Sea Surface Ka-Band Doppler Measurements: Analysis and Model Development

Multi-year field measurements of sea surface Ka-band dual-co-polarized (vertical transmit–receive polarization (VV) and horizontal transmit–receive polarization (HH)) radar Doppler characteristics from an oceanographic platform in the Black Sea are presented. The Doppler centroid (DC) estimated using the first moment of 5 min averaged spectrum, corrected for measured sea surface current, ranges between 0 and ≈1 m/s for incidence angles increasing from 0 to 70∘ . Besides the known wind-to-radar azimuth dependence, the DC can also depend on wind-to-dominant wave direction. For co-aligned wind and waves, a negative crosswind DC residual is found, ≈−0.1 m/s, at ≈20 ∘ incidence angle, becoming negligible at ≈ 60 ∘ , and raising to, ≈+0.5 m/s, at 70∘ . For our observations, with a rather constant dominant wave length, the DC is almost wind independent. Yet, results confirm that, besides surface currents, the DC encodes an expected wave-induced contribution. To help the interpretation, a two-scale model (KaDOP) is proposed to fit the observed DC, based on the radar modulation transfer function (MTF) previously developed for the same data set. Assuming universal spectral shape of energy containing sea surface waves, the wave-induced DC contribution is then expressed as a function of MTF, significant wave height, and wave peak frequency. The resulting KaDOP agrees well with independent DC data, except for swell-dominated cases. The swell impact is estimated using the KaDOP with a modified empirical MTF

Keyword(s)

radar, scatterometer, ocean, backscatter, Doppler shift, Doppler centroid, sea surface current, wind drift, modulation, transfer function, empirical model

Full Text

FilePagesSizeAccess
Publisher's official version
249 Mo
Supplementary File 1
-11 Ko
Supplementary File 2
-15 Ko
How to cite
Yurovsky Yury, Kudryavtsev Vladimir, Grodsky Semyon, Chapron Bertrand (2019). Sea Surface Ka-Band Doppler Measurements: Analysis and Model Development. Remote Sensing. 11 (7). 839 (24p.). https://doi.org/10.3390/rs11070839, https://archimer.ifremer.fr/doc/00489/60077/

Copy this text