Mapping Radial Ocean Surface Currents in the Outer Core of Hurricane Maria From Synthetic Aperture Radar Doppler Measurements

Spaceborne synthetic aperture radar (SAR) Doppler shift measurements have been used for remote sensing of ocean surface currents during nonstorm events. However, mapping strong currents under storm conditions is still a challenging and unsolved issue. In this study, we attempt to retrieve radial cur...

Full description

Bibliographic Details
Main Authors: Shengren Fan, Biao Zhang, Vladimir Kudryavtsev, William Perrie
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10365489/
Description
Summary:Spaceborne synthetic aperture radar (SAR) Doppler shift measurements have been used for remote sensing of ocean surface currents during nonstorm events. However, mapping strong currents under storm conditions is still a challenging and unsolved issue. In this study, we attempt to retrieve radial current velocities from Sentinel-1A SAR Doppler shifts acquired over the outer core regions of Hurricane Maria for the first time. In these areas, the maximum wind speed is 28.7 m/s. Doppler shifts arising from the scalloping effect are first calculated using a linear fitting method. The nonzero Doppler shift measurements over the land within SAR scenes are then used to estimate Doppler shifts caused by antenna electronic mispointing and residual error. Finally, we compute sea-state-induced Doppler shifts (wave Doppler) based on our recently dual copolarization Doppler velocity (DPDop) model. The retrieved radial current velocities are compared with collocated high-frequency radar measurements, and show a bias of 0.02 m/s and a root-mean-square error of 0.19 m/s. These results suggest that it is possible to retrieve reliable radial current velocities under high wind conditions, as the contributions of nongeophysical terms and sea state to the Doppler shifts can be accurately estimated and removed.
ISSN:2151-1535