Tracking global large lake surface temperature variation from space using MODIS land surface temperature product

Water temperature monitoring plays a crucial role in the ecological functioning and biogeochemical cycling of aquatic ecosystems. Compared to conventional methods, satellite remote sensing provides a more efficient way to assess lake surface water temperature (LSWT) variations, particularly for large, remote water bodies. In this study, MODIS Land Surface Temperature (LST) product Level 3 (MOD11A2) is employed to analyze the spatiotemporal changes in LST for global inland water bodies with areas exceeding 25 km 2 . This research aims to understand LSWT variations and identify the contributing factors. The findings indicate that during the nighttime, LSWT in different lakes ranges from −11 °C to 26 °C, while diurnal temperature differences (DTDs) range from 1.3 °C to 16.9 °C. Factors such as lake depth, surface area (or volume), altitude, geographical location, and water supply sources are shown to influence LSWT variations. This study addresses the gap in long-term LSWT research for lakes larger than 25 km 2 worldwide, providing valuable insights into the mechanisms driving LSWT changes in similar lake systems. • Global LSWT pattern with lake surface area > 25 km 2 were assessed with MODIS LST. • Analysis of LSWT variations and driving mechanism at multiple scales. • Air temperature is the most significant factor affecting the changes in LSWT.

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Publication Details

Journal
Ecological Informatics
Published
2025-05-02
DOI
https://doi.org/10.1016/j.ecoinf.2025.103184
Citations
3
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
Field-Weighted Citation Impact
3.90

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article

Tracking global large lake surface temperature variation from space using MODIS land surface temperature product

Zhongqiu Sun, Kaishan Song, Jia Du, Boyu Zhao et al.
3 citations
Ecological Informatics
Arctic and Antarctic ice dynamics
3.90
article

Tracking global large lake surface temperature variation from space using MODIS land surface temperature product

Zhongqiu Sun, Kaishan Song, Jia Du, Boyu Zhao, Min Wang
article en
3 citations

Abstract

Water temperature monitoring plays a crucial role in the ecological functioning and biogeochemical cycling of aquatic ecosystems. Compared to conventional methods, satellite remote sensing provides a more efficient way to assess lake surface water temperature (LSWT) variations, particularly for large, remote water bodies. In this study, MODIS Land Surface Temperature (LST) product Level 3 (MOD11A2) is employed to analyze the spatiotemporal changes in LST for global inland water bodies with areas exceeding 25 km 2 . This research aims to understand LSWT variations and identify the contributing factors. The findings indicate that during the nighttime, LSWT in different lakes ranges from −11 °C to 26 °C, while diurnal temperature differences (DTDs) range from 1.3 °C to 16.9 °C. Factors such as lake depth, surface area (or volume), altitude, geographical location, and water supply sources are shown to influence LSWT variations. This study addresses the gap in long-term LSWT research for lakes larger than 25 km 2 worldwide, providing valuable insights into the mechanisms driving LSWT changes in similar lake systems. • Global LSWT pattern with lake surface area > 25 km 2 were assessed with MODIS LST. • Analysis of LSWT variations and driving mechanism at multiple scales. • Air temperature is the most significant factor affecting the changes in LSWT.

Ecological InformaticsVol. 89
Northeast Normal University (CN), Chinese Academy of Sciences (CN), Northeast Institute of Geography and Agroecology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 7%
Arctic and Antarctic ice dynamics
3.90
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