Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites
With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in re...
Published in: | The Cryosphere |
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Copernicus Publications
2018
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00007507 2023-05-15T13:11:55+02:00 Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites Aalstad, Kristoffer Westermann, Sebastian Schuler, Thomas Vikhamar Boike, Julia Bertino, Laurent 2018-01 electronic https://doi.org/10.5194/tc-12-247-2018 https://noa.gwlb.de/receive/cop_mods_00007507 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00007464/tc-12-247-2018.pdf https://tc.copernicus.org/articles/12/247/2018/tc-12-247-2018.pdf eng eng Copernicus Publications The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-12-247-2018 https://noa.gwlb.de/receive/cop_mods_00007507 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00007464/tc-12-247-2018.pdf https://tc.copernicus.org/articles/12/247/2018/tc-12-247-2018.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2018 ftnonlinearchiv https://doi.org/10.5194/tc-12-247-2018 2022-02-08T22:58:28Z With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least nearly matches the performance of other ensemble-based batch smoother schemes with regards to various evaluation metrics. Given the modularity of the method, it could prove valuable for a range of satellite-era hydrometeorological reanalyses. Article in Journal/Newspaper albedo Arctic Ny Ålesund Ny-Ålesund Svalbard The Cryosphere Niedersächsisches Online-Archiv NOA Arctic Norway Ny-Ålesund Svalbard The Cryosphere 12 1 247 270 |
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Open Polar |
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Niedersächsisches Online-Archiv NOA |
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ftnonlinearchiv |
language |
English |
topic |
article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Aalstad, Kristoffer Westermann, Sebastian Schuler, Thomas Vikhamar Boike, Julia Bertino, Laurent Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites |
topic_facet |
article Verlagsveröffentlichung |
description |
With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least nearly matches the performance of other ensemble-based batch smoother schemes with regards to various evaluation metrics. Given the modularity of the method, it could prove valuable for a range of satellite-era hydrometeorological reanalyses. |
format |
Article in Journal/Newspaper |
author |
Aalstad, Kristoffer Westermann, Sebastian Schuler, Thomas Vikhamar Boike, Julia Bertino, Laurent |
author_facet |
Aalstad, Kristoffer Westermann, Sebastian Schuler, Thomas Vikhamar Boike, Julia Bertino, Laurent |
author_sort |
Aalstad, Kristoffer |
title |
Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites |
title_short |
Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites |
title_full |
Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites |
title_fullStr |
Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites |
title_full_unstemmed |
Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites |
title_sort |
ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at arctic sites |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/tc-12-247-2018 https://noa.gwlb.de/receive/cop_mods_00007507 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00007464/tc-12-247-2018.pdf https://tc.copernicus.org/articles/12/247/2018/tc-12-247-2018.pdf |
geographic |
Arctic Norway Ny-Ålesund Svalbard |
geographic_facet |
Arctic Norway Ny-Ålesund Svalbard |
genre |
albedo Arctic Ny Ålesund Ny-Ålesund Svalbard The Cryosphere |
genre_facet |
albedo Arctic Ny Ålesund Ny-Ålesund Svalbard The Cryosphere |
op_relation |
The Cryosphere -- ˜Theœ Cryosphere -- http://www.bibliothek.uni-regensburg.de/ezeit/?2393169 -- http://www.the-cryosphere.net/ -- 1994-0424 https://doi.org/10.5194/tc-12-247-2018 https://noa.gwlb.de/receive/cop_mods_00007507 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00007464/tc-12-247-2018.pdf https://tc.copernicus.org/articles/12/247/2018/tc-12-247-2018.pdf |
op_rights |
https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5194/tc-12-247-2018 |
container_title |
The Cryosphere |
container_volume |
12 |
container_issue |
1 |
container_start_page |
247 |
op_container_end_page |
270 |
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1766249472151519232 |