A recent ship-based field campaign demonstrated the use of a maritime multi-channel reflectometer using Sirius-XM broadcast radio downlinks as Signals-of-Opportunity. This campaign involved the collection of a large data set of bistatic ocean surface scattering measurements, which coincided with ground truth data detailing local oceanographic parameters. The experiment was unique in that most of its measurements were taken well outside the plane of incidence, with illumination from an oblique angle. This study offers a novel opportunity to explore the fidelity of electromagnetic models (coupled with oceanographic models) to predict radar scattering in these unique geometries. Match-ups are shown between measured and modeled bistatic normalized radar cross sections and range profiles, with the intention of both 1) supporting shore- and pier-based reflectometry through bistatic surface scattering model validation and 2) demonstrating the utility of using reflectometry for oceanic remote sensing from a sea-faring vessel.

A method for determining the cutoff wavenumber used in the geometrical optics theory of scattering from a random rough surface is presented. The method is based on the “alpha stable distribution” approach described in previous studies, and yields a cutoff wavenumber that depends on the spectrum model applied, the angle of incidence, and the frequency of interest. Use of the cutoff wavenumber so determined is found to improve agreement between predictions of the geometrical optics and physical optics theories of near specular scattering from the sea surface in some situations.

With a wind wave spectrum model and input of surface wind speed and dominant wave period, the L-band lowpass mean square slope (LPMSS) can be calculated. Wind and wave data simultaneously measured in four different hurricane hunter missions are analyzed to study the spatial pattern of LPMSS inside tropical cyclones (TCs). There is a clear azimuthal variation in the LPMSS dependence on wind speed. Dividing the TC coverage area into quarters or halves with reference to the TC heading for the same wind speed, the LPMSS in the back quarter (half) is about 12% higher than that in the front quarter (half) for wind speeds up to about 50 m/s. The LPMSSs of the left and right quarters are between those of the front and back quarters and with much smaller differences. There is indication that the LPMSS wind speed dependence steepens in winds greater than 50 m/s, which occurs more frequently in the right half of the TC coverage area. Including all data available with a maximum wind speed up to 67 m/s, the front/back LPMSS difference is about 20%.

Simulation results are used to assist algorithm development for extracting the ocean surface significant wave height (SWH) from microwave scattering of satellite broadcast signals from the ocean surface. The analysis shows that the Doppler frequency spectrum width is a reliable parameter for extracting the SWH. The numerical experiments include both deep and shallow water conditions. The correlation between Doppler frequency spectrum width and SWH is robust and applicable to all wind speeds, inverse wave ages, and water depths tested in this study (5–21 m/s, 0.8–2.0, and 3 m–$\infty $, respectively).

This work presents data from a recent field campaign in which an S-band passive radar using noncooperative satellite-based illumination was used to measure bistatic radar scattering from the sea surface. Significant wave height (SWH) information from a nearby Waverider buoy was reported concurrent with passive radar measurements. These simultaneous data collections fostered a study of the sensitivity of passive radar amplitude and Doppler measurements to SWH. This work demonstrates that Doppler and amplitude measurements with passive radar using satellite-based illumination can provide a promising approach to coastal remote sensing of SWH and mean wave direction, particularly when the scene is illuminated by multiple transmitters with a large physical separation between them.

Numerical experiments are carried out to explore the retrieval of ocean surface significant wave height (SWH) with the Doppler spectrum width (DSW) of microwave bistatic scattering from the ocean surface. Variations of DSW with incidence and scattering angles, wave height, wind speed, wave age, local water depth, and swell condition are described. Physical interpretation is offered on the relationship between SWH and DSW through the surface wave orbital velocity. Among the various environmental factors, the swell exerts the largest influence on the resulting relationship between DSW and SWH. The analysis considers a stationary transmitter and receiver only in order to provide insight into the impact of wave motions on the Doppler signatures.

