Short-term sea level fluctuations prompted by abrupt atmospheric changes can be hazardous phenomena for coastal regions. We report on two such recent storm surges that occurred in 2020 on the shores of British Columbia, Canada. A rare concordance of ground-based and spaceborne sensors made it possible to observe these events with a variety of instruments: (1) a coastal oceanographic radar; (2) the synthetic aperture radar onboard satellite Sentinel-1B; and (3) a network of shoreside tide gauges. In the light of these case studies we show how satellite radar data can be used to complement the observation and interpretation of ground-based measurements in the context of “tsunami-like” oscillations.

On October 14, 2016, the coastal high-frequency radar system in Tofino (British Columbia, Canada) triggered an automatic tsunami warning based on the identification of abnormal surface current patterns. This occurred in the absence of any reported seismic event but coincided with a strong atmospheric perturbation, which qualified the event as meteotsunami. We reanalyze this case in the light of a new radar signal processing method, which was designed recently for inverting fast-varying sea surface currents from the complex voltage time series received on the antennas. This method, based on autoregressive modeling combined with a maximum entropy method, yields a dramatic improvement in both the signal-to-noise ratio and the quality of the surface current estimation for very short integration time. This makes it possible to evidence the propagation of a sharp wavefront of surface current during the event and to map its magnitude and arrival time over the radar coverage. We show that the amplitude and speed of the inferred residual current do not comply with a Proudman resonance mechanism but are consistent with the propagation of a low-pressure atmospheric front. This supports the hypothesis of a storm surge rather than a true meteotsunami to explain this event. Beyond this specific case, another outcome of the analysis is the promising use of HF radars as proxy’s for the characterization of atmospheric fronts.

Radar Wind Profilers (RWP) are well-established instruments for the probing of the atmospheric boundary layer, with the immense advantage of long-range and all-weather operation capability. One of their main limitations, however, is a relatively long integration time compared to other instruments such as lidars. In the context of L-band RWP we show that the use of Autoregressive (AR) modeling for the antenna signals combined with the Maximum Entropy Method (MEM) allows for a correct estimation of radial wind velocity profiles even with very short time samples. A systematical analysis of performance is made with the help of synthetic data. These numerical results are further confirmed by an experimental dataset acquired near the landing runways of Paris Charles de Gaulle (CDG) Airport, France, and validated using a colocated optical lidar at the Aerological station of Payerne, Switzerland. It is found that the AR-MEM approach can successfully derive wind estimates using integration times as short as 2.5 s where the classical spectral approach can barely provide any measurement.

Doppler radars are routinely used for the remote sensing of oceanic surface currents and atmospheric wind profiles. Even though they operate at different frequencies and address different media, they follow very similar processing for the extraction of measured velocities. In particular they both face the challenging issue of capturing geophysical phenomena which vary rapidly with respect to the typical integration time. Recently, the authors applied a non-spectral formalism based on autoregressive processes to model the backscattered time series obtained from High-Frequency oceanic radars. They showed that it allows to calculate Doppler spectra for very short integration times without losing in frequency resolution nor signal-to-noise ratio. We apply this technique to synthetic and experimental data within a common framework and show for the first time the strong potential of the method for the study of transient atmospheric phenomena.

The two-scale model (TSM) based on Bragg tilting is widely employed to model the normalized radar cross section (NRCS) from the sea surface in the microwave bands. It also leads to the compound distribution model when used to represent the distribution of intensity in high-resolution sea clutter. While the TSM satisfactorily describes the dynamical behavior of the polarized NRCS at moderate incidence angles for various sea states and radar frequencies, it fails to consistently describe the polarized sea clutter distribution in the upper microwave band. The hidden reason is an overestimation of the Bragg polarization ratio (PR) at larger local incidence angles. Following the concept of universal analytical scattering models and based on the experimental evidence of two independent X-band airborne data sets, we propose a simple correction to the facet NRCS which brings the PR in closer agreement to the observations and makes it analytically very close to the popular Thompson empirical model. This amended model preserves the simple structure of Bragg scattering; it admits one single extra parameter which makes a dynamical transition between the asymptotic Bragg and Kirchhoff regime depending on the sea state and the radar frequency. This allows to correctly describe the angular variations of the PR in the upper microwave regime (C-, X-, and Ku-bands) with minimala prioriinformation regarding the sea surface. Once this correction is incorporated in the TSM, a consistent modeling of the polarized sea clutter statistics can be obtained with the compound distribution model.

