Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx

<p>Despite the large availability of satellite and in-situ data on snow cover in the Northern Hemisphere, long-term assessments at an adequate resolution to capture the complexities of mountainous terrains remain limited, particularly for countries like Switzerland. This study addresses this g...

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Main Author: Charlotte Poussin (20718146) (author)
Other Authors: Pablo Timoner (12825632) (author), Pascal Peduzzi (19981326) (author), Gregory Giuliani (37454) (author)
Published: 2025
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_version_ 1852022751113510912
author Charlotte Poussin (20718146)
author2 Pablo Timoner (12825632)
Pascal Peduzzi (19981326)
Gregory Giuliani (37454)
author2_role author
author
author
author_facet Charlotte Poussin (20718146)
Pablo Timoner (12825632)
Pascal Peduzzi (19981326)
Gregory Giuliani (37454)
author_role author
dc.creator.none.fl_str_mv Charlotte Poussin (20718146)
Pablo Timoner (12825632)
Pascal Peduzzi (19981326)
Gregory Giuliani (37454)
dc.date.none.fl_str_mv 2025-02-13T07:08:31Z
dc.identifier.none.fl_str_mv 10.3389/frsen.2025.1542181.s001
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Supplementary_file_1_Past_and_future_trends_in_swiss_snow_cover_multi-decades_analysis_using_the_snow_observation_from_space_algorithm_docx/28407215
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Photogrammetry and Remote Sensing
Earth observations
Earth observation data cube
Landsat and Sentinel-2 multi-sensor time series
snow cover changes
climate change
representative concentration pathway scenarios
dc.title.none.fl_str_mv Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <p>Despite the large availability of satellite and in-situ data on snow cover in the Northern Hemisphere, long-term assessments at an adequate resolution to capture the complexities of mountainous terrains remain limited, particularly for countries like Switzerland. This study addresses this gap by employing two products—the monthly NDSI (Normalized Difference Snow Index) and snow cover products—derived from the Snow Observation from Space (SOfS) algorithm to monitor snow cover dynamics across Switzerland over the past 37 years. The pixel-wise analysis reveals significant negative trends in the monthly NDSI across all seasons, with the most pronounced decreases at low to mid-elevations, particularly in winter and spring (e.g., a 50% reduction in NDSI for pixels showing positive significative trends in winter below 1,000 m, and a 43% reduction in spring between 1,000 and 2,000 m). Similarly, snow cover area has declined significantly, with reductions of −13% to −15% in spring for the transitional zones between 1,000–1,500 m and 1,500–2,000 m. Furthermore, the monthly NDSI values are more strongly influenced by temperature than precipitation, especially at lower altitudes. To estimate trends in snow cover for the 21st century, we modelled the relationship between snow presence and two climatic variables (temperature and precipitation) using a binomial generalized linear mixed model (GLMM). In the context of climate change, projections under various greenhouse gas emission scenarios suggest further declines in snow cover by the end of the century. Even with moderate climate action (RCP 2.6), snow-free areas could expand by 22% at lower elevations by 2100. Under the more extreme scenario (RCP 8.5), snow-free regions could increase by over 43%, with significant impacts during the transitional months of April and May. The SOfS algorithm, developed within the Swiss Data Cube, provides valuable insights into snow cover dynamics across Switzerland. Complementing in-situ observations, this innovative approach is essential for assessing snow cover changes and guiding adaptation strategies in a country where snow is not only an environmental indicator but also a cultural and economic asset.</p>
eu_rights_str_mv openAccess
id Manara_e2c2e13c3f96ce8161e3ee5ceddc330c
identifier_str_mv 10.3389/frsen.2025.1542181.s001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/28407215
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
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rights_invalid_str_mv CC BY 4.0
spelling Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docxCharlotte Poussin (20718146)Pablo Timoner (12825632)Pascal Peduzzi (19981326)Gregory Giuliani (37454)Photogrammetry and Remote SensingEarth observationsEarth observation data cubeLandsat and Sentinel-2 multi-sensor time seriessnow cover changesclimate changerepresentative concentration pathway scenarios<p>Despite the large availability of satellite and in-situ data on snow cover in the Northern Hemisphere, long-term assessments at an adequate resolution to capture the complexities of mountainous terrains remain limited, particularly for countries like Switzerland. This study addresses this gap by employing two products—the monthly NDSI (Normalized Difference Snow Index) and snow cover products—derived from the Snow Observation from Space (SOfS) algorithm to monitor snow cover dynamics across Switzerland over the past 37 years. The pixel-wise analysis reveals significant negative trends in the monthly NDSI across all seasons, with the most pronounced decreases at low to mid-elevations, particularly in winter and spring (e.g., a 50% reduction in NDSI for pixels showing positive significative trends in winter below 1,000 m, and a 43% reduction in spring between 1,000 and 2,000 m). Similarly, snow cover area has declined significantly, with reductions of −13% to −15% in spring for the transitional zones between 1,000–1,500 m and 1,500–2,000 m. Furthermore, the monthly NDSI values are more strongly influenced by temperature than precipitation, especially at lower altitudes. To estimate trends in snow cover for the 21st century, we modelled the relationship between snow presence and two climatic variables (temperature and precipitation) using a binomial generalized linear mixed model (GLMM). In the context of climate change, projections under various greenhouse gas emission scenarios suggest further declines in snow cover by the end of the century. Even with moderate climate action (RCP 2.6), snow-free areas could expand by 22% at lower elevations by 2100. Under the more extreme scenario (RCP 8.5), snow-free regions could increase by over 43%, with significant impacts during the transitional months of April and May. The SOfS algorithm, developed within the Swiss Data Cube, provides valuable insights into snow cover dynamics across Switzerland. Complementing in-situ observations, this innovative approach is essential for assessing snow cover changes and guiding adaptation strategies in a country where snow is not only an environmental indicator but also a cultural and economic asset.</p>2025-02-13T07:08:31ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/frsen.2025.1542181.s001https://figshare.com/articles/dataset/Supplementary_file_1_Past_and_future_trends_in_swiss_snow_cover_multi-decades_analysis_using_the_snow_observation_from_space_algorithm_docx/28407215CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/284072152025-02-13T07:08:31Z
spellingShingle Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
Charlotte Poussin (20718146)
Photogrammetry and Remote Sensing
Earth observations
Earth observation data cube
Landsat and Sentinel-2 multi-sensor time series
snow cover changes
climate change
representative concentration pathway scenarios
status_str publishedVersion
title Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
title_full Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
title_fullStr Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
title_full_unstemmed Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
title_short Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
title_sort Supplementary file 1_Past and future trends in swiss snow cover: multi-decades analysis using the snow observation from space algorithm.docx
topic Photogrammetry and Remote Sensing
Earth observations
Earth observation data cube
Landsat and Sentinel-2 multi-sensor time series
snow cover changes
climate change
representative concentration pathway scenarios