Waves much shorter than those measured by operational systems make significant contribution to the ocean surface roughness. This article describes a method to obtain the L-band tilting ocean surface roughness using wind speed and windsea dominant wave period coupled with a wind-wave spectrum model. Examples are presented with wind and dominant wave data from ocean buoys and hurricane hunters. Several related issues are discussed: high-frequency wave spectrum, integration limit, swell contribution, and measurements in extreme winds: 1) it is well known since the 1970s that with stationary sensors, extending the frequency range in measuring elevation spectrum does not yield useful short-wave information because of the low signal level and large Doppler frequency shift involved in measuring short waves. 2) Low-pass mean square slopes (LPMSSs) integrated to 5 and 11 rad/m are computed to quantify their difference as a function of wind speed and inverse wave age (IWA). The normalized difference decreases with increasing wind speed and decreasing IWA. 3) Swell contribution to the L-band LPMSS is almost negligible for wind speed greater than 5 m/s (less than 5% in 99% of observations). In low-wind conditions (wind speed less than 5 m/s), the swell contribution is difficult to assess because of inaccuracy in identifying the weak windsea system. 4) The coarse resolution in National Data Buoy Center (NDBC) wave spectra causes large data scatter in the computed LPMSS in very high winds (greater than 20 m/s). A mitigating solution is offered.

The Cyclone Global Navigation Satellite System (CYGNSS) measures GPS signals specularly reflected from Earth's surface to remotely sense ocean surface roughness and wind speed. The mean square slope (mss) is a key physical parameter that relates the ocean surface properties (wave spectra) with the CYGNSS measurement of the normalized bistatic radar cross section (NBRCS). An approach to model the mss for validation with CYGNSS mss data was developed by adding the contribution of a high frequency tail to the IFREMER WAVEWATCH III (WW3) mss. It is demonstrated that the ratio of CYGNSS mss and the modified WW3 mss can be used to diagnose potential calibration errors that exist in the Level 1 calibration algorithm. This approach can help to improve CYGNSS data quality, including the Level 1 NBRCS and Level 2 ocean surface wind speed and roughness.

Surface wave spectral properties of centimeter to decameter (cmDm) wavelengths are of great interest to microwave remote sensing of the ocean. They are obviously different from the high-frequency extension of the wind-wave spectrum models developed for ocean science and engineering applications, which focus on the longer waves in the energetic peak region of the wave spectrum. For more than six decades, the cmDm waves are generally considered to be in the equilibrium range, and its spectral function has a constant slope: -5 or -4 in the 1-D frequency spectrum, and -3 or -2.5 in the 1-D wavenumber spectrum. The observed wind-wave spectral slopes, however, are not constant. As a result, the cmDm wave properties are significantly different from those inferred from an equilibrium spectrum model. Surface slope measurements are more suited for studying the cmDm waves. Microwave radar backscattering cross sections have been used to study the shorter range of cmDm waves. L-band lowpass-filtered mean square slope (LPMSS) is contributed by waves longer than about 0.6 m, here referred to as the decimeter to decameter (dmDm) waves. The analysis of LPMSS has improved the modeling of dmDm waves. Ultimately, the spectral slope variation is a critical characteristic of cmDm waves. The wave spectrum model formulated with the variable spectral slope consideration produces very good agreement with L-band scatterometer and reflectometer measurements.

Ocean surface roughness and whitecaps are driven by the ocean surface wind stress, thus their values calculated from the wind speed input depend on the applied drag coefficient formula. Roughness and whitecaps are two critical elements of the ocean surface response in microwave remote sensing. Recent analysis of the microwave radiometer measurements in tropical cyclones have yielded the result that when expressed as a wind speed power function, the exponent in high winds (greater than about 35 m/s) is about -1 for the drag coefficient, 0.5 for the wind friction velocity, and 1.25 for the whitecap coverage. The updated information on the drag coefficient, whitecap coverage, and surface roughness is incorporated in the microwave emission and scattering models. The calculated brightness temperature and the co- and cross-polarized scattering radar cross sections in tropical cyclone wind conditions for a range of microwave frequencies and incidence angles are reported.