We show, using simple physical models, that a quantitative estimation of the volume fraction of marine oil slicks can be achieved from dual-polarization synthetic aperture radar (SAR) imagery. Volume fraction, which quantifies the proportion of seawater in oil in the case of a mixture, depends primarily on volume scattering mechanisms and is inferred from the polarization ratio in the L-band. A quantification algorithm is derived, namely, the volume fraction estimation algorithm that is applied to two experimental data sets acquired in the Mediterranean Sea during the POLLUPROOF'2015 exercise and in the North Sea during the NOFO'2015 experiment using the Office National d'Études et de Recherches Aérospatiales airborne L-band SETHI system. The resulting volume fraction maps of the quantification method are presented and discussed, opening new perspectives for marine oil slicks monitoring by means of dual-polarization SAR imagery.

We make a brief review of the state-of-the-art in modeling oil at sea in microwave co-polarized radar imagery. We introduce some simple physical models which can be used to evaluate the impact of oil on the Normalized Radar Cross Section (NRCS) or, conversely, to invert the oceanic parameters impacted by oils. Some preliminary results are shown at L and X bands.

We report recent results on the investigation of upwind/downwind asymmetries in microwave return from the sea surface. We first provide a brief bibliographic synthesis of experimental trends observed for the upwind/downwind of the Normalized Radar Cross Section. This analysis enables the characterization of the asymmetries with respect to the radar geometry, the polarization channel, the sea state and the radar frequency. We consider various physical mechanisms which can account for upwind/downwind asymmetry and investigate in detail the role of unbalanced facet tilting. Using reference wind-wave tank experimental measurements, we design a probability distribution for the steep and asymmetric facet slopes and combine it with a Two-Scale Model. This allows recovering the trends of the asymmetries described in the literature.

This paper aims at presenting a methodology for the absolute quantification of oil/water mixing from microwaves polarimetric SAR measurements. In this approach, the effective relative complex permittivity of observed surface is a key parameter for a quantitative estimation of the oil/water mixing. The scope of application of the method goes far beyond the sole quantification of the mixing and provides further understanding of some electromagnetic scattering processes at the sea surface.

This paper reports the first results inferred from the investigation of sea clutter azimuthal variations and their dependence on the radar electromagnetic frequency. We summarize the results derived from the study of SAR data acquired simultaneously at X- and L-band by ONERA (The French aerospace laboratory) and compare them to results stemming from other experiments in the literature. The conclusions drawn suggest that the azimuthal asymmetry is more pronounced at X than L band, potentially indicating that the directional asymmetry of the NRCS is gradually diminished as the frequency decreases. This seems to entail that the asymmetry is likely associated to the small scales of roughness whose electromagnetic returns are measured at X band and not at L band.

A simple extrapolation technique is proposed for the intercalibration of the Ku- and Ka-band altimeter data based on a recent analytical scattering model referred to as “GO4.” This method is tested with AltiKa and Jason2-Ku altimeters using one year of reprocessed data with the improved retracking algorithm ICENEW. The variations of the normalized radar cross section with respect to the main oceanic parameters are investigated in the Ku and Ka bands; the latter band is shown to have an increased sensitivity to wind speed, significant wave height as well as sea surface temperature. As a by-product of this analysis, we derive an original expression for the swell impact on the mean square slope, which allows to correct the GO4 model for the contribution of long waves. We show that the Ku/Ka prediction agrees within 0.25 dB with the respective levels of AltiKa and Jason2-Ku cross sections at wind speed larger than 4 m/s.

We investigate some temporal properties of the microwave backscattered field from the sea surface at low incidence, namely, the decorrelation time and the Doppler shift distribution. These quantities may have an important impact on the performances of the altimeter and synthetic aperture radar systems in Ku- and Ka-bands and must be accurately evaluated. In the framework of classical analytical scattering models and for realistic sea spectra, we obtain a simple expression for the decorrelation time with respect to the main sea state parameters and the scattering geometry. We further propose an original approach based on a time-domain estimator to evaluate the distribution of instantaneous Doppler shifts and the Doppler centroid. The evolution of the latter with the sea state and scattering angles is calculated and discussed. A procedure is proposed to recover the full two-sided Doppler spectrum. We discuss the use of the Doppler shift in view of the geophysical parameter retrieval at low incidence. We find that the surface wind vector can, in principle, be well estimated from the azimuthal variation of the Doppler shift, whereas the signature of the surface current is not sufficient to allow for its estimation.

