Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation
International audience The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of da...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , , , , , |
Other Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2019
|
Subjects: | |
Online Access: | https://hal.science/hal-02414942 https://hal.science/hal-02414942/document https://hal.science/hal-02414942/file/Metref-al-2019.pdf https://doi.org/10.3390/rs11111336 |
id |
ftunigrenoble:oai:HAL:hal-02414942v1 |
---|---|
record_format |
openpolar |
spelling |
ftunigrenoble:oai:HAL:hal-02414942v1 2024-05-12T08:08:22+00:00 Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation Metref, Sammy Cosme, Emmanuel Le Sommer, Julien Poel, Nora Brankart, Jean-Michel Verron, Jacques Navarro, Laura, Gómez Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ) ANR-17-CE01-0009,BOOST-SWOT,Vers des produits de la circulation océanique de surface à la résolution kilométrique : exploitation de la future mission altimétrique SWOT(2017) 2019 https://hal.science/hal-02414942 https://hal.science/hal-02414942/document https://hal.science/hal-02414942/file/Metref-al-2019.pdf https://doi.org/10.3390/rs11111336 en eng HAL CCSD MDPI info:eu-repo/semantics/altIdentifier/doi/10.3390/rs11111336 hal-02414942 https://hal.science/hal-02414942 https://hal.science/hal-02414942/document https://hal.science/hal-02414942/file/Metref-al-2019.pdf doi:10.3390/rs11111336 info:eu-repo/semantics/OpenAccess ISSN: 2072-4292 Remote Sensing https://hal.science/hal-02414942 Remote Sensing, 2019, ⟨10.3390/rs11111336⟩ SWOT correlated errors OSSE projection detrending ensemble kalman filter [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/article Journal articles 2019 ftunigrenoble https://doi.org/10.3390/rs11111336 2024-04-18T03:38:42Z International audience The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of data, the mismatch between a high spatial resolution and a low temporal resolution, and the observation errors. The present paper focuses on the reduction of the spatially structured errors of SWOT SSH data. It investigates a new error reduction method and assesses its performance in an observing system simulation experiment. The proposed error-reduction method first projects the SWOT SSH onto a subspace spanned by the SWOT spatially structured errors. This projection is removed from the SWOT SSH to obtain a detrended SSH. The detrended SSH is then processed within an ensemble data assimilation analysis to retrieve a full SSH field. In the latter step, the detrending is applied to both the SWOT data and an ensemble of model-simulated SSH fields. Numerical experiments are performed with synthetic SWOT observations and an ensemble from a North Atlantic, 1/60 • simulation of the ocean circulation (NATL60). The data assimilation analysis is carried out with an ensemble Kalman filter. The results are assessed with root mean square errors, power spectrum density, and spatial coherence. They show that a significant part of the large scale SWOT errors is reduced. The filter analysis also reduces the small scale errors and allows for an accurate recovery of the energy of the signal down to 25 km scales. In addition, using the SWOT nadir data to adjust the SSH detrending further reduces the errors. Article in Journal/Newspaper North Atlantic Université Grenoble Alpes: HAL Remote Sensing 11 11 1336 |
institution |
Open Polar |
collection |
Université Grenoble Alpes: HAL |
op_collection_id |
ftunigrenoble |
language |
English |
topic |
SWOT correlated errors OSSE projection detrending ensemble kalman filter [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
spellingShingle |
SWOT correlated errors OSSE projection detrending ensemble kalman filter [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere Metref, Sammy Cosme, Emmanuel Le Sommer, Julien Poel, Nora Brankart, Jean-Michel Verron, Jacques Navarro, Laura, Gómez Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation |
topic_facet |
SWOT correlated errors OSSE projection detrending ensemble kalman filter [SDU]Sciences of the Universe [physics] [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
description |
International audience The Surface Water and Ocean Topography (SWOT) mission is a next generation satellite mission expected to provide a 2 km-resolution observation of the sea surface height (SSH) on a two-dimensional swath. Processing SWOT data will be challenging because of the large amount of data, the mismatch between a high spatial resolution and a low temporal resolution, and the observation errors. The present paper focuses on the reduction of the spatially structured errors of SWOT SSH data. It investigates a new error reduction method and assesses its performance in an observing system simulation experiment. The proposed error-reduction method first projects the SWOT SSH onto a subspace spanned by the SWOT spatially structured errors. This projection is removed from the SWOT SSH to obtain a detrended SSH. The detrended SSH is then processed within an ensemble data assimilation analysis to retrieve a full SSH field. In the latter step, the detrending is applied to both the SWOT data and an ensemble of model-simulated SSH fields. Numerical experiments are performed with synthetic SWOT observations and an ensemble from a North Atlantic, 1/60 • simulation of the ocean circulation (NATL60). The data assimilation analysis is carried out with an ensemble Kalman filter. The results are assessed with root mean square errors, power spectrum density, and spatial coherence. They show that a significant part of the large scale SWOT errors is reduced. The filter analysis also reduces the small scale errors and allows for an accurate recovery of the energy of the signal down to 25 km scales. In addition, using the SWOT nadir data to adjust the SSH detrending further reduces the errors. |
author2 |
Institut des Géosciences de l’Environnement (IGE) Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ) ANR-17-CE01-0009,BOOST-SWOT,Vers des produits de la circulation océanique de surface à la résolution kilométrique : exploitation de la future mission altimétrique SWOT(2017) |
format |
Article in Journal/Newspaper |
author |
Metref, Sammy Cosme, Emmanuel Le Sommer, Julien Poel, Nora Brankart, Jean-Michel Verron, Jacques Navarro, Laura, Gómez |
author_facet |
Metref, Sammy Cosme, Emmanuel Le Sommer, Julien Poel, Nora Brankart, Jean-Michel Verron, Jacques Navarro, Laura, Gómez |
author_sort |
Metref, Sammy |
title |
Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation |
title_short |
Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation |
title_full |
Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation |
title_fullStr |
Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation |
title_full_unstemmed |
Reduction of Spatially Structured Errors in Wide-Swath Altimetric Satellite Data Using Data Assimilation |
title_sort |
reduction of spatially structured errors in wide-swath altimetric satellite data using data assimilation |
publisher |
HAL CCSD |
publishDate |
2019 |
url |
https://hal.science/hal-02414942 https://hal.science/hal-02414942/document https://hal.science/hal-02414942/file/Metref-al-2019.pdf https://doi.org/10.3390/rs11111336 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 2072-4292 Remote Sensing https://hal.science/hal-02414942 Remote Sensing, 2019, ⟨10.3390/rs11111336⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.3390/rs11111336 hal-02414942 https://hal.science/hal-02414942 https://hal.science/hal-02414942/document https://hal.science/hal-02414942/file/Metref-al-2019.pdf doi:10.3390/rs11111336 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.3390/rs11111336 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
11 |
container_start_page |
1336 |
_version_ |
1798851367010304000 |