Data-Driven Calibration Algorithm and Pre-Launch Performance Simulations for the SWOT Mission Article Swipe
Gérald Dibarboure
,
Clément Ubelmann
,
Benjamin Flamant
,
Frédéric Briol
,
Eva Peral
,
Geoffroy Bracher
,
Oscar Vergara
,
Yannice Faugère
,
F. Soulat
,
Nicolas Picot
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/rs14236070
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/rs14236070
The Surface Water and Ocean Topography (SWOT) mission will be affected by various sources of systematic errors, which are correlated in space and in time. Their amplitude before calibration might be as large as tens of centimeters, i.e., able to dominate the mission error budget. To reduce their magnitude, we developed so-called data-driven (or empirical) calibration algorithms. This paper provided a summary of the overall problem, and then presented the calibration framework used for SWOT, as well as the pre-launch performance simulations. We presented two complete algorithm sequences that use ocean measurements to calibrate KaRIN globally. The simple and robust Level-2 algorithm was implemented in the ground segment to control the main source of error of SWOT’s hydrology products. In contrast, the more sophisticated Level-3 (multi-mission) algorithm was developed to improve the accuracy of ocean products, as well as the one-day orbit of the SWOT mission. The Level-2 algorithm yielded a mean inland error of 3–6 cm, i.e., a margin of 25–80% (of the signal variance) with respect to the error budget requirements. The Level-3 algorithm yielded ocean residuals of 1 cm, i.e., a variance reduction of 60–80% with respect to the Level-2 algorithm.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs14236070
- https://www.mdpi.com/2072-4292/14/23/6070/pdf?version=1669958340
- OA Status
- gold
- Cited By
- 34
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4311011786
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4311011786Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs14236070Digital Object Identifier
- Title
-
Data-Driven Calibration Algorithm and Pre-Launch Performance Simulations for the SWOT MissionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-30Full publication date if available
- Authors
-
Gérald Dibarboure, Clément Ubelmann, Benjamin Flamant, Frédéric Briol, Eva Peral, Geoffroy Bracher, Oscar Vergara, Yannice Faugère, F. Soulat, Nicolas PicotList of authors in order
- Landing page
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https://doi.org/10.3390/rs14236070Publisher landing page
- PDF URL
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https://www.mdpi.com/2072-4292/14/23/6070/pdf?version=1669958340Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2072-4292/14/23/6070/pdf?version=1669958340Direct OA link when available
- Concepts
-
SWOT analysis, Algorithm, Calibration, Computer science, Remote sensing, Variance (accounting), Environmental science, Geology, Mathematics, Statistics, Accounting, Business, MarketingTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
34Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 11, 2024: 16, 2023: 7Per-year citation counts (last 5 years)
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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