A Joint Method for Wave and Wind Field Parameter Inversion Combining SAR with Wave Spectrometer Data

Abstract

Synthetic aperture radar (SAR) and wave spectrometer are common methods for observing the ocean wind field and waves on the sea surface, but both have limitations. Due to the influence of velocity bunching modulation, SAR wave observation is limited by the azimuth cut-off phenomenon. Meanwhile, SAR relies on an external wind direction source, so it is difficult for SAR to observe wind fields independently. There is no azimuthal cut-off phenomenon when the spectrometer observes the sea surface, but its azimuth resolution is much lower than SAR. Combining the above characteristics, the joint inversion of SAR and wave spectrometer for sea-state parameters becomes possible. In this paper, a joint method for wind field and wave parameter inversion combining SAR with spectrometer data is proposed. In this method for wave parameter inversion, the wave spectrum of the spectrometer was used as a first-guess spectrum of SAR wave spectrum inversion, the fit wave spectrum obtained by joint inversion and the modified wave spectrum of the spectrometer were fused to form a new spectrum, and the wave parameters were calculated. For wind field parameter inversion, wind direction was obtained using a wave spectrometer, and was used as the input of the SAR wind field inversion. Wind speed was obtained using the CMOD5.N method. Collocated data from Sentinel-1 SAR, the wave spectrometer, the National Data Buoy Center (NDBC) buoy, and the European Centre for Medium-Range Weather Forecasting (ECMWF) are used to verify the proposed method. Sea parameters retrieved from the spectrometer and SAR are compared to the buoy and ECMWF data. The results show that the root mean square errors of significant wave height, mean wave period, wind direction and wind speed are 0.37 m, 1.02 s, 22.7° and 1.06 m/s with ECMWF data, and 0.35 m, 0.78 s, 18.22° and 0.92 m/s with buoy data, respectively. By comparing the inversion results with the L2 products of SAR and SWIM, it can be concluded that the inversion accuracy of the joint method is higher in the middle and low sea conditions. Therefore, the joint inversion method for wind field and wave parameters proposed in this paper has good results, which verifies the accuracy of the joint inversion method.

Reconstruction of Wide Swath Significant Wave Height From Quasi‐Synchronous Observations of Multisource Satellite Sensors

“…Aouf et al. (2016) conducted a study on joint assimilation based on SAR and SWIM wave spectra, while Y. Wan et al, (2022) integrated SAR and SWIM data for joint retrieval of wave and wind field parameters. It is evident that the development of joint observations using SWIM and SAR is meaningful for more accurate ocean detection.…”

Can Sea Surface Waves Be Simulated by Numerical Wave Models Using the Fusion Data from Remote-Sensed Winds?

“…Although altimeter-measured waves are reliable for large-scale analyses, the spatial resolution of approximately 10 km following the satellite footprints does not satisfy the requirement for regional seas. An SAR could provide the wave spectrum with a fine spatial resolution (approximately 3 km), with a swath coverage of 100-300 km [19], and the Surface Wave Investigation and Monitoring (SWIM) [20] module onboard the CFOSAT is designed to obtain the wave spectrum with a spatial resolution of 18 km over global seas, and it also operates in TCs [21,22]. The validation of remote-sensed wind and wave products has been systematically studied; however, the applications for using these data are worthy of further study.…”

Joint Retrieval of Sea Surface Rainfall Intensity, Wind Speed, and Wave Height Based on Spaceborne GNSS-R: A Case Study of the Oceans near China

“…Wan et al studied the joint retrieval method of wave and wind field parameters by combining synthetic aperture radar (SAR) and spectrometer data. The results show that the joint method has better applicability in low and medium sea conditions [8]. Later, Wan et al proposed a method for the joint retrieval of wind field and wave parameters based on Sentinel-1 SAR single look complex (SLC) data.…”