Change and teleconnections of climate on the Tibetan Plateau

Exploring the change and teleconnection of climate on the Tibetan Plateau is of utmost importance to understand global climate change. However, it remains further work because of two aspects: (1) The sparse and short observation provides limited information of climate change. (2) The teleconnection analysis mostly ignores the combined effects of multiple atmospheric circulation indices. This study used a climate dataset with grid size of 0.5 & PRIME; for the period of 1901-2017 to analyze the spatiotemporal characteristics of precipitation and temperature on the Tibetan Plateau. Further, we employed the multivariate wavelet coherence to investigate the combined effects of multiple circulation indices (Atlantic Multidecadal Oscillation-AMO, El Nino-Southern Oscillation-ENSO, Indian Ocean Dipole Index-IOD, North Atlantic Oscillation-NAO, and North Pacific Oscillation-NPO) on climate at varying scales over time. The long-term averages of precipitation and temperature varied spatially because of the terrain effects. The climate for 1901-2017 was overall getting wetter and warmer, but the interannual variability split the whole study period into three sub-periods: drier and warmer for 1901-1940, wetter and colder for 1941-1966, and wetter and warmer for 1966-2017. For a single atmospheric circulation index, ENSO or NPO had the greatest impacts on the climate change at the scale of 8-16 months over the whole study period. Further, multiple atmospheric circulation index can combine to have simultaneous effects (e.g., NAO-NPO) on climate change. The interannual variability of climate can be attributed to that of a single or combined atmospheric circulation indices. These results provide fundamental information for studies of climate change on the Tibetan Plateau and the globe, and the multivariate wavelet analysis is promising in interpreting the impacts of atmospheric circulation on climate change.

Automated summary

Exploring climate change and teleconnection on the Tibetan Plateau is crucial for understanding global climate change. However, further research is needed due to limited observation data and inadequate consideration of multiple atmospheric circulation indices. In this study, a climate dataset for 1901-2017 was used to analyze precipitation and temperature, and multivariate wavelet coherence was employed to investigate the combined effects of various circulation indices. The results showed spatial and temporal variations in climate, with a general trend of increasing precipitation and temperature. Single and combined circulation indices had significant impacts on climate change, highlighting the importance of considering multiple factors.