资源环境科技发展态势分析平台

The annual mean temperature on the Tibetan Plateau (TP) has strongly increased over the past few decades, with larger warming in winter than in summer. Whether this different amplitude of change between seasons has persisted over longer time-scales in the past remains poorly understood, limiting our understanding of the mechanisms responsible. Here, we apply multivariate regression analysis and ensemble empirical mode decomposition (EEMD) to decompose winter (T_DJF) and summer (T_JJA) temperature reconstructions over the 1718–2005 CE period on the southeastern TP to investigate similarities and differences between winter and summer temperature changes over multiple time-scales as well as the driving factors behind the seasonal differences. The results reveal that the T_DJF and T_JJA reconstructions were significantly correlated throughout the study period, with the magnitude of the T_DJF variations approximately three times greater than the T_JJA variations. When the two reconstructions were decomposed over multiple time-scales, it was found that the consistency between winter and summer temperature reconstructions only existed at inter-annual scale. Assessing the driving factors, the main contributions to the T_JJA and T_DJF changes at the inter-annual and inter-decadal scales appear to be mainly the El Niño–Southern Oscillation (ENSO). The Pacific Decadal Oscillation (PDO) contribution was important to T_JJA and T_DJF changes at multi-decadal scale. Furthermore, we found that orbital parameter and the Atlantic Multidecadal Oscillation (AMO) was a major contributor to the changes in T_JJA and T_DJF at centennial scale, respectively. Both the T_JJA and T_DJF have a significant long-term upward trend since c. 1850, mainly attributed to anthropogenic forcing. The detected similarities and differences between T_DJF and T_JJA at multiple time-scales provide new perspectives on the understanding the mechanisms behind climate change on the Tibetan Plateau and even East Asia.