Cargando…

Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data

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 o...

Descripción completa

Detalles Bibliográficos
Autores principales: Xie, Cong, Zhang, Xin, Zhuang, Long, Zhu, Ruixi, Guo, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8844009/
https://www.ncbi.nlm.nih.gov/pubmed/35165355
http://dx.doi.org/10.1038/s41598-022-06363-9
_version_ 1784651391038390272
author Xie, Cong
Zhang, Xin
Zhuang, Long
Zhu, Ruixi
Guo, Jie
author_facet Xie, Cong
Zhang, Xin
Zhuang, Long
Zhu, Ruixi
Guo, Jie
author_sort Xie, Cong
collection PubMed
description 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 °C/decade. The increasing rate of nighttime LSWT is 0.31 °C/decade, faster than that of daytime temperature (0.21 °C/decade). Overall, 121 (71.6%) lakes showed an increase in daytime temperature with a mean rate of 0.38 °C/decade, while the rest 48 (28.4%) lakes decreased in temperature with a mean rate of − 0.21 °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.
format Online
Article
Text
id pubmed-8844009
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-88440092022-02-16 Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data Xie, Cong Zhang, Xin Zhuang, Long Zhu, Ruixi Guo, Jie Sci Rep Article 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 °C/decade. The increasing rate of nighttime LSWT is 0.31 °C/decade, faster than that of daytime temperature (0.21 °C/decade). Overall, 121 (71.6%) lakes showed an increase in daytime temperature with a mean rate of 0.38 °C/decade, while the rest 48 (28.4%) lakes decreased in temperature with a mean rate of − 0.21 °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. Nature Publishing Group UK 2022-02-14 /pmc/articles/PMC8844009/ /pubmed/35165355 http://dx.doi.org/10.1038/s41598-022-06363-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Xie, Cong
Zhang, Xin
Zhuang, Long
Zhu, Ruixi
Guo, Jie
Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
title Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
title_full Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
title_fullStr Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
title_full_unstemmed Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
title_short Analysis of surface temperature variation of lakes in China using MODIS land surface temperature data
title_sort analysis of surface temperature variation of lakes in china using modis land surface temperature data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8844009/
https://www.ncbi.nlm.nih.gov/pubmed/35165355
http://dx.doi.org/10.1038/s41598-022-06363-9
work_keys_str_mv AT xiecong analysisofsurfacetemperaturevariationoflakesinchinausingmodislandsurfacetemperaturedata
AT zhangxin analysisofsurfacetemperaturevariationoflakesinchinausingmodislandsurfacetemperaturedata
AT zhuanglong analysisofsurfacetemperaturevariationoflakesinchinausingmodislandsurfacetemperaturedata
AT zhuruixi analysisofsurfacetemperaturevariationoflakesinchinausingmodislandsurfacetemperaturedata
AT guojie analysisofsurfacetemperaturevariationoflakesinchinausingmodislandsurfacetemperaturedata