Significant wave height retrieval using the volumetric correlation data of SWOT KaRIn

This study proposes a new model for retrieving the significant wave height (SWH) only using the volumetric correlation data of Surface Water and Ocean Topography (SWOT) Ka-band Radar Interferometer (KaRIn). The colocated data used include European Centre for Medium-Range Weather Forecasts (ECMWF), Ocean Surface Current Analyses Real-time (OSCAR), Haiyang-2C (HY-2C) altimeter and National Data Buoy Center (NDBC) buoy data. The sensitivity of volumetric correlation on some dynamic environmental parameters was first analyzed. From the theoretic and data analysis, the volumetric correlation is only sensitive to SWH, but not sensitive to other parameters (wind speed, wind direction, mean wave direction, mean wave period, current speed, current direction and sea surface temperature). Then, a new model was proposed by relating SWH to volumetric correlation and incidence angle based on the analysis. Finally, the SWH retrievals from the proposed model were validated by three types of colocated data (ECMWF, HY-2C altimeter and NDBC buoy). Validations show SWH retrievals have a good agreement with the colocations. It also has a comparable accuracy to operational product in terms of standard deviation by comparing to ECMWF and HY-2C data, while exhibiting lower bias. It indicates the SWOT KaRIn data have the SWH retrieval capacity only using the volumetric correlation data. The SWH retrievals help for correcting the sea state bias for colocated SWOT KaRIn sea surface height product. Compared to existing models, this convenient model is more suitable for in orbit retrieval processing of satellite data.

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Publication Details

Journal
Geo-spatial Information Science
Published
2025-09-10
DOI
https://doi.org/10.1080/10095020.2025.2556275
Primary Topic
Ocean Waves and Remote Sensing
Type
article
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article

Significant wave height retrieval using the volumetric correlation data of SWOT KaRIn

Jingsong Yang, Yongjun Jia, Yiqi Wang, Zhiyang Jiang et al.
Geo-spatial Information Science
Ocean Waves and Remote Sensing
article

Significant wave height retrieval using the volumetric correlation data of SWOT KaRIn

Jingsong Yang, Yongjun Jia, Yiqi Wang, Zhiyang Jiang, Xiao Dong, Lin Ren, Limin Cui, Yi Zhang
article en

Abstract

This study proposes a new model for retrieving the significant wave height (SWH) only using the volumetric correlation data of Surface Water and Ocean Topography (SWOT) Ka-band Radar Interferometer (KaRIn). The colocated data used include European Centre for Medium-Range Weather Forecasts (ECMWF), Ocean Surface Current Analyses Real-time (OSCAR), Haiyang-2C (HY-2C) altimeter and National Data Buoy Center (NDBC) buoy data. The sensitivity of volumetric correlation on some dynamic environmental parameters was first analyzed. From the theoretic and data analysis, the volumetric correlation is only sensitive to SWH, but not sensitive to other parameters (wind speed, wind direction, mean wave direction, mean wave period, current speed, current direction and sea surface temperature). Then, a new model was proposed by relating SWH to volumetric correlation and incidence angle based on the analysis. Finally, the SWH retrievals from the proposed model were validated by three types of colocated data (ECMWF, HY-2C altimeter and NDBC buoy). Validations show SWH retrievals have a good agreement with the colocations. It also has a comparable accuracy to operational product in terms of standard deviation by comparing to ECMWF and HY-2C data, while exhibiting lower bias. It indicates the SWOT KaRIn data have the SWH retrieval capacity only using the volumetric correlation data. The SWH retrievals help for correcting the sea state bias for colocated SWOT KaRIn sea surface height product. Compared to existing models, this convenient model is more suitable for in orbit retrieval processing of satellite data.

Geo-spatial Information Science
Chinese Academy of Sciences (CN), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN)
Openalex Percentile: Top 75%
Ocean Waves and Remote Sensing
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