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<p>Land surface temperature (LST) derived from satellite thermal infrared sensors is widely used to monitor climate variability in mountain regions, yet its ability to reproduce long-term daily temperature trends under complex topographic and radiative conditions remains insufficiently constrained. Here, we evaluate the performance of four daily MODIS LST products from the Terra and Aqua platforms (daytime and nighttime) over the period 2000–2023 using an exceptional network of 78 high-elevation thermal infrared radiometers from the IMIS network in the Swiss Alps. Daily LST trends were compared at station–pixel pairs using strict temporal matching and quality filtering, while explicitly assessing the influence of land-cover composition, sub-pixel thermal heterogeneity, and seasonal insolation conditions on the agreement between satellite-derived and in situ signals. Results show that nighttime MODIS products exhibit substantially higher temporal coherence, lower dispersion, and minimal sensitivity to data-availability thresholds compared with daytime products. Daytime trends are strongly affected by illumination conditions, with mixed-insolation pixels displaying pronounced internal temperature variability and reduced agreement with ground-based trends, despite retaining spatially coherent regional patterns. Using a composite of all station–pixel pairs across the Swiss Alps, nighttime MODIS products accurately reproduce the seasonal structure of in situ daily trends and reveal two robust winter warming peaks that exceed those observed during spring, summer, or autumn. These findings demonstrate that nocturnal MODIS LST provides a stable and robust basis for detecting regional-scale signals of LST changes in complex mountain environments.</p>

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Daily MODIS land surface temperature trends reveal dual winter warming peaks in the Swiss Alps

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月29日

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  • Andrés Lo Vecchio,
  • Mathieu Gravey,
  • Esteban Lannutti,
  • Fernando Ruiz Peyré,
  • Oliver Bender,
  • Ricardo Villalba

摘要

Land surface temperature (LST) derived from satellite thermal infrared sensors is widely used to monitor climate variability in mountain regions, yet its ability to reproduce long-term daily temperature trends under complex topographic and radiative conditions remains insufficiently constrained. Here, we evaluate the performance of four daily MODIS LST products from the Terra and Aqua platforms (daytime and nighttime) over the period 2000–2023 using an exceptional network of 78 high-elevation thermal infrared radiometers from the IMIS network in the Swiss Alps. Daily LST trends were compared at station–pixel pairs using strict temporal matching and quality filtering, while explicitly assessing the influence of land-cover composition, sub-pixel thermal heterogeneity, and seasonal insolation conditions on the agreement between satellite-derived and in situ signals. Results show that nighttime MODIS products exhibit substantially higher temporal coherence, lower dispersion, and minimal sensitivity to data-availability thresholds compared with daytime products. Daytime trends are strongly affected by illumination conditions, with mixed-insolation pixels displaying pronounced internal temperature variability and reduced agreement with ground-based trends, despite retaining spatially coherent regional patterns. Using a composite of all station–pixel pairs across the Swiss Alps, nighttime MODIS products accurately reproduce the seasonal structure of in situ daily trends and reveal two robust winter warming peaks that exceed those observed during spring, summer, or autumn. These findings demonstrate that nocturnal MODIS LST provides a stable and robust basis for detecting regional-scale signals of LST changes in complex mountain environments.