Interactions between surface waves and ocean currents over the northwest Atlantic during Hurricanes Earl and Igor (2010) are investigated using a coupled wave‐circulation model and observational data. Our results show that the coupled model improves the model performance in simulating the surface waves, sea level, water temperature, and salinity. By including the wave‐current interactions (WCIs), the maximum significant wave heights (SWHs) are reduced by more than 10% along the storm tracks and more than 20% over eddies. In the Gulf of Maine (GoM), the simulated SWHs and peak wave periods are also modulated by strong tidal currents. Surface waves, in turn, reduce the semidiurnal tidal amplitudes (up to ∼9%) and currents (up to ∼40%) in the GoM due mainly to the wave‐enhanced bottom stress. Surface waves also increase the peak storm surge (up to ∼19%) during these hurricanes, which is mostly attributed to the wave‐induced forces through Stokes drift and wave dissipation but slightly compensated by the wave‐enhanced bottom stress. The hurricane‐driven surface currents are modulated by waves toward the clockwise direction with a decrease in current speeds of more than ∼60%. This is attributed to the reduced current shear and density gradient resulting from mixing enhanced by wave breaking, but compensated by wave‐induced forces. Salinity and temperature are also modulated by surface waves, mostly through the wave‐induced forces and enhanced mixing by wave breaking. Overall, the coupled model produces higher surface salinity and stronger surface cooling due to the inclusion of the WCIs.

The HY-2B scatterometer (HSCAT-B) has now completed a one-year orbit. The instrument was declared operational after six months of in-orbit testing. The ocean wind field products are routinely being made available to the global science community. The HY-2B will work with the HY-2A to provide the Ku-band sea surface observations on a long-term scale, and this collaboration is expected to be important for disaster prevention and mitigation, as well as globally focused climate change research. However, to obtain reasonable evaluations of the system's functional, performance, and instrument stability results, the temperature, internal calibration parameters, attitude angles, and normalized radar cross section (NRCS) of the instrument were rigorously analyzed during the in-orbit tests. This study provided an overview of the six-month in-orbit testing process results. The temperature levels of some important parts of the scatterometer were found to meet the design requirements. The internal calibration and noise power had shown similar trends and were both within the normal range. The attitude angles, which mainly included the roll and pitch, had displayed variations within a very small scope. The evaluation results of the Amazon rainforest observations indicated that the scatterometer instrument had met all the design requirements and had established a good database for geophysical processing.

The Chinese HY-2A satellite microwave scatterometer (HSCAT) is designed to measure the ocean surface wind vector with a large observation swath. HSCAT is a Ku-band scatterometer that has continuously observing the earth's surface for more than 6 years. Approximately, 30,000 orbit revolutions of scientific data are archived in its ground application system. To further understand the characteristics of the instrument, deeper analyses of these scientific data must be carried out. Currently, the geolocation accuracy of the normalized radar cross section (NRCS) has yet to be documented. However, geolocation errors can cause significant measurement bias, and have large impacts on the calibration and validation results. In this paper, the coastline crossing detection method is used to evaluate the geolocation errors of the NRCS data. Some coastal areas and islands where the NRCS data have large gradients are selected for the geolocation error analysis. The coastline inflection points can be identified on the basis that the radar backscatter of land and water exhibits a significant difference when the ocean surface wind speed is relatively low. The longitudes and latitudes of these points from different time periods are then fit to the global self-consistent hierarchical high-resolution shorelines map. The comparison results show that the overall distance error of HSCAT is approximately 2.59 km. This geolocation accuracy meets the instrument design requirements. The sources of geolocation errors are also analyzed in this paper in order to improve the geolocation accuracy.

The normalized radar cross section (NRCS) of microwave backscattering from a rough sea surface can be described by a composite Bragg scattering (CBS) model, which is a combination of a two-scale backscatter model and a geometric optics model. For small local radar incidence angles that are smaller than a given angle setting, the two-scale backscattering mechanism of the sea surface is replaced by a geometric optics solution for specular reflection. In this study, an optimized setting of 18 degrees for the small incidence angle is determined by comparing the NRCSs between 52 RADARSAT-2 (R2) synthetic aperture radar (SAR) images and the CBS model with simultaneous sea surface wind derived by meteorological mooring buoys located in the northern South China Sea (SCS). By using the CBS model with the optimized incidence angle setting of 18 degrees and the nearly simultaneous wind directions of the Advanced Scatterometer (ASCAT) as the input, sea surface wind speeds are retrieved from 46 R2 SAR images at C-band and from 2 COSMO-SkyMed (CSK) SAR images at X-band for the application study. The average root mean square error (RMSE) of the C-band R2 SAR retrieval results validated against nearly simultaneous measurements of ASCAT is 1.5 m/s, while the same value is 1.6 m/s for the X-band CSK SAR image. The results also indicate that the optimized small incidence angle setting of the CBS model found in this study is relatively reliable under sea surface wind speed conditions less than 14.0 m/s.

The goal of the paper is to reveal discrepancies of turbulent variables over different surfaces (sea, island, land) based on the measurements taken on three towers during (including before and after) seven typhoon episodes from 2008 to 2018. The atmospheric stability, turbulent spectrum, friction velocity, turbulent kinetic energy, dissipative heating, and gust factor are examined. The similar turbulent characteristics over sea and on the island reinforce the previous conclusion that the turbulent measurements on the island mainly represent the sea surface. The turbulent characteristics over sea and on land are very different due to the different underlying surface roughness. The unstable (stable) condition dominates on the sea (land) surface. Turbulent spectra both over sea and on land follow the canonical Kolmogorov’s power law with the −5/3 slope. The cospectra on land are more peaked than those over sea. All of the friction velocity, turbulent kinetic energy, and dissipative heating increase with increasing 10 m wind speed, and those on land are much larger than those over sea. The distributions of gust factors widen and shift to higher on land than those over sea. The distributions of gust factors at heights of 10 m and 40 m are biased to higher values than those at heights of 160 m and 320 m on land.

Sea surface temperature (SST), sea surface wind speed (SSW), and total column water vapor (WV) are critical parameters for understanding ocean-atmosphere interactions. While conventional microwave retrieval methods typically rely on C- and X-band channels, this study proposes a Physics-Informed Coupled Neural Network (PIC-NN) designed to jointly retrieve all three parameters using only K- and Ka-band brightness temperatures. The model incorporates two key components: bidirectional coupling connections, which explicitly encode known physical interactions among SST, SSW, and WV, and an adaptive scaling factor loss function that balances the multi-task learning process. Validated against ERA5 reanalysis data and multiple in-situ datasets, PIC-NN achieves SST retrieval accuracy comparable to that of the operational AMSR-2 product (which uses lower frequencies). Moreover, it significantly outperforms AMSR-2 in retrieving SSW and WV, achieving STD reductions of 19.0% and 23.7%, respectively. Ablation studies confirm the contribution of each model component, and comparisons with traditional methods highlight the importance of modeling nonlinearity and physical coupling. Further validated on an in-orbit high-frequency payload, this work demonstrates the robust generalization of multi-parameter retrievals using high-frequency bands alone. Under potential constraints of low-frequency spectrum scarcity or specific payload designs restricted to high frequencies, this approach provides a viable solution for accurately extracting key ocean-atmosphere parameters.