An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval

State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given...

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Main Authors: Skourup, H, Farrell, SL, Hendricks, S, Ricker, R, Armitage, TWK, Ridout, A, Andersen, OB, Haas, C, Baker, S
Format: Article in Journal/Newspaper
Language:English
Published: 2017
Subjects:
Online Access:https://discovery.ucl.ac.uk/id/eprint/10039581/1/Skourup_et_al-2017-Journal_of_Geophysical_Research__Oceans.pdf
https://discovery.ucl.ac.uk/id/eprint/10039581/
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author Skourup, H
Farrell, SL
Hendricks, S
Ricker, R
Armitage, TWK
Ridout, A
Andersen, OB
Haas, C
Baker, S
author_facet Skourup, H
Farrell, SL
Hendricks, S
Ricker, R
Armitage, TWK
Ridout, A
Andersen, OB
Haas, C
Baker, S
author_sort Skourup, H
collection University College London: UCL Discovery
description State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high-frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multisensor oceanographic time series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04 and DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, intersatellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m.
format Article in Journal/Newspaper
genre Arctic
Arctic Ocean
ice pack
Sea ice
genre_facet Arctic
Arctic Ocean
ice pack
Sea ice
geographic Arctic
Arctic Ocean
Gakkel Ridge
geographic_facet Arctic
Arctic Ocean
Gakkel Ridge
id ftucl:oai:eprints.ucl.ac.uk.OAI2:10039581
institution Open Polar
language English
long_lat ENVELOPE(90.000,90.000,87.000,87.000)
op_collection_id ftucl
op_relation https://discovery.ucl.ac.uk/id/eprint/10039581/1/Skourup_et_al-2017-Journal_of_Geophysical_Research__Oceans.pdf
https://discovery.ucl.ac.uk/id/eprint/10039581/
op_rights open
op_source Journal of Geophysical Research: Oceans , 122 (11) pp. 8593-8613. (2017)
publishDate 2017
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spelling ftucl:oai:eprints.ucl.ac.uk.OAI2:10039581 2025-01-16T20:08:43+00:00 An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval Skourup, H Farrell, SL Hendricks, S Ricker, R Armitage, TWK Ridout, A Andersen, OB Haas, C Baker, S 2017-11-11 text https://discovery.ucl.ac.uk/id/eprint/10039581/1/Skourup_et_al-2017-Journal_of_Geophysical_Research__Oceans.pdf https://discovery.ucl.ac.uk/id/eprint/10039581/ eng eng https://discovery.ucl.ac.uk/id/eprint/10039581/1/Skourup_et_al-2017-Journal_of_Geophysical_Research__Oceans.pdf https://discovery.ucl.ac.uk/id/eprint/10039581/ open Journal of Geophysical Research: Oceans , 122 (11) pp. 8593-8613. (2017) Arctic sea ice mean sea surface geoid model error estimation altimetry Article 2017 ftucl 2023-11-27T13:07:27Z State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high-frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multisensor oceanographic time series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04 and DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, intersatellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m. Article in Journal/Newspaper Arctic Arctic Ocean ice pack Sea ice University College London: UCL Discovery Arctic Arctic Ocean Gakkel Ridge ENVELOPE(90.000,90.000,87.000,87.000)
spellingShingle Arctic
sea ice
mean sea surface
geoid model
error estimation
altimetry
Skourup, H
Farrell, SL
Hendricks, S
Ricker, R
Armitage, TWK
Ridout, A
Andersen, OB
Haas, C
Baker, S
An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval
title An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval
title_full An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval
title_fullStr An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval
title_full_unstemmed An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval
title_short An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval
title_sort assessment of state-of-the-art mean sea surface and geoid models of the arctic ocean: implications for sea ice freeboard retrieval
topic Arctic
sea ice
mean sea surface
geoid model
error estimation
altimetry
topic_facet Arctic
sea ice
mean sea surface
geoid model
error estimation
altimetry
url https://discovery.ucl.ac.uk/id/eprint/10039581/1/Skourup_et_al-2017-Journal_of_Geophysical_Research__Oceans.pdf
https://discovery.ucl.ac.uk/id/eprint/10039581/