The ocean surface roughness and foam coverage are the two important elements in the electromagnetic (EM) thermal emission computation. The foam contribution accounts for the air modifying the dielectric property of the water side interface layer. It can be modeled using a mixing rule of the air and water relative permittivities weighted by the air fraction and foam-free portion in the EM-influence volume, respectively. For high EM frequencies, the air fraction can be approximated by the whitecap fraction given as a function of wind speed empirically established with oceanographic observations. This simplification works very well for C band and higher frequencies but overestimates the foam effects for the L-band; the air fraction needs to be reduced compared to the whitecap fraction. Through the thermal emission analysis applied to several data sets of radiometer measurements in high winds, a function relating the air fraction and whitecap coverage is established. Incorporating the proposed function, the thermal emission model computations are in very good agreement with radiometer measurements at 1.4, 4.7, 6, 10, 18, 23, and 37 GHz with various incidence angles and both vertical and horizontal polarizations. Comparing the foam and roughness components contributing to the wind-induced thermal emission, the roughness contribution dominates over a broad wind speed range. Except for the vertical polarization near the 55° incidence angle, the roughness contribution is almost always greater than the foam contribution to well above 20 m/s wind speed, the crossover wind speed for the foam contribution to exceed roughness contribution is dependent on the frequency, incidence angle, and polarization.

Surface roughness and foam are two main components of ocean surface microwave thermal emission. Surface roughness provides scattering element and modifies local incidence angle. Air in foam alters the dielectric property of the surface layer. Bubbles in foam also alter the curvature of foam- water interface and modify emission and scattering properties of the water surface itself. Whitecap coverage Wc is the most accessible oceanographic information to represent surface foam. For emission analysis, it is necessary to establish a function relating to Wc and the effective air fraction Fa interacting with electromagnetic (EM) waves. An empirical relation is established through analyzing several microwave radiometer data sets in high winds covering a wide range of frequency, incidence angle, and vertical and horizontal polarizations. A physical interpretation of the proposed Fa (Wc) relationship is discussed. The relationship is used to quantify several important characteristics of surface foam relevant to microwave emission, including effective air fraction and skin depth as functions of wind speed, microwave frequency, and incidence angle.

Directional wave spectra with associated wind velocity information have been acquired in several hurricane reconnaissance and research missions. Here we present the analysis results of wind and wave directional properties and the comparison of the directionally integrated 1D frequency spectra S(ω), where ω is the angular frequency, with three published wind-wave spectral models denoted as J, D, and G models. The spectral slope in the high frequency portion is -5 for the J model (short hand for JONSWAP) [1]-[2], -4 for the D model (Donelan) [3], and unrestricted for the G model (General) [4]. Based on analyses of spectral observations in hurricane [5] and non-hurricane conditions [4], the spectral slope -s = -4.5 is used for the G model in the comparison study.

Spectral properties near the dominant wave region influence significantly the surface roughness relevant to ocean remote sensing employing low-frequency microwave sensors. The critical parameters characterizing dominant waves are wind speed and dimensionless spectral peak frequency, which is the inverse wave age. The dimensionless spectral peak frequency can be expressed as an equivalent dimensionless fetch or duration. The connection between dominant waves and surface roughness is the spectral slope. This paper presents a surface wave spectral model designed for low-frequency microwave remote sensing, with special emphasis on tropical cyclone (TC) applications. The key elements of the spectral model are: 1) a general spectral function with coefficients accommodating a variable spectral slope and 2) a parametric function connecting the spectral slope and wind speed, which is established with the mean square slope (MSS) observations obtained inside hurricanes by the global positioning system reflectometry technique. In order to make use of the MSS observations inside hurricanes, parametric models of the spatial distributions of wind speed and dimensionless spectral peak frequency inside TCs are developed. The parametric models are based on the wind and wave similarity relationships derived from analyses of hurricane hunter measurements.

The close connection between wind and wave properties has been the foundation of ocean remote sensing using microwave frequencies. This wind-wave connection is employed either explicitly or implicitly in the scatterometer wind measurement: the touted capability of “all-weather” and “day-and-night” operation of microwave wind sensing means that the sensor sees through clouds and atmosphere, thus obvious it does measure the motion of air mass or clouds to deduce wind speed.

