Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps

Seasonal snow is an essential water resource in many mountain regions. However, the spatio-temporal variability in mountain snow depth or snow water equivalent (SWE) at regional to global scales is not well understood due to the lack of high-resolution satellite observations and robust retrieval alg...

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Published in:The Cryosphere
Main Authors: H. Lievens, I. Brangers, H.-P. Marshall, T. Jonas, M. Olefs, G. De Lannoy
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
Subjects:
geo
Online Access:https://doi.org/10.5194/tc-16-159-2022
https://tc.copernicus.org/articles/16/159/2022/tc-16-159-2022.pdf
https://doaj.org/article/4497bd48775e4f0680d62b6bcdd5c1b8
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:4497bd48775e4f0680d62b6bcdd5c1b8 2023-05-15T18:32:19+02:00 Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps H. Lievens I. Brangers H.-P. Marshall T. Jonas M. Olefs G. De Lannoy 2022-01-01 https://doi.org/10.5194/tc-16-159-2022 https://tc.copernicus.org/articles/16/159/2022/tc-16-159-2022.pdf https://doaj.org/article/4497bd48775e4f0680d62b6bcdd5c1b8 en eng Copernicus Publications doi:10.5194/tc-16-159-2022 1994-0416 1994-0424 https://tc.copernicus.org/articles/16/159/2022/tc-16-159-2022.pdf https://doaj.org/article/4497bd48775e4f0680d62b6bcdd5c1b8 undefined The Cryosphere, Vol 16, Pp 159-177 (2022) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2022 fttriple https://doi.org/10.5194/tc-16-159-2022 2023-01-22T17:50:31Z Seasonal snow is an essential water resource in many mountain regions. However, the spatio-temporal variability in mountain snow depth or snow water equivalent (SWE) at regional to global scales is not well understood due to the lack of high-resolution satellite observations and robust retrieval algorithms. We investigate the ability of the Sentinel-1 mission to monitor snow depth at sub-kilometer (100 m, 500 m, and 1 km) resolutions over the European Alps for 2017–2019. The Sentinel-1 backscatter observations, especially in cross-polarization, show a high correlation with regional model simulations of snow depth over Austria and Switzerland. The observed changes in radar backscatter with the accumulation or ablation of snow are used in an empirical change detection algorithm to retrieve snow depth. The algorithm includes the detection of dry and wet snow conditions. Compared to in situ measurements at 743 sites in the European Alps, dry snow depth retrievals at 500 m and 1 km resolution have a spatio-temporal correlation of 0.89. The mean absolute error equals 20 %–30 % of the measured values for snow depths between 1.5 and 3 m. The performance slightly degrades for retrievals at the finer 100 m spatial resolution as well as for retrievals of shallower and deeper snow. The results demonstrate the ability of Sentinel-1 to provide snow estimates in mountainous regions where satellite-based estimates of snow mass are currently lacking. The retrievals can improve our knowledge of seasonal snow mass in areas with complex topography and benefit a number of applications, such as water resource management, flood forecasting, and numerical weather prediction. However, future research is recommended to further investigate the physical basis of the sensitivity of Sentinel-1 backscatter observations to snow accumulation. Article in Journal/Newspaper The Cryosphere Unknown The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) The Cryosphere 16 1 159 177
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
H. Lievens
I. Brangers
H.-P. Marshall
T. Jonas
M. Olefs
G. De Lannoy
Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
topic_facet geo
envir
description Seasonal snow is an essential water resource in many mountain regions. However, the spatio-temporal variability in mountain snow depth or snow water equivalent (SWE) at regional to global scales is not well understood due to the lack of high-resolution satellite observations and robust retrieval algorithms. We investigate the ability of the Sentinel-1 mission to monitor snow depth at sub-kilometer (100 m, 500 m, and 1 km) resolutions over the European Alps for 2017–2019. The Sentinel-1 backscatter observations, especially in cross-polarization, show a high correlation with regional model simulations of snow depth over Austria and Switzerland. The observed changes in radar backscatter with the accumulation or ablation of snow are used in an empirical change detection algorithm to retrieve snow depth. The algorithm includes the detection of dry and wet snow conditions. Compared to in situ measurements at 743 sites in the European Alps, dry snow depth retrievals at 500 m and 1 km resolution have a spatio-temporal correlation of 0.89. The mean absolute error equals 20 %–30 % of the measured values for snow depths between 1.5 and 3 m. The performance slightly degrades for retrievals at the finer 100 m spatial resolution as well as for retrievals of shallower and deeper snow. The results demonstrate the ability of Sentinel-1 to provide snow estimates in mountainous regions where satellite-based estimates of snow mass are currently lacking. The retrievals can improve our knowledge of seasonal snow mass in areas with complex topography and benefit a number of applications, such as water resource management, flood forecasting, and numerical weather prediction. However, future research is recommended to further investigate the physical basis of the sensitivity of Sentinel-1 backscatter observations to snow accumulation.
format Article in Journal/Newspaper
author H. Lievens
I. Brangers
H.-P. Marshall
T. Jonas
M. Olefs
G. De Lannoy
author_facet H. Lievens
I. Brangers
H.-P. Marshall
T. Jonas
M. Olefs
G. De Lannoy
author_sort H. Lievens
title Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
title_short Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
title_full Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
title_fullStr Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
title_full_unstemmed Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
title_sort sentinel-1 snow depth retrieval at sub-kilometer resolution over the european alps
publisher Copernicus Publications
publishDate 2022
url https://doi.org/10.5194/tc-16-159-2022
https://tc.copernicus.org/articles/16/159/2022/tc-16-159-2022.pdf
https://doaj.org/article/4497bd48775e4f0680d62b6bcdd5c1b8
long_lat ENVELOPE(73.317,73.317,-52.983,-52.983)
geographic The Sentinel
geographic_facet The Sentinel
genre The Cryosphere
genre_facet The Cryosphere
op_source The Cryosphere, Vol 16, Pp 159-177 (2022)
op_relation doi:10.5194/tc-16-159-2022
1994-0416
1994-0424
https://tc.copernicus.org/articles/16/159/2022/tc-16-159-2022.pdf
https://doaj.org/article/4497bd48775e4f0680d62b6bcdd5c1b8
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op_doi https://doi.org/10.5194/tc-16-159-2022
container_title The Cryosphere
container_volume 16
container_issue 1
container_start_page 159
op_container_end_page 177
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