Articles | Volume 16, issue 9
https://doi.org/10.5194/essd-16-3913-2024
https://doi.org/10.5194/essd-16-3913-2024
Data description paper
 | 
02 Sep 2024
Data description paper |  | 02 Sep 2024

Time series of alpine snow surface radiative-temperature maps from high-precision thermal-infrared imaging

Sara Arioli, Ghislain Picard, Laurent Arnaud, Simon Gascoin, Esteban Alonso-González, Marine Poizat, and Mark Irvine

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Cited articles

Aasen, H., Honkavaara, E., Lucieer, A., and Zarco-Tejada, P. J.: Quantitative remote sensing at ultra-high resolution with UAV spectroscopy: a review of sensor technology, measurement procedures, and data correction workflows, Remote Sensing, 10, 1091, https://doi.org/10.3390/rs10071091, 2018. a
Adams, E., Slaughter, A., McKittrick, L., and Miller, D.: Local terrain-topography and thermal-properties influence on energy and mass balance of a snow cover, Ann. Glaciol., 52, 169–175, https://doi.org/10.3189/172756411797252257, 2011. a
Alonso-González, E., Gascoin, S., Arioli, S., and Picard, G.: Exploring the potential of thermal infrared remote sensing to improve a snowpack model through an observing system simulation experiment, The Cryosphere, 17, 3329–3342, https://doi.org/10.5194/tc-17-3329-2023, 2023. a, b
Arioli, S., Picard, G., and Arnaud, L.: Timeseries of the snow surface temperature acquired at the Col du Lautaret (French Alps) during winter 2021–2022 with an uncooled thermal infrared camera – v2 – UTC, EaSy Data [data set], https://doi.org/10.57932/8ed8f0b2-e6ae-4d64-97e5-1ae23e8b97b1, 2024a. a, b
Arioli, S., Picard, G., and Arnaud, L.: Timeseries of the snow surface temperature acquired at the Col du Lautaret (French Alps) during spring 2023 with an uncooled thermal infrared camera – v2 – UTC, EaSy Data [data set], https://doi.org/10.57932/1e9ff61f-1f06-48ae-92d9-6e1f7df8ad8c, 2024b. a, b
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Short summary
High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.
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