A hybrid backscattering model is built to provide a consistent description for C-band VH- and VV-polarized normalized radar cross sections (NRCSs). Ocean surface coand cross-polarized NRCS are both treated as a sum of Bragg and non-Bragg scattering components. To better understand the synthetic aperture radar (SAR) observed NRCS signals under high-wind conditions, five C-band RADARSAT-2 dual-polarization SAR hurricane images and the collocated wind vectors measured by the airborne stepped-frequency microwave radiometer (SFMR) are collected. Based on the match-up data, we add a non-Bragg term in the composite Bragg theory to explain the discrepancy between the measurements in the cross-polarization channel and the existing theory results. The non-Bragg scattering to Bragg scattering ratio (Br) is found to be a constant. We build the hybrid backscattering model with Br and establish a relationship between the cross-polarization NRCS and the radar incidence angle under different wind conditions. The NRCS dependence on incidence angle is simulated by the hybrid backscattering model. Finally, a C-band Cross-Polarization Coupled-Parameters Ocean (C-3PO) model is developed to retrieve hurricane winds using VH-polarized ScanSAR by including the radar incidence angle. The collocated SAR and SFMR data sets are separated into two parts: data set-A, for hybrid backscattering model derivation and C-3PO model coefficients tuning, and data set-B, for hurricane wind validation. C-3PO model validation results show that the model is suitable for ocean surface wind mapping from RADARSAT-2 cross-polarization ScanSAR images. The retrieval has a rootmean-square error less than 3 m/s for wind speed up to 40 m/s.

The robust wind wave growth functions established with ideal fetch-limited and quasi-steady wind conditions (e.g., [11-13]; and references therein) have been observed to be applicable to wind generated waves under considerably more varying conditions, including hurricanes [1, 3, 4, 14, 15] and rapidly accelerating and decelerating wind fields such as those encountered in mountain gap winds [16-19].

We present a method to retrieve wind speeds in hurricanes from spaceborne passive microwave radiometer data. Brightness temperature (TB) observations acquired at the 6.9-GHz horizontal polarization channel by the AMSR-E and AMSR2 onboard the Earth Observing System Aqua and Global Change Observation Mission-Water 1 satellites are selected for wind retrieval due to the fact that the signal at this frequency is sensitive to high wind speeds but less sensitive to rain scatter than those acquired at other higher frequency channels. The AMSR-E and AMSR2 observations of 53 hurricanes between 2002 and 2014 are collected and collocated with stepped-frequency microwave radiometer (SFMR) measurements. Based on the small slope approximation/small perturbation method model and an ocean surface roughness spectrum, the wind speeds are retrieved from the TBdata and validated against the SFMR measurements. The statistical comparison of the entire data set shows that the bias and root-mean-square error (RMSE) of the retrieved wind speeds are 1.11 and 4.34 m/s, respectively, which suggests that the proposed method can obtain high wind speeds under hurricane conditions. Two case studies show that the wind speed retrieval bias and RMSE are 1.08 and 3.93 m/s for Hurricane Earl and 0.09 and 3.23 m/s for Hurricane Edouard, respectively. The retrieved wind speeds from the AMSR-E and AMSR2 continuous three-day observations clearly show the process of hurricane intensification and weakening.

Ocean surface roughness and surface wave breaking are two common parameters important to the studies of microwave ocean remote sensing and air-sea interactions. For example, remote sensing of ocean surface vector winds by radars and radiometers makes implicit use of the property that the normalized radar cross section (NRCS) and the sea surface brightness temperature are modified by the surface roughness and wave breaking; and both oceanographic properties are closely influenced by the wind. For air-sea interaction processes such as gas transfer or sea spray aerosol generation, the boundary layer turbulence properties are closely associated with the surface roughness, and wave breaking represents a dominate process of turbulence generation and air entrainment in the upper ocean layer.

Microwave backscattering from the ocean surface is closely related to the wind-generated ocean surface roughness. This property is used for obtaining global ocean surface vector winds. The deployed scatterometers so far do not use the cross-polarized sea return (VH, representing either vertical transmit horizontal receive or horizontal transmit vertical receive) because of its weak signal level. The copolarized returns (VV or HH), however, may saturate in high wind speeds especially for low incidence angles.

