Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment
The SWOT satellite, carrying the KaRIN first wide-swath onboard altimeter, was launched in December 2022, and has now delivered more than a year of surface water elevation data over the ocean and inland lakes/rivers. These data are affected by systematic errors which constitute the dominant part of...
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MDPI AG
2024-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/19/3558 |
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| author | Clément Ubelmann Gérald Dibarboure Benjamin Flamant Antoine Delepoulle Maxime Vayre Yannice Faugère Pierre Prandi Matthias Raynal Frédéric Briol Geoffroy Bracher Emeline Cadier |
| author_facet | Clément Ubelmann Gérald Dibarboure Benjamin Flamant Antoine Delepoulle Maxime Vayre Yannice Faugère Pierre Prandi Matthias Raynal Frédéric Briol Geoffroy Bracher Emeline Cadier |
| author_sort | Clément Ubelmann |
| collection | DOAJ |
| description | The SWOT satellite, carrying the KaRIN first wide-swath onboard altimeter, was launched in December 2022, and has now delivered more than a year of surface water elevation data over the ocean and inland lakes/rivers. These data are affected by systematic errors which constitute the dominant part of the error budget at scales larger than a few thousands of kilometers. Some strategies for their estimation and calibration were explored during the pre-launch studies with performance estimations. Now, based on the real data, we propose in this study to assess the systematic error budget with statistical methods relying on spectral and co-spectral analysis. From this assessment, suggesting very low error levels (below requirements), we propose the implementation of the calibration algorithms at Level-2 and Level-3 with a few minor adjustments justified by the error spectra. The calibrated products are then validated with usual CalVal metrics. |
| format | Article |
| id | doaj-art-d0930e0c23ed41b08a5631bafbbb20f1 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-d0930e0c23ed41b08a5631bafbbb20f12025-08-20T01:47:34ZengMDPI AGRemote Sensing2072-42922024-09-011619355810.3390/rs16193558Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight AssessmentClément Ubelmann0Gérald Dibarboure1Benjamin Flamant2Antoine Delepoulle3Maxime Vayre4Yannice Faugère5Pierre Prandi6Matthias Raynal7Frédéric Briol8Geoffroy Bracher9Emeline Cadier10Datlas, 38000 Grenoble, FranceCentre National d’Etudes Spatial, 31401 Toulouse, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceCentre National d’Etudes Spatial, 31401 Toulouse, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceCentre National d’Etudes Spatial, 31401 Toulouse, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceCollecte Localisation Satellites, 31520 Ramonville Saint-Agne, FranceThe SWOT satellite, carrying the KaRIN first wide-swath onboard altimeter, was launched in December 2022, and has now delivered more than a year of surface water elevation data over the ocean and inland lakes/rivers. These data are affected by systematic errors which constitute the dominant part of the error budget at scales larger than a few thousands of kilometers. Some strategies for their estimation and calibration were explored during the pre-launch studies with performance estimations. Now, based on the real data, we propose in this study to assess the systematic error budget with statistical methods relying on spectral and co-spectral analysis. From this assessment, suggesting very low error levels (below requirements), we propose the implementation of the calibration algorithms at Level-2 and Level-3 with a few minor adjustments justified by the error spectra. The calibrated products are then validated with usual CalVal metrics.https://www.mdpi.com/2072-4292/16/19/3558wide-swath altimetrySWOTcalibration |
| spellingShingle | Clément Ubelmann Gérald Dibarboure Benjamin Flamant Antoine Delepoulle Maxime Vayre Yannice Faugère Pierre Prandi Matthias Raynal Frédéric Briol Geoffroy Bracher Emeline Cadier Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment Remote Sensing wide-swath altimetry SWOT calibration |
| title | Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment |
| title_full | Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment |
| title_fullStr | Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment |
| title_full_unstemmed | Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment |
| title_short | Data-Driven Calibration of SWOT’s Systematic Errors: First In-Flight Assessment |
| title_sort | data driven calibration of swot s systematic errors first in flight assessment |
| topic | wide-swath altimetry SWOT calibration |
| url | https://www.mdpi.com/2072-4292/16/19/3558 |
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