A 10-year record of Arctic summer sea ice freeboard from CryoSat-2
Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculat...
Published in: | Remote Sensing of Environment |
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Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Elsevier
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10037/23142 https://doi.org/10.1016/j.rse.2021.112744 |
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author | Dawson, Geoffrey Landy, Jack Christopher Tsamados, Michel Komarov, Alexander S. Howell, Stephen Heorten, Harold Krumpen, Thomas |
author_facet | Dawson, Geoffrey Landy, Jack Christopher Tsamados, Michel Komarov, Alexander S. Howell, Stephen Heorten, Harold Krumpen, Thomas |
author_sort | Dawson, Geoffrey |
collection | University of Tromsø: Munin Open Research Archive |
container_start_page | 112744 |
container_title | Remote Sensing of Environment |
container_volume | 268 |
description | Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculation. Here, we use over 350 optical and synthetic aperture radar (SAR) images from the summer months to train a 1D convolution neural network for separating CryoSat-2 radar altimeter returns from sea ice floes and leads with an accuracy >80%. This enables us to generate the first pan-Arctic measurements of sea ice radar freeboard for May–September between 2011 and 2020. Results indicate that the freeboard distributions in May and September compare closely to those from a conventional ‘winter’ processor in April and October, respectively. The freeboards capture expected patterns of sea ice melt over the Arctic summer, matching well to ice draft observations from the Beaufort Gyre Exploration Program (BGEP) moorings. However, compared to airborne laser scanner freeboards from Operation IceBridge and airborne EM ice thickness surveys from the Alfred Wegener Institute (AWI) IceBird program, CryoSat-2 freeboards are underestimated by 0.02–0.2 m, and ice thickness is underestimated by 0.28–1.0 m, with the largest differences being over thicker multi-year sea ice. To create the first pan-Arctic summer sea ice thickness dataset we must address primary sources of uncertainty in the conversion from radar freeboard to ice thickness. |
format | Article in Journal/Newspaper |
genre | Arctic Arctic Sea ice |
genre_facet | Arctic Arctic Sea ice |
geographic | Arctic |
geographic_facet | Arctic |
id | ftunivtroemsoe:oai:munin.uit.no:10037/23142 |
institution | Open Polar |
language | English |
op_collection_id | ftunivtroemsoe |
op_doi | https://doi.org/10.1016/j.rse.2021.112744 |
op_relation | Remote Sensing of Environment Norges forskningsråd: 237906 info:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/ FRIDAID 1949515 doi:10.1016/j.rse.2021.112744 https://hdl.handle.net/10037/23142 |
op_rights | openAccess Copyright 2022 The Author(s) |
publishDate | 2022 |
publisher | Elsevier |
record_format | openpolar |
spelling | ftunivtroemsoe:oai:munin.uit.no:10037/23142 2025-04-13T14:11:35+00:00 A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 Dawson, Geoffrey Landy, Jack Christopher Tsamados, Michel Komarov, Alexander S. Howell, Stephen Heorten, Harold Krumpen, Thomas 2022-10-29 https://hdl.handle.net/10037/23142 https://doi.org/10.1016/j.rse.2021.112744 eng eng Elsevier Remote Sensing of Environment Norges forskningsråd: 237906 info:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/ FRIDAID 1949515 doi:10.1016/j.rse.2021.112744 https://hdl.handle.net/10037/23142 openAccess Copyright 2022 The Author(s) VDP::Mathematics and natural science: 400::Physics: 430 VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2022 ftunivtroemsoe https://doi.org/10.1016/j.rse.2021.112744 2025-03-14T05:17:55Z Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculation. Here, we use over 350 optical and synthetic aperture radar (SAR) images from the summer months to train a 1D convolution neural network for separating CryoSat-2 radar altimeter returns from sea ice floes and leads with an accuracy >80%. This enables us to generate the first pan-Arctic measurements of sea ice radar freeboard for May–September between 2011 and 2020. Results indicate that the freeboard distributions in May and September compare closely to those from a conventional ‘winter’ processor in April and October, respectively. The freeboards capture expected patterns of sea ice melt over the Arctic summer, matching well to ice draft observations from the Beaufort Gyre Exploration Program (BGEP) moorings. However, compared to airborne laser scanner freeboards from Operation IceBridge and airborne EM ice thickness surveys from the Alfred Wegener Institute (AWI) IceBird program, CryoSat-2 freeboards are underestimated by 0.02–0.2 m, and ice thickness is underestimated by 0.28–1.0 m, with the largest differences being over thicker multi-year sea ice. To create the first pan-Arctic summer sea ice thickness dataset we must address primary sources of uncertainty in the conversion from radar freeboard to ice thickness. Article in Journal/Newspaper Arctic Arctic Sea ice University of Tromsø: Munin Open Research Archive Arctic Remote Sensing of Environment 268 112744 |
spellingShingle | VDP::Mathematics and natural science: 400::Physics: 430 VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430 Dawson, Geoffrey Landy, Jack Christopher Tsamados, Michel Komarov, Alexander S. Howell, Stephen Heorten, Harold Krumpen, Thomas A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 |
title | A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 |
title_full | A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 |
title_fullStr | A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 |
title_full_unstemmed | A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 |
title_short | A 10-year record of Arctic summer sea ice freeboard from CryoSat-2 |
title_sort | 10-year record of arctic summer sea ice freeboard from cryosat-2 |
topic | VDP::Mathematics and natural science: 400::Physics: 430 VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430 |
topic_facet | VDP::Mathematics and natural science: 400::Physics: 430 VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430 |
url | https://hdl.handle.net/10037/23142 https://doi.org/10.1016/j.rse.2021.112744 |