This article introduces the Harmony scientific workbench (SWB), a tool for modeling the multistatic polarimetric ocean observations of the European Space Agency (ESA) Earth Explorer 10 Harmony Mission. This work focuses on the retrieval of the mission’s radar-based level-2 (L2) geophysical data products, namely stress-equivalent wind at 10 m height (U10s) and total surface current (TSC) vectors. The retrieval uses simulated level-1 (L1) radar data, which is documented in a companion paper (part 1). Different inversions of the simulated L1 observations are tested. We demonstrate that the assumptions made in traditional scatterometric retrieval approaches do not always hold at the high resolutions [O (1 km)] at which Harmony will operate. In particular, wave-Doppler suffers from representation noise, which leads to incorrect estimates of surface currents. The incorporation of the mean cross section (MACS) and the spectral cutoff parameters improves the estimates of surface current substantially. In addition, iterative estimations with increasing resolution help to reduce the noise in the geophysical retrievals. Although it is possible to get close to 0.3-m/s root mean square error (RMSE) on the wind speed, and 0.1 m/s on the ocean currents at the scale of 1× 1 km, there are limits to geophysical model function (GMF)-type retrievals, as they are not able to fully account for ocean-surface characteristics such as the skewed and wavelength-dependent directional behavior of wave systems. Despite these limitations, our results indicate that Harmony will provide the world’s first accurate high-resolution ocean wind and current observations based on synthetic aperture radar (SAR) data. ... Read more

Oceans cover a significant part of the Earth's surface. The coupling between the upper ocean and the atmosphere is very complicated with defied theoretical understanding, while it is essential for climate studies, weather prediction, and marine ecosystems. With the advent of spaceborne Synthetic Aperture Radar (SAR) systems, surface signatures of ocean and atmospheric processes have been revealed. As winds blowing over the ocean excite the wind waves, all undulations of the ocean surface are assumed as waves in this study. The primary sources for ocean surface signatures in SAR images are waves that are created by the exertion of the local wind stress. Wind waves cause changes in the backscattered power due to three mechanisms: specular reflections, Bragg scattering, and a contribution from wave breaking. A statistical multi-static normalized radar cross-section (NRCS) background model in terms of the directional wave spectrum is developed, considering both Bragg and non-Bragg mechanisms for various polarization states. As the qualitative comparison between optical and SAR data reveals a significant correlation in sea surface signatures, a synthetic attempt is made to estimate the SAR signals from optical signatures. This is realized with the transformation of the wave spectrum in a nonuniform medium, as a consequence of surface currents, and varying near-surface wind fields. A comparison between modeled NRCS and observations is presented. This modulated NRCS model advances the quantitative interpretation of the upper ocean dynamics from satellite measurements. ... Read more

River width is an important indication for water storage, with the development of remote sensing techniques, estimating river width in a large area becomes possible. In this report, fully-focused SAR altimetry data with an advantage of high spatial resolution is applied to compute river width for the first time. Methodology developed based on morphologic characters of rivers and data features is validated in two different areas, the Netherlands and Vietnam, with good statistical results. ... Read more