This paper describes the Naval Research Laboratory Multi Aperture Synthetic Aperture Radar (NRL MSAR) and presents initial results from the inaugural field deployment of this system. The NRL MSAR is an airborne test bed designed to investigate remote sensing and surveillance applications that exploit multiple along-track phase centers, in particular, applications that require measurement of scene motion. This paper presents the results of initial coherent analyses to estimate scene and target motion and to correct the image distortions that these motions induce. These images were collected over an ocean inlet and contain a variety of moving backscatter sources, including automobiles, ships, shoaling ocean waves, and tidal currents.

Several papers highlighting the monotonic increase (with respect to wind speed) of the cross polarization radar backscatter (σ0VHor VH for shorthand in the text) from the ocean surface have been published recently (Hwang et al, 2010a, b; Vachon and Wolfe, 2011; Zhang et al., 2011). The result has generated some interest in exploring hurricane wind retrieval using VH and to incorporate VH in the next generation scatterometer designs. In the subsequent development of algorithms (e.g., Zhang el al, 2011, 2012, 2014 Zhang and Perrie, 2012; van Zadelhoff et al. 2013 Belmonte Rivas et al, 2014), it is assumed that VH varies mainly with wind speed (U10) and independent on the azimuthal angle (φ). Its dependence on incidence angle (θ) is either ignored [Zhang et al, 2011, 2012, 2014 Zhang and Perrie, 2012] or accounted for only in low to strong wind range (U10<;21 m/s) [van Zadelhoff et al., 2013, 1014].

Recent wind retrieval algorithms using crosspolarization (cross-pol) radar sea return (VH) assume that VH is independent on the azimuth angle and mainly varies with the wind speed. Incidence angle dependence is either absent or is only in wind speeds less than 21 m/s. However, azimuth and incidence angle variations are expected since theory and data comparisons show the dominance of surface effects in the scattering mechanisms; thus, both co-polarization and cross-pol cross sections reflect the directional distribution of the ocean surface roughness and wave breaking. Here, the VH dependence on wind velocity is analyzed with special focus on the variations with the incidence and azimuth angles. The results show that, for the typical incidence angle range of radar images used for hurricane wind retrieval (20°-50°), the magnitude of these angular variations is equivalent to a difference of about 10 m/s in the retrieved wind speed for low-to-strong winds (~21 m/s) as well. It is prudent to incorporate the incidence angle dependence and the azimuth angle dependence in the wind retrieval algorithm and in the signal simulation for the design of next-generation scatterometers. The dependence on the wind speed is also examined. It reconfirms that the VH sensitivity increases toward high winds, but signal saturation may occur.

Meissner and Wentz (M09) [4] report global WindSat measurements of wind-induced emissivity change at 6, 10, 18, 23 and 37 GHz in wind speeds up to about 50 m/s (Fig. 1). Superimposed in the figure are the SSA/SPM simulations accounting for both foam and roughness effects. The agreement between computation and measurements is generally very good. Both measurements and simulations show a monotonic increase of emissivity change with wind speed up to 50 m/s, and the rate of change seem to slow down somewhat in high winds. Fig. 2 shows the comparison of WindSat measurements and SSA/SPM simulations with the foam and roughness components displayed separately. The foam effect increases monotonically with wind stress. For the vertical polarization in the WindSat configuration (incidence angle about 53°), foam is the dominant contributor of wind-induced emissivity change. The roughness contribution is positive at 6, 10 and 18 GHz with decreasing magnitude toward higher frequency; it becomes negative at 23 and 37 GHz. The null roughness contribution occurs between 18 and 23 GHz, and this range represents the ideal frequency band for passive microwave remote sensing with minimal surface roughness contamination. For the horizontal polarization, roughness contribution dominates in all five frequencies except for a small range of wind speeds near 50 m/s at 6 GHz. For microwave frequencies less than about 10 GHz, the wind speed sensitivity of roughness contribution is less than that of the foam contribution; for higher microwave frequencies, the two contributions have similar wind speed sensitivity.

