Global Ocean Wave Measurements Using Complex Synthetic Aperture Radar Data

Schulz‐Stellenfleth, Johannes; Lehner, Susanne; Hoja, Danielle

doi:10.1061/40604(273)18

Cited by 4 publications

(2 citation statements)

References 61 publications

(139 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is due to the Bragg scattering of the short capillary waves in the dimension of centimeters, produced by wind stress, which allows extraction of wave and wind parameters from radar imagery [3][4][5].…”

Section: Meteo-marine Parameters In the Baltic Sea In Relation To Synmentioning

confidence: 99%

Meteo-Marine Parameters from Sentinel-1 SAR Imagery: Towards Near Real-Time Services for the Baltic Sea

et al. 2018

View full text Add to dashboard Cite

Abstract:A method for estimating meteo-marine parameters from satellite Synthetic Aperture Radar (SAR) data, intended for near-real-time (NRT) service over the Baltic Sea, is presented and validated. Total significant wave height data are retrieved with an empirical function CWAVE_S1-IW, which combines spectral analysis of Sentinel-1A/B Interferometric Wide swath (IW) subscenes with wind data derived with common C-Band Geophysical Model Functions (GMFs). In total, 15 Sentinel-1A/B scenes (116 acquisitions) over the Baltic Sea were processed for comparison with off-shore sea state measurements (52 collocations) and coastal wind measurements (357 colocations). Sentinel-1 wave height was spatially compared with WAM wave model results (Copernicus Marine Environment Monitoring Service (CMEMS). The comparison of SAR-derived wave heights shows good agreement with measured wave heights correlation r of 0.88 and with WAM model (r = 0.85). The wind speed estimated from SAR images yields good agreement with in situ data (r = 0.91). The study demonstrates that the wave retrievals from Sentinel-1 IW data provide valuable information for operational and statistical monitoring of wave conditions in the Baltic Sea. The data is valuable for model validation and interpretation in regions where, and during periods when, in situ measurements are missing. The Sentinel-1 A/B wave retrievals provide more detailed information about spatial variability of the wave field in the coastal zone compared to in situ measurements, altimetry wave products and model forecast. Thus, SAR data enables estimation of storm locations and areal coverage. Methods shown in the study are implemented in NRT service in German Aerospace Center's (DLR) ground station Neustrelitz.

show abstract

Section: Meteo-marine Parameters In the Baltic Sea In Relation To Synmentioning

confidence: 99%

Meteo-Marine Parameters from Sentinel-1 SAR Imagery: Towards Near Real-Time Services for the Baltic Sea

et al. 2018

View full text Add to dashboard Cite

show abstract

“…For surface waves, it is likely to improve its focus by adjusting the focus setting. However, due to the rather intricate motion of surface waves [14,15], it is generally difficult to directly obtain its optimum focus setting.…”

Section: Introductionmentioning

confidence: 99%

Airborne SAR Imaging Algorithm for Ocean Waves Based on Optimum Focus Setting

et al. 2019

View full text Add to dashboard Cite

Ocean waves are the richest texture on the sea surface, from which valuable information can be inversed. In general, the Synthetic Aperture Radar (SAR) images of surface waves will inevitably be distorted due to the intricate motion of surface waves. However, commonly used imaging algorithms do not take the motion of surface waves into consideration. Therefore, surface waves on the obtained SAR images are rather blurred. To solve this problem, an airborne SAR imaging algorithm for ocean waves based on optimum focus setting is proposed in this paper. Firstly, in order to obtain the real azimuth phase speed of dominant wave, the geometric and scanning distortion in the blurred SAR image is calibrated. Subsequently, according to the SAR integration time and wavelength of the dominant wave, a proper focus setting variation section is selected. Afterwards, all the focus settings in this variation section are used to refocus the image, which are then compared to decide the optimum focus setting for dominant wave. Finally, by redesigning the azimuth matched filter using this optimum focus setting, a well-focused SAR image for the dominant wave can be obtained. The proposed algorithm is applied to both simulation and field data, and SAR images of surface waves are obtained. Furthermore, the obtained images are compared with those obtained with a zero-focus setting. The comparison shows that the focus of surface waves is significantly improved, which verifies the effectiveness of the proposed algorithm. Finally, how to choose the appropriate focus setting variation section under different parameters and the applicability of the algorithm are analyzed.

show abstract