Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval
Snow water equivalent (SWE) is a valuable characteristic of snow cover, and it can be estimated using passive spaceborne radiometer measurements. The radiometer-based GlobSnow SWE retrieval methodology, which assimilates weather station snow depth observations into the retrieval, has improved the re...
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Copernicus Publications
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ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00064974 2023-05-15T18:32:33+02:00 Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval Venäläinen, Pinja Luojus, Kari Mortimer, Colleen Lemmetyinen, Juha Pulliainen, Jouni Takala, Matias Moisander, Mikko Zschenderlein, Lina 2023-02 electronic https://doi.org/10.5194/tc-17-719-2023 https://noa.gwlb.de/receive/cop_mods_00064974 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00063631/tc-17-719-2023.pdf https://tc.copernicus.org/articles/17/719/2023/tc-17-719-2023.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-17-719-2023 https://noa.gwlb.de/receive/cop_mods_00064974 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00063631/tc-17-719-2023.pdf https://tc.copernicus.org/articles/17/719/2023/tc-17-719-2023.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2023 ftnonlinearchiv https://doi.org/10.5194/tc-17-719-2023 2023-02-20T00:14:02Z Snow water equivalent (SWE) is a valuable characteristic of snow cover, and it can be estimated using passive spaceborne radiometer measurements. The radiometer-based GlobSnow SWE retrieval methodology, which assimilates weather station snow depth observations into the retrieval, has improved the reliability and accuracy of SWE retrieval when compared to stand-alone radiometer SWE retrievals. To further improve the GlobSnow SWE retrieval methodology, we investigate implementing spatially and temporally varying snow densities into the retrieval procedure. Thus far, the GlobSnow SWE retrieval has used a constant snow density throughout the retrieval despite differing locations, snow depth, or time of winter. This constant snow density is a known source of inaccuracy in the retrieval. Four different versions of spatially and temporally varying snow densities are tested over a 10-year period (2000–2009). These versions use two different spatial interpolation techniques: ordinary Kriging interpolation and inverse distance weighted regression (IDWR). All versions were found to improve the SWE retrieval compared to the baseline GlobSnow v3.0 product, although differences between versions are small. Overall, the best results were obtained by implementing IDWR-interpolated densities into the algorithm, which reduced RMSE (root mean square error) and MAE (mean absolute error) by about 4 mm (8 % improvement) and 5 mm (16 % improvement) when compared to the baseline GlobSnow product, respectively. Furthermore, implementing varying snow densities into the SWE retrieval improves the magnitude and seasonal evolution of the Northern Hemisphere snow mass estimate compared to the baseline product and a product post-processed with varying snow densities. Article in Journal/Newspaper The Cryosphere Niedersächsisches Online-Archiv NOA The Cryosphere 17 2 719 736 |
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Open Polar |
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Niedersächsisches Online-Archiv NOA |
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ftnonlinearchiv |
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English |
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article Verlagsveröffentlichung |
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article Verlagsveröffentlichung Venäläinen, Pinja Luojus, Kari Mortimer, Colleen Lemmetyinen, Juha Pulliainen, Jouni Takala, Matias Moisander, Mikko Zschenderlein, Lina Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval |
topic_facet |
article Verlagsveröffentlichung |
description |
Snow water equivalent (SWE) is a valuable characteristic of snow cover, and it can be estimated using passive spaceborne radiometer measurements. The radiometer-based GlobSnow SWE retrieval methodology, which assimilates weather station snow depth observations into the retrieval, has improved the reliability and accuracy of SWE retrieval when compared to stand-alone radiometer SWE retrievals. To further improve the GlobSnow SWE retrieval methodology, we investigate implementing spatially and temporally varying snow densities into the retrieval procedure. Thus far, the GlobSnow SWE retrieval has used a constant snow density throughout the retrieval despite differing locations, snow depth, or time of winter. This constant snow density is a known source of inaccuracy in the retrieval. Four different versions of spatially and temporally varying snow densities are tested over a 10-year period (2000–2009). These versions use two different spatial interpolation techniques: ordinary Kriging interpolation and inverse distance weighted regression (IDWR). All versions were found to improve the SWE retrieval compared to the baseline GlobSnow v3.0 product, although differences between versions are small. Overall, the best results were obtained by implementing IDWR-interpolated densities into the algorithm, which reduced RMSE (root mean square error) and MAE (mean absolute error) by about 4 mm (8 % improvement) and 5 mm (16 % improvement) when compared to the baseline GlobSnow product, respectively. Furthermore, implementing varying snow densities into the SWE retrieval improves the magnitude and seasonal evolution of the Northern Hemisphere snow mass estimate compared to the baseline product and a product post-processed with varying snow densities. |
format |
Article in Journal/Newspaper |
author |
Venäläinen, Pinja Luojus, Kari Mortimer, Colleen Lemmetyinen, Juha Pulliainen, Jouni Takala, Matias Moisander, Mikko Zschenderlein, Lina |
author_facet |
Venäläinen, Pinja Luojus, Kari Mortimer, Colleen Lemmetyinen, Juha Pulliainen, Jouni Takala, Matias Moisander, Mikko Zschenderlein, Lina |
author_sort |
Venäläinen, Pinja |
title |
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval |
title_short |
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval |
title_full |
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval |
title_fullStr |
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval |
title_full_unstemmed |
Implementing spatially and temporally varying snow densities into the GlobSnow snow water equivalent retrieval |
title_sort |
implementing spatially and temporally varying snow densities into the globsnow snow water equivalent retrieval |
publisher |
Copernicus Publications |
publishDate |
2023 |
url |
https://doi.org/10.5194/tc-17-719-2023 https://noa.gwlb.de/receive/cop_mods_00064974 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00063631/tc-17-719-2023.pdf https://tc.copernicus.org/articles/17/719/2023/tc-17-719-2023.pdf |
genre |
The Cryosphere |
genre_facet |
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-17-719-2023 https://noa.gwlb.de/receive/cop_mods_00064974 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00063631/tc-17-719-2023.pdf https://tc.copernicus.org/articles/17/719/2023/tc-17-719-2023.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-17-719-2023 |
container_title |
The Cryosphere |
container_volume |
17 |
container_issue |
2 |
container_start_page |
719 |
op_container_end_page |
736 |
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1766216739554590720 |