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Analysis of factors influencing significant wave height retrieval and performance improvement in spaceborne GNSS-R

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Abstract

As an emerging observational method, spaceborne global navigation satellite system-reflectometry (GNSS-R) has been applied recently for significant wave height (SWH) retrieval. However, the complexity of the sea surface and the influence of multiple potential factors have been constraining the accuracy of SWH retrieval. This study verified the effect of sea surface temperature (SST), sea surface salinity (SSS), and seasonal variation on cyclone-GNSS (CYGNSS) observables for the first time. After controlling for the SWH, the CYGNSS observables exhibit a dependence on SST and SSS, where the dependence on SST dominates. The correlation coefficient (R) between SST and CYGNSS observables is the highest in 3.5–4 m, which is 0.53. In addition, the geographical distribution of retrieval bias exhibits seasonality. Therefore, seasonal factors can provide an additional contribution to SWH retrieval. SWH retrieval is based on the multilayer perceptron. The European center for medium-range weather forecast reanalysis 5th Generation SWH data were used as the reference for the computation of retrieval performance metrics. The results show that after considering SST, salinity, and season, the root mean square error (RMSE) of the retrieved SWH decreases from 0.65 to 0.48 m and the R increases from 0.66 to 0.83. The retrievals were compared to the ground truth measurements from the National Data Buoy Center buoys; the RMSE decreased from 0.52–1.07 m to 0.30–0.61 m, and the R increased from 0.44–0.71 to 0.60–0.78.

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Availability of data and materials

The CYGNSS data presented in this study are openly available in PODAA at https://podaac.jpl.nasa.gov/dataset/CYGNSS_L1_V3.1. The SWH data are openly available in ECMWF at https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysisera5-single-levels. The SSS data are openly available in the Multi-Mission Optimally Interpolated SSS Global Dataset V1 at https://search.earthdata.nasa.gov/.

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Acknowledgements

We express our gratitude to the CYGNSS team for providing the Level 1 data, which is publicly accessible via the NASA EOSDIS Physical Oceanography Distributed Active Archive Center. In addition, we would like to thank the University of Hawaii for providing the SSS data, and ECMWF for providing the SWH data.

Funding

This research was supported by the National Science Fund for Distinguished Young Scholars (Grant No. 41825009), the National Natural Science Foundation of China (Grant No. 42074029), and the Fundamental Research Funds for the Central Universities (Grant No. 2042023kfyq01).

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Authors and Affiliations

  1. School of Geodesy and Geomatics, Hubei Luojia Laboratory, Wuhan University, Wuhan, 430079, China

    Zheng Li, Fei Guo, Xiaohong Zhang, Yu Guo & Zhiyu Zhang

  2. Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan, 430079, China

    Xiaohong Zhang

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  1. Zheng Li
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  4. Yu Guo
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Contributions

Conceptualization, ZL and FG; methodology, ZL; software, YG; validation, ZL, FG, ZZ; formal analysis, ZL, XZ and FG; investigation, ZL; resources, ZL and FG; data curation, ZL; writing—original draft preparation, ZL; writing—review and editing, FG and ZL; visualization, ZL; supervision, FG; project administration, FG, XZ; funding acquisition, FG, XZ.

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Correspondence to Fei Guo.

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Li, Z., Guo, F., Zhang, X. et al. Analysis of factors influencing significant wave height retrieval and performance improvement in spaceborne GNSS-R. GPS Solut 28, 64 (2024). https://doi.org/10.1007/s10291-023-01605-3

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