Whitecaps and surface roughness are the two main components of the wind-induced microwave emissivity change of the ocean surface. The resulting difference of the received brightness temperature from that of a flat foamless sea surface at the same sea surface temperature and salinity is used for ocean surface wind vector retrieval using passive microwave remote sensing technology. In other applications such as sea surface salinity retrieval using L-band microwave radiometers, the wind-induced emissivity change is the major source of error, and its correction is important to the accuracy of retrieved salinity. Furthermore, global whitecap distribution using spaceborne radiometer measurements is possible if the contributions of emissivity change from roughness and foam can be separated. This is an important application because whitecaps are the manifestation of surface wave breaking, which is of great importance in air-sea interaction and climate research. This paper describes an analysis of the foam and roughness components of wind-induced emissivity change. The analysis is in good agreement with global WindSat measurements obtained over a broad range of wind speeds. Quantitative results on the variation of the foam and roughness components with respect to wind speed, incidence angle, microwave frequency, and polarization are presented.

Presently, wind velocity retrieval uses co-polarized (co-pol) normalized radar cross sections (NRCS) from the ocean surface (σοyy and σ0HH, respectively vertical transmit vertical receive and horizontal transmit horizontal receive). In recent analyses of the RADARSAT-2 (R2) quad polarization (quad-pol) data, it is found that whereas the co-pol backscatter shows a saturation trend in winds exceeding about 16 m/s for incidence angle 6*;~10 m/s) from about linear in moderate winds (<;~7 m/s). Thus, the retrieved wind speed using σ0VH becomes more accurate in higher wind speeds. This is a significant breakthrough for monitoring hazardous wind events such as hurricanes and subtropical storms with wind speeds frequently exceed the ambiguity thresholds of wind retrieval using the co-pol radar backscatter. The spatial coverage of R2 quad-pol data is nominally 25 km by 25 km. For a large area of coverage, the Scan SAR beam modes (300 km for narrow and 500 km for widemode) are more practical, and the cross-pol data are only available in dual-polarization (dual-pol) mode, either HH and HV or VV and VH. Here the result of wind speed retrieval using dual-pol σ0VH is presented.

The influence of sea surface roughness dominates the error budget of satellite sea surface salinity (SSS) retrieval from L-band radiometers; thus, accurate roughness correction models are needed. Semi-analytical SSS correction models, as used in the soil moisture and ocean salinity satellite Level 2 processor, combine an emissivity model with an ocean wave spectrum model that describes the rough sea surface. Previous findings indicate that the errors contributed by ocean roughness model exceed those of the emissivity model. In this paper, we compare the performance of three well-known spectrum models and a new one as inputs to the small slope approximation/small perturbation method emissivity model. The new spectrum model, which is developed from empirical parameterization of short water wave spectra measured in the ocean and incorporates swell effects, performs very well in comparison with the other spectrum models, and we propose its consideration for future SSS roughness correction models.

The dual-beam interferometer is an airborne instrument that combines two vertically polarized C-band along-track interferometric synthetic aperture radars (AT-InSARs) observing the surface below at different squints. The system was designed by the University of Massachusetts and saw several deployments in the early 2000s. An imagery of a small vessel with a rather pronounced wake pattern captured during one of such flights is the subject of this letter. Specifically, the interferometric phase in the turbulent wake exhibits a conspicuous banding structure that is still visible at distances more than 1 km behind the craft. The phase signatures from the fore and aft looks are combined to retrieve both longitudinal and lateral velocity components along cuts traversing the wake 400 and 750 m behind the boat. The results identify appreciable variations in the longitudinal velocity across the turbulent wake which are apparently consistent with the combined effect of the hull drag and the propeller backwash. A persistent pattern for the lateral component is also observed but is harder to interpret without the detailed knowledge of the vessel. The examples demonstrate the utility of AT-InSAR and, particularly, of a dual-beam AT-InSAR, for studies of centerline ship wakes. Readily available velocity signatures of a turbulent wake obtained with such systems can help with vessel classification tasks.