The Ingara X-band fully polarimetric medium-grazing-angle sea-clutter data set was collected in the Australian maritime environment over an angular range of 360° in azimuth and from 15° to 45° in grazing. This paper reports further analysis of this data set, focusing on understanding the azimuth variation to enable improved simulation accuracy and extraction of relevant geophysical parameters. This includes some original properties of the co- and cross-polarized normalized radar cross section as a function of the scattering geometry and sea surface parameters. We also assess the performances and limitations of recent sea surface scattering models in the light of this rich data set.

We report on the study of an extensive fully-polarimetric X-band data set of airborne radar measurements collected in the Australian maritime environment, referred to as Ingara data. The grazing angles range from 15 to 45 degrees with a full 360 degree excursion in azimuth for various wind and sea state conditions. We unveil some original properties of the like- and cross-polarized radar cross section as a function of the scattering geometry and sea surface parameters. We also assess the performances and limitations of recent sea surface scattering models in the light of this rich data set.

We introduce a practical and accurate model, referred to as “GO4,” to describe near-nadir microwave scattering from the sea surface, and at the same time, we address the issue of the filtered mean square slope (mss) conventionally used in the geometrical optics model. GO4 is a simple correction of this last model, taking into account the diffraction correction induced by the rough surface through what we call an effective mean square curvature (msc). We evaluate the effective msc as a function of the surface wavenumber spectrum and the radar frequency and show that GO4 reaches the same accuracy as the physical optics model in a wide range of incidence and frequency bands with the sole knowledge of the mss and msc parameters. The key point is that the mss entering in GO4 is not the filtered but the total slope. We provide estimation of the effective msc on the basis of classical sea spectrum models. We also evaluate the effective msc from near-nadir satellite data in various bands and show that it is consistent with model predictions. Non-Gaussian effects are discussed and shown to be incorporated in the effective msc. We give some applications of the method, namely, the estimation of the total sea surface mss and the recalibration of relative radar cross sections.

We present simplified expressions for the cross-polarized backscatter of a randomly rough surface predicted by the second-order small-slope approximation (SSA2). The simplification is based on appropriate polynomial approximations of the SSA2 kernel function. We obtain numerically efficient expressions for the cross-polarized backscattering amplitude of a deterministic surface in the form of a single space integral involving only the surface elevation and the second (mixed) derivative of the surface elevation. The ensemble average normalized radar cross section is then derived under a Gaussian random process assumption for the surface. The resulting expression has the form of a Kirchhoff integral involving the roughness correlation function and its second- and fourth-order cross-derivatives. Further simplification is achieved for off-nadir observations using a high-frequency approximation; the result is an analytical formula involving only the resonant curvature and the radar-filtered mean square slope in the out-of-plane direction. A numerical validation of the simplified expressions is provided by comparison with exact SSA2 predictions in representative test cases. The dependence of cross-polarized backscattering on the incidence angle as well as wind speed and direction is then investigated for the case of a directional sea surface model. At near nadir incidence, a clear maximum in azimuth of the cross-polarized backscatter is observed for radar look directions 45° from the wind direction.

The GO-SSA-Extended model is an extension of the physical GO-SSA model with augmented range of validity. It is obtained through the addition of extra empirical terms. This improved model can predict the backscatter reflectivity from the sea surface for the full range of grazing and azimuthal angles. This model compares favorably with Xband experimental measurements (VV and HH polarization) acquired by the ONERA and DSTO.

