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Analysis of the Characteristics of Non-stationary Spatio-temporal
Variations of Future Temperature in the Qinghai-Xizang
Plateau Based on EOF-EEMD Combination
1, 2
1, 2
ZHANG Xue , DONG Xiaohua 1, 2* , MA Yaoming 3, 4, 5, 6, 7, 8* , GONG Chengqi ,
HU Xueer , CHEN Ling , SU Zhongbo 9
1, 2
1, 2
(1. College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, Hubei, China;
2. Engineering Research Center of Eco-environment in Three Gorges Reservoir Region,
China Three Gorges University, Yichang 443002, Hubei, China;
3. Land-Atmosphere Interaction and its Climatic Effects Group, State Key Laboratory of Tibetan Plateau Earth System, Environment
and Resources(TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China;
4. College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China;
5. College of Atmospheric Science, Lanzhou University, Lanzhou 730000, Gansu, China;
6. National Observation and Research Station for Qomolongma Special Atmospheric Processes and
Environmental Changes, Dingri 858200, Xizang, China;
7. Kathmandu Center of Research and Education, Chinese Academy of Sciences, Beijing 100101, China;
8. China-Pakistan Joint Research Center on Earth Sciences, Chinese Academy of Sciences, Islamabad 45320, Pakistan;
9. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, The Netherlands, 7500 AE)
Abstract: Using effective bias correction methods and transforming non-stationary data to stationary can en‐
hance the scientific accuracy of temperature analysis, allowing for a deeper understanding of its temporal and
spatial distribution characteristics and evolution patterns. This study utilizes the ERA5_Land near-surface (2 m)
monthly mean temperature observation dataset covering the period from 1970 to 2014. Initially, it employs the
Taylor diagram, Taylor index, interannual variability skill score, and rank scoring method to evaluate and select