In this paper, we investigate an issue related to the use of synthetic aperture radar imagery to detect ocean and lake waterlines. In a previous publication, the waterlines indicated by Land P-band AIRSAR imagery of a tidal flat in South Korea were compared and found to be offset from one another by approximately 80 to 170 m. The authors postulated that the difference was due to depth-dependent dissipation or dispersion of surface waves and the subsequent modulation of the radar backscatter as described by the Bragg model. In this paper, we present an alternative explanation based on the growth of wind waves as a function of distance (i.e., fetch). This new explanation is more consistent with the environmental conditions, radar look geometry, and surface wave theory, while also explaining several finer-scale features observed in the imagery that are not addressed in the original publication. Our results indicate that the detected waterline position should be a sensitive function of radar frequency only under a restricted set of conditions, namely, when the body of water in question is cutoff from incoming swell and the only surface waves present are locally generated by a land breeze. While such conditions may occur relatively infrequently in the coastal ocean, they appear to be common when imaging the windward shores of inland lakes, as illustrated by additional AIRSAR imagery. The analysis also serves as a remote-sensing-based validation of the existing theory for wind-wave growth in a wavenumber regime not previously studied in the field.

The recent and imminent launch of the SMOS and Aquarius satellites carrying microwave L-band radiometers provides an opportunity to map Sea Surface Salinity (SSS) globally with an expected error <; 0.2 psu. However, the accuracy of retrieved SSS depends critically on brightness temperature (Tb) corrections for sea surface roughness (SSR) effects. This paper assesses the performance of representative roughness correction models when compared with published data, and applied to recently-acquired airborne L-band radiometer data. One type of model currently being used to process SMOS data combines a wind-driven gravity wave spectrum that describes SSR, with an electromagnetic (EM) model that determines microwave emissivity, to predict the Tb roughness increment relative to the flat sea response. We find that selection of both the spectral and emissivity models strongly influences the resulting (~1 K) Tb errors. We conclude that more accurate modeling of short wavelength spectral components and their EM influence is needed, to reduce these errors to acceptable levels.

The technique for extracting wave period and wave direction from a navigation radar backscattering intensity is well developed but the determination of spectral density or wave height is hindered by the complex nature of the modulation transfer function. In contrast to backscattering intensity, Doppler velocity from coherent radar is the radial velocity of the scattering objects. Its oscillatory component is contributed by ocean waves. The spectral peak component of Doppler velocity is close to the peak wave period measured by a nearby buoy and the significant wave height can be accurately calculated. With radar range coverage on the order of ten dominant wavelengths, reliable assessment of peak wave period and significant wave height is achievable with radar data as short as one second. Wave direction can also be determined with a scanning system.

The wind generates a distribution of small slope waves and sporadic steep breaking events. Such double structure of the sea surface is expected to have a strong impact on the radar scattering from the ocean surface. The signature of the double structure is in the wind speed dependence of radar returns: linear for scattering from gentle waves and cubic for breaking contribution. The composite-surface Bragg resonance (CB) theory describes the former very well. Detection of the breaking contribution remains difficult. Here we show that the depolarized (de-pol) radar return exhibits the typical double structure, its wind speed dependence increases with wind speed from linear to cubic. The increased sensitivity of the de-pol returns in high winds is ideal for hurricane wind retrieval. The strong breaking connection offers an opportunity to measure wave breaking and the associated energy dissipation and area of foam coverage from space, their quantification is important in air-sea interaction and electromagnetic and electro-optical remote sensing.

The Dual-Beam Interferometer is an airborne instrument that combines two along-track interferometric synthetic aperture radars observing the surface below at different squints. This configuration allows retrieving vector velocities of surface flows in a single aircraft pass. The system was designed by the University of Massachusetts and saw several deployments in the early 2000s. An imagery of a boat with a rather pronounced wake system captured during one of these flights is the subject of this paper. The velocity of the vessel is estimated based on the “train off the tracks” displacement in one of the looks. This estimate, which will be affected by uncertainty in target position due to smearing, is then used to remove unknown phase biases in the interferometric channels. Retrieved velocity variations are examined along cuts traversing the wake, with the focus on its narrow “turbulent” part. We find that the reconstructed velocities 150 m behind the boat are intuitively satisfying, but we are unable to fully account for the cross-wake component of velocity at 400 m behind the vessel.

