fingerprinting; natural forcing; Tibetan Plateau; Tibetan Plateau; China
• ISSN: 1748-9326; 1748-9326
• DOI: 10.1088/1748-9326/ab503c

The Tibetan Plateau (TP) is the largest and highest upland on Earth. Warming on the TP is faster than that in surrounding areas. Evaluating our understanding of the causes behind these changes provides a test of tools used for projections of future climate in the region. In this study, we analyse the observed changes in twelve extreme temperature indices and compare them with model simulations based on the Coupled Model Intercomparison Project Phase 5 (CMIP5). An optimal fingerprinting method is used to perform detection and attribution analyses on the changes in absolute intensity, percentile-based frequency, fixed threshold exceedances of temperature extremes and diurnal temperature ranges in the central and eastern TP. The results show that during 1958-2017 the TP has experienced increasing intensity and frequency of warm extremes and decreasing intensity and frequency of cold extremes, with almost all these changes larger than those in China and East China. The detection results and attribution analyses show that the anthropogenic (ANT) signal can be robustly detected in the trends for all extreme indices on the TP, and the natural (NAT) signal in some cases, too. The attributable contribution from ANT is estimated to be much larger than that from NAT for most indices. The study also indicates that the CMIP5 models may underestimate the magnitude of warming in some temperature extremes, especially the indices related to cold extremes. This should be kept in mind when informing adaptation decisions on the TP with projections based on the same models.