Sea Surface Current Measurements Using Along-Track Interferometric SAR

Licentiate thesis, 2018

Ocean currents affect the weather, the climate and the marine ecosystem. Observing ocean currents is important for understanding the upper-ocean layer dynamics and its interaction with the other components of the climate system. In-situ measurements are sparse and their deployment and maintenance is costly. Satellite remote sensing with large spatial coverage offers a good complement to the in-situ observations.
In this work we have studied the spaceborne Along-Track Interferometric SAR (ATI-SAR) for measuring sea surface currents. The measurement principle is based on the fact that the phase difference between two SAR acquisitions is directly related to radial (line-of-sight) velocity of the illuminated surface. Previous studies based on similar systems were carried out in areas with well defined and strong tidal currents ( 1 -3 m /s). In this work we demonstrate the capability of ATI-SAR, through several study cases, in areas with weak currents ( <0.5 m /s). This is challenging for the satellite measurements of surface currents because it requires very accurate processing and retrieval algorithms. In addition, it has been found that wave motion contribution, systematically dominates the measured ATI-SAR radial velocity in these weak current areas. Estimation of the wave motion  contribution relies on high-resolution and accurate wind data. Thus, a wind speed retrieval algorithm from SAR is needed to support the ATI-SAR current retrieval. We have shown that with an appropriate processing of the ATI-SAR phase and with applying the necessary corrections to the measured velocity a good agreement with ocean circulation models is achieved (rmse = 0.1 m/s). These corrections include phase calibration and wind  compensation to correct for instrument and geophysical systematic errors, respectively. Finally, a novel method for removing the wind direction ambiguity, based on the ATI-SAR phase, is presented. In previous methods, the wind ambiguity removal was based on external information, e.g. an atmospheric model or on visual observation of wind shadows.