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Snow depth variability in the Northern Hemisphere mountains observed from space
Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we sho...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789005/ https://www.ncbi.nlm.nih.gov/pubmed/31604957 http://dx.doi.org/10.1038/s41467-019-12566-y |
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author | Lievens, Hans Demuzere, Matthias Marshall, Hans-Peter Reichle, Rolf H. Brucker, Ludovic Brangers, Isis de Rosnay, Patricia Dumont, Marie Girotto, Manuela Immerzeel, Walter W. Jonas, Tobias Kim, Edward J. Koch, Inka Marty, Christoph Saloranta, Tuomo Schöber, Johannes De Lannoy, Gabrielle J. M. |
author_facet | Lievens, Hans Demuzere, Matthias Marshall, Hans-Peter Reichle, Rolf H. Brucker, Ludovic Brangers, Isis de Rosnay, Patricia Dumont, Marie Girotto, Manuela Immerzeel, Walter W. Jonas, Tobias Kim, Edward J. Koch, Inka Marty, Christoph Saloranta, Tuomo Schöber, Johannes De Lannoy, Gabrielle J. M. |
author_sort | Lievens, Hans |
collection | PubMed |
description | Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change. |
format | Online Article Text |
id | pubmed-6789005 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67890052019-10-15 Snow depth variability in the Northern Hemisphere mountains observed from space Lievens, Hans Demuzere, Matthias Marshall, Hans-Peter Reichle, Rolf H. Brucker, Ludovic Brangers, Isis de Rosnay, Patricia Dumont, Marie Girotto, Manuela Immerzeel, Walter W. Jonas, Tobias Kim, Edward J. Koch, Inka Marty, Christoph Saloranta, Tuomo Schöber, Johannes De Lannoy, Gabrielle J. M. Nat Commun Article Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change. Nature Publishing Group UK 2019-10-11 /pmc/articles/PMC6789005/ /pubmed/31604957 http://dx.doi.org/10.1038/s41467-019-12566-y Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lievens, Hans Demuzere, Matthias Marshall, Hans-Peter Reichle, Rolf H. Brucker, Ludovic Brangers, Isis de Rosnay, Patricia Dumont, Marie Girotto, Manuela Immerzeel, Walter W. Jonas, Tobias Kim, Edward J. Koch, Inka Marty, Christoph Saloranta, Tuomo Schöber, Johannes De Lannoy, Gabrielle J. M. Snow depth variability in the Northern Hemisphere mountains observed from space |
title | Snow depth variability in the Northern Hemisphere mountains observed from space |
title_full | Snow depth variability in the Northern Hemisphere mountains observed from space |
title_fullStr | Snow depth variability in the Northern Hemisphere mountains observed from space |
title_full_unstemmed | Snow depth variability in the Northern Hemisphere mountains observed from space |
title_short | Snow depth variability in the Northern Hemisphere mountains observed from space |
title_sort | snow depth variability in the northern hemisphere mountains observed from space |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789005/ https://www.ncbi.nlm.nih.gov/pubmed/31604957 http://dx.doi.org/10.1038/s41467-019-12566-y |
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