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Land Surface Temperature Dynamics in the Yarlung Zangbo River Basin on the Tibetan Plateau from 2000 to 2024.

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Title: Land Surface Temperature Dynamics in the Yarlung Zangbo River Basin on the Tibetan Plateau from 2000 to 2024.
Authors: Qiu, Yuanlin1 (AUTHOR) ylqiu@nhri.cn, Li, Ming2 (AUTHOR), Jia, Jianwei3 (AUTHOR), Zhang, Xiaohao1,3 (AUTHOR), Chen, Liangang1,2 (AUTHOR), Tian, Zihe1,3 (AUTHOR), Wang, Tao2 (AUTHOR), Wan, Min2 (AUTHOR), Wang, Wei2 (AUTHOR)
Source: Remote Sensing. Jun2026, Vol. 18 Issue 11, p1819. 26p.
Subjects: Land surface temperature, Meteorological precipitation, Satellite-based remote sensing, Watersheds, Climate change, Uplands, Heat flux, Monsoon Experiment
Geographic Terms: Tibet (China)
Abstract: Highlights: What are the main findings? Satellite-based land surface temperature (LST) reveals pronounced warming in the Yarlung Zangbo River Basin, with maximum LST increasing nearly twice as fast as mean LST. Precipitation is identified as the primary meteorological drivers of LST changes and exhibits a generally negative relationship with LST trends across the basin. What are the implications of the main findings? Surface thermal conditions in high-altitude basins are changing rapidly, with important implications for cryosphere processes and downstream water resources. The dominant role of precipitation highlights the importance of monsoon moisture in regulating long-term surface thermal dynamics over the southern Tibetan Plateau. The Yarlung Zangbo River Basin (YZRB) stores abundant solid water resources. These components are highly sensitive to climate warming and play a critical role in regulating downstream water availability. However, the spatiotemporal responses of the thermal state to ongoing climate change and its potential atmospheric forcing remain poorly understood. Here, we use satellite-based land surface temperature (LST) to characterize the thermal dynamics of the YZRB during 2000–2024. Further, a machine learning model combined with Shapley Additive Explanations (SHAP) is applied to quantify the pixel-level statistical contributions of meteorological variables to LST trends. The climatological LST exhibits pronounced spatial and seasonal heterogeneity, with lower temperatures in the northwestern and northeastern regions and higher temperatures in the central and southeastern regions. The intra-annual cycle follows a unimodal pattern, peaking in early summer, while downstream sub-basins show a delay in peaking times. Mean LST increases at a rate of 0.18 °C decade−1, while maximum LST warms at nearly twice this rate (0.40 °C decade−1) with widespread warming across the basin. However, minimum LST shows no significant long-term trend, mainly due to the polarization trend within the year. The warming signal shows strong season dependence, with the largest monthly warming trend exceeding 0.80 °C decade−1 for all three LST metrics. Attribution analysis identifies precipitation as the primary meteorological factor statistically associated with basin-scale LST trends. Wind speed may largely represent a response to increasing LST rather than a direct driving factor. Downward shortwave radiation, air temperature and specific humidity exhibit stronger influences in specific regions rather than at the basin scale. The dominant control of precipitation reflects strong monsoon influence on LST dynamics along the southern margin of the Tibetan Plateau. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Land Surface Temperature Dynamics in the Yarlung Zangbo River Basin on the Tibetan Plateau from 2000 to 2024.
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  Data: <searchLink fieldCode="AR" term="%22Qiu%2C+Yuanlin%22">Qiu, Yuanlin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ylqiu@nhri.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Ming%22">Li, Ming</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jia%2C+Jianwei%22">Jia, Jianwei</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xiaohao%22">Zhang, Xiaohao</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Liangang%22">Chen, Liangang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tian%2C+Zihe%22">Tian, Zihe</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Tao%22">Wang, Tao</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wan%2C+Min%22">Wan, Min</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Wei%22">Wang, Wei</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2026, Vol. 18 Issue 11, p1819. 26p.
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  Data: <searchLink fieldCode="DE" term="%22Land+surface+temperature%22">Land surface temperature</searchLink><br /><searchLink fieldCode="DE" term="%22Meteorological+precipitation%22">Meteorological precipitation</searchLink><br /><searchLink fieldCode="DE" term="%22Satellite-based+remote+sensing%22">Satellite-based remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Watersheds%22">Watersheds</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Uplands%22">Uplands</searchLink><br /><searchLink fieldCode="DE" term="%22Heat+flux%22">Heat flux</searchLink><br /><searchLink fieldCode="DE" term="%22Monsoon+Experiment%22">Monsoon Experiment</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Tibet+%28China%29%22">Tibet (China)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Highlights: What are the main findings? Satellite-based land surface temperature (LST) reveals pronounced warming in the Yarlung Zangbo River Basin, with maximum LST increasing nearly twice as fast as mean LST. Precipitation is identified as the primary meteorological drivers of LST changes and exhibits a generally negative relationship with LST trends across the basin. What are the implications of the main findings? Surface thermal conditions in high-altitude basins are changing rapidly, with important implications for cryosphere processes and downstream water resources. The dominant role of precipitation highlights the importance of monsoon moisture in regulating long-term surface thermal dynamics over the southern Tibetan Plateau. The Yarlung Zangbo River Basin (YZRB) stores abundant solid water resources. These components are highly sensitive to climate warming and play a critical role in regulating downstream water availability. However, the spatiotemporal responses of the thermal state to ongoing climate change and its potential atmospheric forcing remain poorly understood. Here, we use satellite-based land surface temperature (LST) to characterize the thermal dynamics of the YZRB during 2000–2024. Further, a machine learning model combined with Shapley Additive Explanations (SHAP) is applied to quantify the pixel-level statistical contributions of meteorological variables to LST trends. The climatological LST exhibits pronounced spatial and seasonal heterogeneity, with lower temperatures in the northwestern and northeastern regions and higher temperatures in the central and southeastern regions. The intra-annual cycle follows a unimodal pattern, peaking in early summer, while downstream sub-basins show a delay in peaking times. Mean LST increases at a rate of 0.18 °C decade−1, while maximum LST warms at nearly twice this rate (0.40 °C decade−1) with widespread warming across the basin. However, minimum LST shows no significant long-term trend, mainly due to the polarization trend within the year. The warming signal shows strong season dependence, with the largest monthly warming trend exceeding 0.80 °C decade−1 for all three LST metrics. Attribution analysis identifies precipitation as the primary meteorological factor statistically associated with basin-scale LST trends. Wind speed may largely represent a response to increasing LST rather than a direct driving factor. Downward shortwave radiation, air temperature and specific humidity exhibit stronger influences in specific regions rather than at the basin scale. The dominant control of precipitation reflects strong monsoon influence on LST dynamics along the southern margin of the Tibetan Plateau. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/rs18111819
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 26
        StartPage: 1819
    Subjects:
      – SubjectFull: Land surface temperature
        Type: general
      – SubjectFull: Meteorological precipitation
        Type: general
      – SubjectFull: Satellite-based remote sensing
        Type: general
      – SubjectFull: Watersheds
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Uplands
        Type: general
      – SubjectFull: Heat flux
        Type: general
      – SubjectFull: Monsoon Experiment
        Type: general
      – SubjectFull: Tibet (China)
        Type: general
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      – TitleFull: Land Surface Temperature Dynamics in the Yarlung Zangbo River Basin on the Tibetan Plateau from 2000 to 2024.
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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