Land Surface Temperature May Have a Greater Impact than Air Temperature on the Autumn Phenology in the Tibetan Plateau

Author:

Tang Hanya1,Sun Xizao1,Zhou Xuelin2ORCID,Li Cheng34,Ma Lei34,Liu Jinlian1,Ding Zhi1,Liu Shiwei1,Yu Pujia1ORCID,Jia Luyao1,Zhang Feng1

Affiliation:

1. Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China

2. College of Computer and Information Engineering, Xinjiang Agriculture University, Urumqi 830052, China

3. Observation and Research Station of Ecological Restoration for Chongqing Typical Mining Areas, Ministry of Natural Resources, Chongqing Institute of Geology and Mineral Resources, Chongqing 401120, China

4. Wansheng Mining Area Ecological Environment Protection and Restoration of Chongqing Observation and Research Station, Ministry of Natural Resources, Chongqing Institute of Geology and Mineral Resources, Chongqing 400715, China

Abstract

The Tibetan Plateau (TP), with its unique geographical and climatic conditions, holds a significant role in global climate change. Therefore, it is particularly urgent to fully understand its vegetation phenology. Herbaceous plants are widely distributed in the TP. However, previous studies have predominantly examined the impact of air temperature on the end date of the vegetation growing season (EOS), with less emphasis on the influence of land surface temperature (LST). In this study, the dynamic changes in the EOS from 2001 to 2020 were analyzed by utilizing the Normalized Difference Vegetation Index (NDVI) data published by NASA. Furthermore, the impact of climate change on the EOS was examined, and the dominant factor (air temperature, LST, or precipitation) influencing the EOS was identified. The main findings were as follows: the average annual EOS predominantly occurred between day of year (DOY) 240 and 280, with an advance from the edge of the plateau to the center. The EOS across the entire region displayed a marginal tendency towards delay, with an average rate of 0.017 days/year. Among all vegetation, shrubs showed the most pronounced delay at a rate of 0.04 days/year. In terms of precipitation, the impact of climate change increased precipitation in both summer and autumn, which could delay EOS. In terms of temperature, an increase in summer Tmin, autumn air temperatures and summer LST delayed the EOS, while an increase in autumn LST advanced the EOS. Compared to air temperature and precipitation, LST had a stronger controlling effect on the EOS (the largest pixel area dominated by LST). These results could offer new insights for enhancing the parameters of vegetation phenology models across the TP.

Funder

earmarked fund

National Natural Science Foundation of China

Science and Technology Department of Xinjiang Uygur Autonomous Region

Natural Science Foundation of Chongqing

Guangdong Provincial Key Laboratory of Big Data Processing and Applications of Hyperspectral Remote Sensing Micro/Nano Satellites

Publisher

MDPI AG

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