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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
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