Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
文献类型: 外文期刊
第一作者: Xie, Cong
作者: Xie, Cong;Zhuang, Long;Zhu, Ruixi;Guo, Jie;Zhang, Xin
作者机构:
期刊名称:SCIENTIFIC REPORTS ( 影响因子:4.996; 五年影响因子:5.516 )
ISSN: 2045-2322
年卷期: 2022 年 12 卷 1 期
页码:
收录情况: SCI
摘要: China has a great wealth of lake resources over a great spatial extent and these lakes are highly sensitive to climate changes through their heat and water budgets. However, little is known about the changes in lake surface water temperature (LSWT) across China under the climate warming conditions over the past few decades. In this study, MODIS land surface temperature (LST) data were used to examine the spatial and temporal (diurnal, intra-annual, and inter-annual) variations in LSWT of China's lakes during 2001-2016. Our results indicated that 169 large lakes included in the study exhibited an overall increasing trend in LSWT, with an average rate of 0.26 degrees C/decade. The increasing rate of nighttime LSWT is 0.31 degrees C/decade, faster than that of daytime temperature (0.21 degrees C/decade). Overall, 121 (71.6%) lakes showed an increase in daytime temperature with a mean rate of 0.38 degrees C/decade, while the rest 48 (28.4%) lakes decreased in temperature with a mean rate of - 0.21 degrees C/decade. We also quantitatively analyzed the relationship of the lake surface temperature and diurnal temperature differences (DTDs) with geographical location, topography, and lake morphometry by utilizing multivariate regression analysis. Our analysis suggested that the geographical location (latitude and longitude) and topography (altitude) were primary driving factors in explaining the national lake water temperature variation (P < 0.001), which were also mediated by morphometric factors such as lake surface area and volume. Moreover, the diurnal lake temperature variations were significantly correlated with altitude, latitude, and lake surface area (R-2 = 0.426, P < 0.001). Correlation analyses of LSWT trend and air temperature trend for each lake indicated that LSWT was positively correlated with air temperature in both daytime and nighttime for most lakes.
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