Wave Azimuth Cutoff Compensation Method and the Multisatellite Networking Mode of SAR

Synthetic aperture radars(SARs)encounter the azimuth cutoff problem when observing sea waves.Consequently,SARs can only capture the waves with wavelengths larger than the cutoff wavelength and lose the information of waves with smaller wavelengths.To increase the accuracy of SAR wave observations,this paper investigates an azimuth cutoff compensation method based on the simulated multiview SAR wave synchronization data obtained by the collaborative observation via networked satellites.Based on the simulated data and the equivalent multiview measured data from Sentinel-1 virtual networking,the method is verified and the cutoff wavelengths decrease by 16.40%and 14.00%.The biases of the inversion significant wave height with true values decrease by 0.04 m and 0.14 m,and the biases of the mean wave period decrease by 0.17 s and 0.22 s,respectively.These results demonstrate the effectiveness of the azimuth cutoff compensation method.Based on the azimuth cutoff compensation method,the multisatellite SAR networking mode for wave observations are discussed.The highest compensation effect is obtained when the combination of azimuth angle is(95°,115°,135°),the orbital intersection angle is(50°,50°),and three or four satellites are used.The study of the multisatellite networking mode in this paper can provide valuable references for the compensation of azimuth cutoff and the observation of waves by a multisatellite network.

Multisatellite observations of smaller mesoscale eddy generation in the Kuroshio Extension

Smaller mesoscale eddies(SMEs)have an important effect on the transmission of ocean temperatures,salinity,energy,and marine biochemical processes.However,traditional altimeters,the dominant sensors used to identify and track eddies,have made it challenging to observe SMEs accurately due to resolution limitations.Eddies drive local upwelling or downwelling,leaving signatures on sea surface temperatures(SSTs)and chlorophyll concentrations(Chls).SST can be observed by spaceborne infrared sensors,and Chl can be measured by ocean color remote sensing.Therefore,multisatellite observations provide an opportunity to obtain information to characterize SMEs.In this paper,an eddy detection algorithm based on SST and Chl images is proposed,which identifies eddies by characterizing the spatial and temporal distribution of SST and Chl data.The algorithm is applied to characterize and analyze SMEs in the Kuroshio Extension.Statistical results on their distribution and seasonal variability are shown,and the formation processes are preliminarily discussed.SMEs generation may be contributed by horizontal strain instability,the interaction of topographic obstacles and currents,and wind stress curl.