Articles | Volume 20, issue 3
https://doi.org/10.5194/tc-20-1715-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-1715-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A remote sensing approach for measuring climatic change effects on snow cover dynamics
Francesco Parizia
Department of Civil, Building and Environmental Engineering, Università di Roma “La Sapienza”, Via Eudossiana 18, Roma, 00184, Italy
Department of Agricultural, Forest and Food Sciences, Università degli Studi di Torino, Largo Paolo Braccini 2, Grugliasco (TO), 10095, Italy
Samuele De Petris
Department of Agricultural, Forest and Food Sciences, Università degli Studi di Torino, Largo Paolo Braccini 2, Grugliasco (TO), 10095, Italy
Luigi Perotti
CORRESPONDING AUTHOR
Department of Agricultural, Forest and Food Sciences, Università degli Studi di Torino, Largo Paolo Braccini 2, Grugliasco (TO), 10095, Italy
Italian Glaciological Committee, Corso Massimo D'Azeglio 42, Torino (TO), 10125, Italy
Marco Giardino
Italian Glaciological Committee, Corso Massimo D'Azeglio 42, Torino (TO), 10125, Italy
Department of Earth Sciences, Università degli Studi di Torino, Via Valperga Caluso 35, Torino (TO), 10125, Italy
Enrico Borgogno-Mondino
Department of Agricultural, Forest and Food Sciences, Università degli Studi di Torino, Largo Paolo Braccini 2, Grugliasco (TO), 10095, Italy
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Mario Gallarate, Nicola Colombo, Enrico Gazzola, Mauro Valt, Christian Ronchi, Luca Lanteri, Roberto Dinale, Rudi Nadalet, Stefano Ferraris, Alessio Gentile, Davide Gisolo, Marco Giardino, Michele Freppaz, and Fiorella Acquaotta
The Cryosphere, 20, 5061–5070, https://doi.org/10.5194/tc-20-5061-2026, https://doi.org/10.5194/tc-20-5061-2026, 2026
Short summary
Short summary
We present a network of 26 sensors measuring snow water equivalent through cosmic rays across the Italian Alps. We study the application of a parameterisation shared by all the probes. The parameters were defined and validated with data taken during two seasons at 13 sites. We show that the parameterisation gives a good estimate of the water equivalent. This finding can contribute to expand data availability by installing similar probes in sites at high elevations and in inaccessible locations.
Edoardo Ronco and Enrico Corrado Borgogno Mondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-7-2025, 201–206, https://doi.org/10.5194/isprs-archives-XLVIII-M-7-2025-201-2025, https://doi.org/10.5194/isprs-archives-XLVIII-M-7-2025-201-2025, 2025
A. Farbo, F. Sarvia, S. De Petris, and E. Borgogno-Mondino
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 863–870, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-863-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-863-2022, 2022
S. De Petris, F. Sarvia, and E. Borgogno-Mondino
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 225–232, https://doi.org/10.5194/isprs-annals-V-3-2022-225-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-225-2022, 2022
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Short summary
This study introduces innovative methods in cryospheric research by mapping and quantifying multi-decadal snow cover changes in the Western Alps using remote sensing. The normalized trend (nT) index offers a novel metric for analyzing annual mean snow events. This enables intensity analysis of climate change impacts on snow dynamics, highlighting critical vulnerabilities in water management and regional economic systems.
This study introduces innovative methods in cryospheric research by mapping and quantifying...