Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements

Utilizing a high-resolution (2-km) coastal ocean model output off Eastern Newfoundland, this paper explores the potential for reconstructing the sea surface height (SSH) and the surface inshore Labrador Current from high-resolution SSH data of the upcoming Surface Water and Ocean Topography (SWOT) s...

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Published in:Remote Sensing
Main Authors: Zhimin Ma, Guoqi Han
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2019
Subjects:
Q
Online Access:https://doi.org/10.3390/rs11111264
https://doaj.org/article/6ac06810df2c453f84c73103290b8666
id ftdoajarticles:oai:doaj.org/article:6ac06810df2c453f84c73103290b8666
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spelling ftdoajarticles:oai:doaj.org/article:6ac06810df2c453f84c73103290b8666 2023-05-15T17:22:28+02:00 Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements Zhimin Ma Guoqi Han 2019-05-01T00:00:00Z https://doi.org/10.3390/rs11111264 https://doaj.org/article/6ac06810df2c453f84c73103290b8666 EN eng MDPI AG https://www.mdpi.com/2072-4292/11/11/1264 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11111264 https://doaj.org/article/6ac06810df2c453f84c73103290b8666 Remote Sensing, Vol 11, Iss 11, p 1264 (2019) altimetry application SWOT sea surface height sea surface current inshore Labrador Current optimal interpolation Science Q article 2019 ftdoajarticles https://doi.org/10.3390/rs11111264 2022-12-31T16:06:39Z Utilizing a high-resolution (2-km) coastal ocean model output off Eastern Newfoundland, this paper explores the potential for reconstructing the sea surface height (SSH) and the surface inshore Labrador Current from high-resolution SSH data of the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. The model results are evaluated against in-situ data from tide gauges and nadir altimetry for the period from June to October, 2010. The hourly model SSH output is used as true SSH and sampled along-swath with expected measurement errors by using a SWOT simulator, which produces SWOT-like data. We reconstruct half-day SSH fields from the SWOT-like data using optimal interpolation and average them into weekly fields. The average normalized root-mean-square difference between the weekly reconstructed SSH field and the model SSH filed is 0.07 for the inshore Labrador Current. Between the geostrophic surface current derived from the reconstructed SSH field and the model surface current, the average normalized root-mean-square difference is 0.26 for the inshore Labrador Current. For the surface unit-depth transport of the inshore Labrador Current, the normalized root-mean-square differences are 0.32−0.38 between the reconstructed current and the model current. Article in Journal/Newspaper Newfoundland Directory of Open Access Journals: DOAJ Articles Newfoundland Remote Sensing 11 11 1264
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic altimetry application
SWOT
sea surface height
sea surface current
inshore Labrador Current
optimal interpolation
Science
Q
spellingShingle altimetry application
SWOT
sea surface height
sea surface current
inshore Labrador Current
optimal interpolation
Science
Q
Zhimin Ma
Guoqi Han
Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements
topic_facet altimetry application
SWOT
sea surface height
sea surface current
inshore Labrador Current
optimal interpolation
Science
Q
description Utilizing a high-resolution (2-km) coastal ocean model output off Eastern Newfoundland, this paper explores the potential for reconstructing the sea surface height (SSH) and the surface inshore Labrador Current from high-resolution SSH data of the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. The model results are evaluated against in-situ data from tide gauges and nadir altimetry for the period from June to October, 2010. The hourly model SSH output is used as true SSH and sampled along-swath with expected measurement errors by using a SWOT simulator, which produces SWOT-like data. We reconstruct half-day SSH fields from the SWOT-like data using optimal interpolation and average them into weekly fields. The average normalized root-mean-square difference between the weekly reconstructed SSH field and the model SSH filed is 0.07 for the inshore Labrador Current. Between the geostrophic surface current derived from the reconstructed SSH field and the model surface current, the average normalized root-mean-square difference is 0.26 for the inshore Labrador Current. For the surface unit-depth transport of the inshore Labrador Current, the normalized root-mean-square differences are 0.32−0.38 between the reconstructed current and the model current.
format Article in Journal/Newspaper
author Zhimin Ma
Guoqi Han
author_facet Zhimin Ma
Guoqi Han
author_sort Zhimin Ma
title Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements
title_short Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements
title_full Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements
title_fullStr Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements
title_full_unstemmed Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements
title_sort reconstruction of the surface inshore labrador current from swot sea surface height measurements
publisher MDPI AG
publishDate 2019
url https://doi.org/10.3390/rs11111264
https://doaj.org/article/6ac06810df2c453f84c73103290b8666
geographic Newfoundland
geographic_facet Newfoundland
genre Newfoundland
genre_facet Newfoundland
op_source Remote Sensing, Vol 11, Iss 11, p 1264 (2019)
op_relation https://www.mdpi.com/2072-4292/11/11/1264
https://doaj.org/toc/2072-4292
2072-4292
doi:10.3390/rs11111264
https://doaj.org/article/6ac06810df2c453f84c73103290b8666
op_doi https://doi.org/10.3390/rs11111264
container_title Remote Sensing
container_volume 11
container_issue 11
container_start_page 1264
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