We propose two new analytical polarization ratio (PR) models based on the RADARSAT-2 Quad-Polarization (HH+VV+HV+VH) observations over the ocean. One is a function of incidence angle only and the other has additional dependence on wind speed. Comparisons are presented with theoretical and empirical PR models from the literature. The new PR model with wind speed and incidence angle dependence is shown to compare best with observed RADARSAT-2 data. An assessment of the PR model with only incidence angle dependence is given using CMOD algorithms and HH-polarized images. Results suggest that this PR model can accurately convert normalized radar cross sections (NRCS) in HH polarization to VV polarization and retrieve wind speeds from RADARSAT-1 or RADARSAT-2 HH polarization images.

Swell effects of surface roughness spectral properties, including their wind speed dependence and modification of components characterizing Bragg resonance and surface tilting in radar application, are investigated. Computations of radar cross sections are performed with four different spectral models with various degrees of swell consideration. Swell impact on the resulting radar return is illustrated.

The anomaly of radar sea spikes, defined here as the non-Bragg scattering events with backscattering cross section of horizontal polarization exceeding that of vertical polarization, has been associated with steep wave features possibly going through wave breaking process. This property is employed for remote detection of breaking waves. The results are used to quantify the effect of wave breaking on radar returns. Large increase due to breaking is found in the Doppler velocities of both polarizations (about 50% faster with breaking). The effect of breaking on the backscattering cross section is much stronger for the horizontal polarization (with 15 to 20 dB enhancement) and relatively small in the vertical polarization (on the order of 0.5 dB fluctuations). The presence of swell reduces the impact of breaking waves on radar return in comparison to the scattering from wind seas.

Radar backscatter data are collected using a coherent, dual-polarized radar from a fixed tower in the ocean. Statistical analysis is performed to investigate the 1D and 2D probability density functions of backscatter intensity, Doppler frequency, coherence function and polarization ratio. The fraction of sea spike coverage generally increases with wind speed but the trend of increase is modified by the intensity of background swell condition. Parameterizations of sea spike coverage combining both wind and wave factors show some apparent advantage than parameterizations with wind or wave factors alone.

A dual-beam interferometric synthetic aperture radar provides two velocity components of the ocean current remotely from a single fight pass. Combining two flight passes, all three orthogonal components of the surface velocity can be retrieved. An experiment was conducted near the Gulf Stream (GS) boundary. A sharp change of the surface velocity of about 1 m/s over a 500 m distance was measured. The wave condition is dominated by a 14-s swell system and low wind velocity. The wave variance inside GS is about twice the wave variance outside the GS in the present data. The large difference in the wave variance is considerably higher than that can be expected from hydrodynamic modulation. An ocean current system with strong current shears such as the Gulf Stream is a wave guide and can trap waves with the right combination of wavelengths and propagation directions. Numerical calculations indicate that the wave properties of the data set may satisfy the conditions for wave trapping by the Gulf Stream.

This paper presents an analysis of the wavenumber spectra of intermediate-scale waves (wavelengths between 0.02 and 6 m) under various sea-state conditions. The main result of the analysis is that the dependence of the dimensionless wave spectrum on the dimensionless wind friction velocity follows a power-law function. The coefficient and exponent of the power-law function vary systematically with the wavenumber. The wavenumber dependence of the coefficient and exponent serves as an empirical parameterization for computing the wavenumber spectra of intermediate-scale waves at different wind speeds. Calculation of the mean-square slope from the resulting wavenumber spectrum confirms that intermediate-scale waves are the dominant contributor of the ocean surface roughness. A simple formula is presented for calculating the band-pass filtered mean-square slope of the ocean surface for remote sensing applications.

Local wind-generated surface roughness can be decomposed into ambient component, surface wave geometric contribution (the mean square slope) and breaking wave contribution (the breaking roughness). Only the last two components can be attributed to local wind condition for remote sensing considerations. The ambient roughness level is estimated to be between 0.01 and 0.02 from altimeter data. The rate of increase of breaking roughness with wind speed is much faster than the counterpart of the mean square slope of wave geometry. In high wind conditions, breaking roughness contribution may exceed the wind-wave geometrical contribution. The data of Cox and Munk (1954) collected in clean and slick conditions, and newer data of filtered surface roughness derived from spaceborne altimeter are analyzed to provide a quantitative description of the breaking roughness.