Analysis of spatiotemporal variation in land surface temperature on the Tibetan Plateau from 2001 to 2020

ABSTRACT

With global climate warming intensifying, the Land Surface Temperature (LST) variation on the Tibetan Plateau (TP) has become a hot topic in environmental studies. This letter employs spatial analysis to identify LST distribution characteristics, the Pettitt test to detect abrupt changes, and Fast Fourier Transform (FFT) to analyse periodic variations. Analysing mean annual and seasonal LST from 2001 to 2020, the results indicate the following: (1) Over the past 20 years, the TP’s LST increased slowly at 0.08°C per decade, with significant seasonal variations. Warming trends dominate in spring, summer, and autumn, shifting from the northern to the southwestern plateau. Autumn shows the most significant warming at 0.31°C per decade, while winter shows a cooling trend at −0.46°C per decade. (2) The Pettitt test reveals no statistically significant abrupt changes in mean annual and seasonal LST, though potential change points were detected in 2013 for mean annual LST, and in 2005, 2006, 2014, and 2017 for summer, spring, autumn, and winter, respectively. This indicates relative stability in interannual temperature changes, with some asynchronous seasonal variations. FFT analysis indicates dominant short-term variability with a period of 3.33 years and secondary cycles of 10 and 5 years.

Keywords:

• Tibetan plateau
• land surface temperature
• Pettitt test
• fast Fourier transform

Acknowledgments

The authors gratefully acknowledge funding support from the National Natural Science Foundation of China (Nos. 41871321), the National Key Research and Development Program of China (2022YFC3005702), and the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources (KF-2021-06-033). They also greatly thank the National Tibetan Plateau Data Center (http://data.tpdc.ac.cn) for providing the land surface temperature data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the National Key Research and Development Program of China [2022YFC3005702]; National Natural Science Foundation of China [Nos. 41871321]; Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources [KF-2021-06-033].