Deriving Deflection of the Vertical and Gravity Anomaly from SWOT/KaRIn Data Using an Optimized Discretization Method.
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| Title: | Deriving Deflection of the Vertical and Gravity Anomaly from SWOT/KaRIn Data Using an Optimized Discretization Method. |
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| Authors: | Guo, Hengyang1,2 (AUTHOR), Wan, Xiaoyun1,2,3 (AUTHOR) wanxy@cugb.edu.cn, Wu, Xing3,4 (AUTHOR) |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 9, p1360. 21p. |
| Subjects: | Discretization methods, Numerical differentiation, Gravitational fields, Ocean surface topography, Gravity anomalies, Geodetic techniques |
| Abstract: | Highlights: What are the main findings? An optimized discretization method (ODM) is developed to fully utilize the two-dimensional characteristics of SWOT/KaRIn data. It integrates multi-directional observations and higher-order numerical differentiation, providing a practical alternative method. It avoids complex covariance modeling and parameter estimation while achieving comparable accuracy. This makes the method easier to implement and more suitable for large-scale applications. The derived SWOT_DOV achieves high accuracy, with STDs of 1.60 μrad (north) and 2.02 μrad (east) against the SIO V32.1 model. Marine gravity anomaly (SWOT_GA) is derived using the inverse Vening-Meinesz formula. The STD of the differences between SWOT_GA and the NCEI shipborne gravity data is 3.85 mGal. Accuracy analyses show that high-quality gravity signals are mainly obtained in deep-ocean and offshore regions with gentle seafloor gradients. What are the implications of the main findings? The ODM provides a simple, efficient, and robust alternative to the LSC method while improving data utilization. Exploiting multi-directional and higher-order information is critical for fully leveraging wide-swath altimetry data. SWOT performs well in recovering marine gravity anomalies in the open ocean and can support future geodetic and oceanographic studies. The Surface Water and Ocean Topography (SWOT) mission carries a Ka-band interferometric radar altimeter (KaRIn), which enables high-resolution wide-swath measurements of sea surface height, providing new opportunities for deriving high-precision marine gravity fields. The discretization method used by the Scripps Institution of Oceanography (SIO) is one of the simplest methods for deriving deflections of the vertical (DOV), as it avoids parameter estimation and complex mathematical procedures. However, this method only uses adjacent observations for first-order differentiation and ignores diagonal directions, resulting in relatively low data utilization for SWOT/KaRIn data. The optimized discretization method is proposed to take advantage of the two-dimensional characteristics of KaRIn data. Multi-directional data is introduced to estimate the DOV (SWOT_DOV), and the numerical differentiation strategy is extended to higher orders. These significantly improve the solution quality. The standard deviation (STD) of the differences between SWOT_DOV and north_32.1 is 1.60 μrad, and that with east_32.1 is 2.02 μrad. Gravity anomalies are further derived using the inverse Vening-Meinesz formula. Validation using NCEI shipborne gravity data indicates an STD of 3.85 mGal. Further analyses considering seafloor topography gradient, depth, and offshore distance demonstrate that SWOT/KaRIn data have a stable capability to restore high-precision marine gravity field features. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 193715391 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Deriving Deflection of the Vertical and Gravity Anomaly from SWOT/KaRIn Data Using an Optimized Discretization Method. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Guo%2C+Hengyang%22">Guo, Hengyang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wan%2C+Xiaoyun%22">Wan, Xiaoyun</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> wanxy@cugb.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Xing%22">Wu, Xing</searchLink><relatesTo>3,4</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. May2026, Vol. 18 Issue 9, p1360. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Discretization+methods%22">Discretization methods</searchLink><br /><searchLink fieldCode="DE" term="%22Numerical+differentiation%22">Numerical differentiation</searchLink><br /><searchLink fieldCode="DE" term="%22Gravitational+fields%22">Gravitational fields</searchLink><br /><searchLink fieldCode="DE" term="%22Ocean+surface+topography%22">Ocean surface topography</searchLink><br /><searchLink fieldCode="DE" term="%22Gravity+anomalies%22">Gravity anomalies</searchLink><br /><searchLink fieldCode="DE" term="%22Geodetic+techniques%22">Geodetic techniques</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? An optimized discretization method (ODM) is developed to fully utilize the two-dimensional characteristics of SWOT/KaRIn data. It integrates multi-directional observations and higher-order numerical differentiation, providing a practical alternative method. It avoids complex covariance modeling and parameter estimation while achieving comparable accuracy. This makes the method easier to implement and more suitable for large-scale applications. The derived SWOT_DOV achieves high accuracy, with STDs of 1.60 μrad (north) and 2.02 μrad (east) against the SIO V32.1 model. Marine gravity anomaly (SWOT_GA) is derived using the inverse Vening-Meinesz formula. The STD of the differences between SWOT_GA and the NCEI shipborne gravity data is 3.85 mGal. Accuracy analyses show that high-quality gravity signals are mainly obtained in deep-ocean and offshore regions with gentle seafloor gradients. What are the implications of the main findings? The ODM provides a simple, efficient, and robust alternative to the LSC method while improving data utilization. Exploiting multi-directional and higher-order information is critical for fully leveraging wide-swath altimetry data. SWOT performs well in recovering marine gravity anomalies in the open ocean and can support future geodetic and oceanographic studies. The Surface Water and Ocean Topography (SWOT) mission carries a Ka-band interferometric radar altimeter (KaRIn), which enables high-resolution wide-swath measurements of sea surface height, providing new opportunities for deriving high-precision marine gravity fields. The discretization method used by the Scripps Institution of Oceanography (SIO) is one of the simplest methods for deriving deflections of the vertical (DOV), as it avoids parameter estimation and complex mathematical procedures. However, this method only uses adjacent observations for first-order differentiation and ignores diagonal directions, resulting in relatively low data utilization for SWOT/KaRIn data. The optimized discretization method is proposed to take advantage of the two-dimensional characteristics of KaRIn data. Multi-directional data is introduced to estimate the DOV (SWOT_DOV), and the numerical differentiation strategy is extended to higher orders. These significantly improve the solution quality. The standard deviation (STD) of the differences between SWOT_DOV and north_32.1 is 1.60 μrad, and that with east_32.1 is 2.02 μrad. Gravity anomalies are further derived using the inverse Vening-Meinesz formula. Validation using NCEI shipborne gravity data indicates an STD of 3.85 mGal. Further analyses considering seafloor topography gradient, depth, and offshore distance demonstrate that SWOT/KaRIn data have a stable capability to restore high-precision marine gravity field features. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18091360 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1360 Subjects: – SubjectFull: Discretization methods Type: general – SubjectFull: Numerical differentiation Type: general – SubjectFull: Gravitational fields Type: general – SubjectFull: Ocean surface topography Type: general – SubjectFull: Gravity anomalies Type: general – SubjectFull: Geodetic techniques Type: general Titles: – TitleFull: Deriving Deflection of the Vertical and Gravity Anomaly from SWOT/KaRIn Data Using an Optimized Discretization Method. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Guo, Hengyang – PersonEntity: Name: NameFull: Wan, Xiaoyun – PersonEntity: Name: NameFull: Wu, Xing IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 9 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