Existing models for the short-wave spectrum of the sea surface are not consistent with microwave satellite data when multi-bands and multi-incidence data sets are considered. We devise a simple parametric model for the short-wave omnidirectional spectrum of the sea surface on the basis of a three-band (C, Ku, and Ka) and multi-incidence (low, moderate, and large) data set and an improved analytical scattering model, namely the non-Gaussian Weighted Curvature Approximation. This spectrum is also constrained by several optical measurements which provide a priori conditions on the total and filtered mean-square slopes. It is compared with classical models such as Elfouhaily and Kudryavtsev unified curvature spectra. Significant differences are observed at wave numbers corresponding to the range of decimeter scales. The new spectrum is by construction fully consistent with the omnidirectional normalized radar cross section of the multi-band data set.

We simulate the Doppler spectra that can be obtained under experimental conditions from bistatic high-frequency oceanic radar. For this, we combine the bistatic second-order theory with the characteristics of the full radar system, such as antenna patterns, range attenuation, and postprocessing of the received signal. Because of the sharp variation of the bistatic geometry at short range, we show that it is crucial to take these effects into account for the correct interpretation of the first-order Bragg peaks. The second-order spectrum is more robust to the system characteristics but can under some conditions also suffer from its artifacts, especially in the vicinity of the secondary peaks. A comparison is made with experimental spectra acquired recently with a Wellen radar system on the Mediterranean coast. The Wave Watch III model is used to simulate directional wave height spectra after a preliminary validation with in situ buoy measurements. Experimental and simulated Doppler spectra agree generally well, except in the case where the directional wave spectrum has little energy in the line of sight of the radar.

We present a numerical investigation of horizontally polarized microwave scattering from 1-D sea surfaces at extreme grazing angles. Rigorous electromagnetic calculations are performed with a specific integral formalism dedicated to grazing angles. Sample sea surfaces are simulated using a classical Pierson-Moskowitz elevation spectrum together with weakly nonlinear hydrodynamic models, namely, the Creamer solution, the “choppy wave model,” and a recent improved version thereof. For this, the electromagnetic integral formalism is extended to surfaces with irregular sampling. For the different nonlinear surface models and assuming no large-scale current, we evidence a dramatic increase, followed by a saturation of the mean Doppler shift in the last few grazing degrees, with a limiting value depending quasi-linearly on the significant wave height. Our numerical investigations confirm that breaking events are not necessary to produce fast scatterers but tend to show that they are necessary to reproduce the elevated level of backscattered power. The results of this study also support the hypothesis that the blow-up of the mean Doppler shift at grazing angle is associated to an electromagnetic sharp edge effect on the large surface crests rather than geometrical shadowing of the troughs.

We report on the development of free surface reconstruction algorithms to predict ocean waves, based on spatial observations made with a high-frequency Flash light detection and ranging camera. We assume that the camera is mounted on a vessel, in a forward looking position, and is pointing at some distance ahead of its path yielding a sample of spatiotemporal wave elevation data. Because of the geometry, the density of measurement points gradually decreases (i.e., becomes sparse) with the distance to the camera. Free surface reconstruction algorithms were first developed and validated for linear 1-D and 2-D irregular surface models, whose amplitude coefficients are estimated on the basis of minimizing the mean square error of simulated surface elevations to measurements, over space and time (for a specified time initialization period). In the validation tests reported here, irregular ocean surfaces are generated on the basis of a directional Pierson-Moskowitz or Elfouhaily spectrum, and simulated LIDAR data sets are constructed by performing geometric intersections of laser rays with each generated surface. Once a nowcast of the ocean surface is estimated from the (simulated) LIDAR data, a forecast can be made of expected waves ahead of the vessel, for a time window that depends both on the initialization period and the resolved wavenumbers in the reconstruction. The process can then be repeated for another prediction window, and so forth. To reconstruct severe sea states, however, nonlinear effects must be included in the sea surface representation. This is done, here, by representing the ocean surface using the efficient Lagrangian choppy wave model .

The simulation and interpretation of microwave sea radar return in the near-nadir region are still issues in view of the limitations of the geometrical optics approximation and the multiscale and non-Gaussian nature of the surface. We show that an unambiguous and fully consistent physical approach can be reached in the framework of the physical optics. The model is developed on the basis of various satellite and airborne C-, Ku-, and Ka-band measurements using different reference surface roughness spectra. As found, the introduction of a peakedness correction based upon the excess kurtosis of slopes is necessary to obtain consistent analysis across the microwave frequency range. The model yields accurate simulations for the omnidirectional near-nadir normalized radar cross section in different frequency bands, provided the spectrum satisfies some a priori constraints on the distribution of the total and filtered slopes.

