He Zhi-Wei, Tang Bo-Hui
Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China; Key Laboratory of Plateau Remote Sensing, Department of Education of Yunnan Province, Kunming, China.
Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China; Key Laboratory of Plateau Remote Sensing, Department of Education of Yunnan Province, Kunming, China; State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Sci Total Environ. 2023 Oct 20;896:165288. doi: 10.1016/j.scitotenv.2023.165288. Epub 2023 Jul 3.
In this study, the spatiotemporal change patterns and driving factors of land surface temperature (LST) on the Yunnan-Kweichow Plateau (YKP) during 2000-2020 are investigated by using the Thermal and Reanalysis Integrating Moderate-resolution Spatial-seamless (TRIMS) LST dataset provided by National Tibetan Plateau Data Center. The YKP LST spatiotemporal change patterns are revealed at annual, seasonal, monthly, and daily scales. Furthermore, seven driving factors such as air temperature, land cover types, normalized difference vegetation index, precipitation, solar radiation, elevation, and latitude are quantified the impacts on LST spatial heterogeneity at annual scale. The main findings are as follows: (1) Annual mean LST increases by 0.016 K/year. Annual mean daytime LST slightly decreases by 0.009 K/year. Annual mean nighttime LST significantly increases by 0.042 K/year. (2) The trend and seasonal components of the daily, daily mean daytime, and daily mean nighttime LST have five and four breakpoints respectively, indicating that the variation of LST is unstable during 2000-2020 on the YKP. (3) The LST lapse rates at nighttime are generally higher than those at daytime on the YKP at the annual, seasonal, and monthly scales. The LST maximum lapse rate is 0.59 K/100 m in summer nighttime, and the LST minimum lapse rate is 0.18 K/100 m in winter daytime. (4) The controlling effects of seven factors are generally stronger in the nighttime than those in the daytime. The factors of elevation and air temperature dominate the LST spatial distribution on the YKP, with a contribution rate of >70 %. In addition, the interactions among the seven factors are all enhancing the effects on the spatial distribution of annual mean LST, including bivariate enhancement and nonlinear enhancement. This study contributes to the mitigation and adaptation to climate change of LST in the plateau and plays a theoretical reference role in formulating corresponding policies for environmental protection.
本研究利用国家青藏高原数据中心提供的热与再分析集成中分辨率空间无缝（TRIMS）地表温度数据集，对2000—2020年云贵高原地表温度（LST）的时空变化格局及驱动因素进行了研究。揭示了云贵高原LST在年、季、月和日尺度上的时空变化格局。此外，对气温、土地覆盖类型、归一化植被指数、降水、太阳辐射、海拔和纬度等7个驱动因素在年尺度上对LST空间异质性的影响进行了量化。主要研究结果如下：（1）年平均LST以0.016 K/年的速度上升。年平均白天LST以0.009 K/年的速度略有下降。年平均夜间LST以0.042 K/年的速度显著上升。（2）日、日平均白天和日平均夜间LST的趋势和季节分量分别有5个和4个断点，表明2000—2020年云贵高原LST的变化不稳定。（3）在年、季和月尺度上，云贵高原夜间LST的递减率一般高于白天。夏季夜间LST最大递减率为0.59 K/100 m，冬季白天LST最小递减率为0.18 K/100 m。（4）7个因素的控制作用在夜间一般比白天更强。海拔和气温因素主导了云贵高原LST的空间分布，贡献率>70%。此外，7个因素之间的相互作用均增强了对年平均LST空间分布的影响，包括双变量增强和非线性增强。本研究有助于高原地区LST的气候变化减缓与适应，为制定相应的环境保护政策提供理论参考。
