On the 20 April 2010 the oil platform Deep Water Horizon in the Gulf of Mexico suffered an explosion during the final phases of drilling an exploratory well. As a result, an oil film covered the sea surface area of several thousand square kilometers. In the present paper the data of the Ku‐band Precipitation Radar, which operates at low incidence angles, were used to explore the oil spill event. The two‐scale model of the scattering surface was used to describe radar backscatter from the sea surface. The algorithm for retrieval of normalized radar cross section at nadir and the total slope variance of large‐scale waves compared to the wavelength of electromagnetic wave (22 mm) was developed for the Precipitation Radar swath. It is shown that measurements at low incidence angles can be used for oil spill detection. This is the first time that the dependence of mean square slope of large‐scale waves on wind speed has been obtained for oil slicks from Ku‐band data, and compared to mean square slope obtained by Cox and Munk from optical data.

Improvement of methods for satellite monitoring of the world ocean state is one of the most important areas of the remote sensing because of the influence the oceans have on the Earth's climate. Currently, only one parameter is measured on a regular basis on a global scale: the significant wave height which is obtained from spaceborne radar altimeter data. It is known that at small incidence angles within the framework of Kirchhoff approximation, the backscattering radar cross section depends mainly on the mean square slope (mss) of the sea surface; therefore, this parameter can be measured. The performed studies lead to the improvement of the methods for processing the data from a precipitation radar. We demonstrate that the mss of the large‐scale (compared to the radar wavelength) sea waves can be restored within the swath, that is, about 115 km wide. The aim of this work is to communicate these new possibilities to the broad research community involved in the studies of the oceans. In this paper, a review of the results is performed and the prospects for global monitoring are first shown. On the basis of the precipitation radar data, it becomes possible to measure global fields of sea wave slopes, which in turn will help scientists to analyze the processes of air‐sea interaction. Availability of this new mss parameter essentially doubles the amount of available descriptors of sea waves, which will advance the understanding of the processes occurring in the oceans.

The total mean square slope (mss) of large-scale (in comparison with the scale of radar wavelengths) ocean waves can describe the roughness of the ocean surface. This important parameter has found many applications and can be determined by the dependence of large-scale mss on azimuthal angles. The Surface Waves Investigation and Monitoring instrument onboard the China France Oceanography Satellite (CFOSAT) can provide a 2-D normalized backscattering radar cross section (NRCS) for 2-D global ocean-surface wave detection. In this article, the 2-D NRCS is used to calculate the total large-scale mss via two methods. The first method is constructed from regression, while the second scheme is derived from a three-solution method. Finally, the total large-scale mss is calculated using these methods, and the map of the distribution of the global total mss is presented for the first time. Our results show that the two sources of total large-scale mss obtained are consistent with each other. CFOSAT can provide a 2-D total large-scale mss map and be used as a new data resource for global applications.

The Doppler spectrum (DS) of the signal backscattered at the low incidence angles from the sea surface was measured by the Ka-band radar in an experiment on a marine oceanographic platform. The directional elevation spectrum of sea waves was measured simultaneously by a six-string wave gauge mounted on a platform. At low incidence angles the backscattering mechanism is quasi-specular, and DS of the backscattered signal is calculated in the Kirchhoff approximation with the antenna pattern being taken into account. In the case of pure wind sea, the parameters of the sea waves spectrum model (wind speed and fetch) were retrieved by 2-D optimization method from measured DS shift and width. Sea wave propagation direction was obtained from the azimuthal dependence of Doppler shift. Analytical dependence of DS shift and width on incidence angle calculated from the spectrum model is in a good agreement with the experiment for incidence angles from 0° to 12°. Close values of significant wave height, the average wave period, and the variance of orbital velocities were obtained from the retrieved model spectrum and from the spectrum directly measured by the string wave gauge, which also proves the correctness of DS model.

Orbital radars are used to monitor the state of the sea ice in the Arctic and Antarctic. The backscattering radar cross section (RCS) is used to determine the type of scattering surface. The power of the reflected signal depends on many factors, so the problem of separating sea ice and sea waves is not always unambiguous. Previous research has shown that microwave Doppler radar installed on aircrafts can be used to determine the boundary of sea ice. The width of the Doppler spectrum for wide or knife-like antenna beam depends on the statistical parameters of the reflecting surface, so sea ice and sea waves are easily separated. However, when installing a Doppler radar on a satellite, the spatial resolution becomes extremely low. In this research, we discuss the possibility of improving the spatial resolution by dividing the antenna footprint into elementary scattering cells. To do this, it is proposed to use the original incoherent synthesis procedure, which allows one to determine the dependence of the RCS on the incidence angle for an elementary scattering cell. Numerical modeling was performed and processing of model data confirmed that sea ice and sea waves are separated. The coefficient of kurtosis was used as a criterion in the algorithm. In addition, for sea waves, it is possible to determine the mean square slopes (mss) of large-scale waves, compared to the electromagnetic wavelength of sea waves along the sounding direction.

This paper presents the first results of sea ice detection using the data of Ka- and Ku-band radars at low incidence angles. A classification method based on an unsupervised K-means approach is applied to the arrays of the data for the Arctic and Antarctic regions. Comparison with Advanced Microwave Scanning Radiometer 2 (AMSR-2) data was performed, and the dependence of classification performance was evaluated for incidence angles from 0° to 18.15°. This paper evaluates the classification accuracy of sea ice detection based on Ku-band, Ka-band, and their combination. Preliminary results indicate that the classification based solely on Ku-band data achieves the best performance.