This paper is the first in a series of two papers on the use of combined improved hydrodynamic and electromagnetic analytical models for the simulation of the ocean Doppler spectrum at microwave frequencies. Under a linear assumption for the sea surface, we derive statistical expression for the main Doppler characteristics according to asymptotic scattering models. We consider classical models such as the Kirchhoff approximation and the two-scale model, as well as the more recent weighted curvature approximation (WCA). We recover two salient features of Doppler signature in the microwave regime. First, the Doppler characteristics are very sensitive to polarization, with higher mean Doppler shift in horizontal polarization. This is correctly rendered by the WCA but not the classical models. Second, the first two moments of the Doppler spectrum exhibit a nontrivial dependence on incidence angle. Results compare favorably with rigorous numerical computations for 1-D surfaces published in the literature. The simplicity and accuracy of the analytical models provide a valuable tool for the Doppler analysis of 2-D sea surfaces.

This paper extends the results of a previous work by combining hydrodynamic and electromagnetic analytical models for the simulation of the ocean Doppler spectrum at microwave frequencies. We consider weakly nonlinear sea surfaces after the choppy wave model and incorporate them in classical and unified scattering models, namely, the Kirchhoff and weighted curvature approximations. We show that statistical expressions can be obtained for the Doppler spectrum in a way similar to the case of linear surfaces. As expected, the nonlinear nature of the sea surface dramatically impacts the Doppler spectrum at moderate to large incidence angles, with a shift of the central frequency and a broadening of the spectrum. Monte Carlo comparisons are performed with the Creamer model, which is frequently used to describe weakly nonlinear sea surfaces but does not enjoy a statistical formulation for the Doppler characteristics. The same qualitative behavior is found but some quantitative differences are found and discussed.

To progress in the understanding of the impact of nonlinear wave profiles in scattering from sea surfaces, a nonlinear model for infinite-depth gravity waves is considered. This model, termed as the “Choppy Wave” Model (CWM), is based on horizontal deformation of a linear reference random surface. It is numerically efficient and enjoys explicit second-order statistics for height and slope, which makes it well adapted to a large family of scattering models. We incorporate the CWM into a Kirchhoff or small-slope approximation and derive statistical expressions for the corresponding incoherent cross section. We insist on the importance of “undressing” the wavenumber spectrum to generate a nonlinear surface with a prescribed spectrum. Interestingly, the inclusion of nonlinearities is found to be practically compensated by the spectral undressing process; an effect which might be specific to the CWM and needs to be investigated in the framework of fully nonlinear models. Accordingly, the difference between the respective normalized radar cross section is rather small. The most noticeable changes are faster azimuthal variations and a slight increase of the radar returns at nadir. A statistical analysis of sea clutter in the framework of a two-scale model is also performed at large but nongrazing incidence. It shows a pronounced polarization dependence of the distribution of large backscattered amplitudes, the tail being much larger in horizontal polarization and for small resolution cell. Surface nonlinearities are shown to increase the tail of the amplitude distribution, as expected. Less obviously, their relative impact is found lesser in horizontal polarization. This raises the question of the actual contribution of nonlinearities in radar sea spikes at nongrazing angles.

The two-scale model (TSM) is one of the most frequently employed approaches in scattering from multiscale surfaces such as ocean surfaces. It consists of combining geometrical optics (GO) with the small-perturbation model (SPM) to be able to cope with both the small- and large-scale components of the surface. However, well-known shortcomings of this method are the arbitrariness of the dividing scale and the sensitivity of the scattering cross section to the choice of this parameter. We propose to replace SPM with the first-order small-slope approximation (SSA1) to treat the small-scale roughness and derive the formulas for the corresponding TSM, referred to as GO-SSA. We show that GO-SSA is robust to the choice of the frequency cutoff and give a numerical illustration for the sea surface.

A study has been undertaken which objective is to contribute to the investigation of the validity of microwave surface scattering models used in remote sensing applications, particularly when applied to realistic representations of natural surfaces. These investigations are based on recent implementations of rigorous methods (MoM and FDTD) and cover a wide range of configurations of observation (mono- and bi-static). Both land (bare soils) and sea surfaces are being investigated.