Normalized Radar Backscattering Cross Section Research Articles

Wind speed retrieval from Chinese Gaofen-3 synthetic aperture radar using an analytical approach in the nearshore waters of China’s seas

ABSTRACT Empirical wind-retrieval algorithms for synthetic aperture radar (SAR), such as the geophysical model function (GMF) CMOD5N in the C-Band, are currently well developed. The retrieval accuracy of GMFs, however, is lower in the presence of marine phenomena such as oceanic fronts and mesoscale eddies, making SAR wind retrieval challenging under these conditions. In this study, we proposed a scheme for wind retrieval from Chinese Gaofen-3 (GF-3) SAR images using an analytical approach to obtain the wind speed in the nearshore waters of China’s seas. Approximately 300 images were acquired from 2018 to 2021 in the copolarization channels [vertical–vertical (VV) and horizontal–horizontal (HH)]. The images were collocated with the measurements from the Advanced Scatterometer (ASCAT) and the Chinese Haiyang-2B (HY-2B) scatterometer. Our analytical approach was based on the Bragg resonant and non-Bragg (NB) scattering model for the calculation of the normalized radar backscatter cross-section (NRCS), which accounted for the influence of wave-current interactions and breaking waves in nearshore waters. We used the sea surface currents obtained from the HYbrid Coordinate Ocean Model (HYCOM) to simulate the Bragg resonant roughness. We derived the contribution of the NB breaking waves from the SAR-measured NRCS values in both the VV and HH channels. By comparing the retrieval results obtained using the analytical approach with the scatterometer products, we concluded that the root mean square error (RMSE) of the wind speed was 2.01 m s−1 with a 0.91 correlation coefficient (COR), which was less than the 2.93 m s−1 RMSE and 0.72 COR for the GMF CMOD5N. The variation in the bias of the HYCOM currents was approximately 1 m s−1 for current speeds greater than 0.3 m s−1. These findings verified the stability of the analytical approach for SAR wind retrieval in complex sea states.

Effect of Bispectrum on Radar Backscattering From Non-Gaussian Sea Surface

The upwind-downwind asymmetry in normalized radar backscattering cross section (NRBCS) from ocean surface is well known; one acceptable and convincing reasoning is explained by the fact that the surface height distribution deviates from Gaussian one, which causes a nonzero skewness function, and consequently affects the radar cross section in up and down wind directions. Specific forms of skewness function, in between Gaussian and exponential, have been proposed in previous studies to account for the upwind/downwind asymmetry in radar backscatter. Attempt is made, through numerical simulation, in this article to examine the impact of these two types of skewness functions on NRBCS. The simulated NBRCSs, with and without skewness contributions, are compared with measured data in upwind and downwind directions at L-, C-, and Ku-bands for different wind speeds. The results indicate that the Gaussian-type skewness function works better to account for the upwind/downwind asymmetry of NBRCS by choosing an appropriate root mean square (RMS) height appearing in skewness function and as the wind speed or radar frequency increases, the RMS height increases but regardless of wind direction and radar incidence angle.

Effects of Wind Wave Spectra on Radar Backscatter From Sea Surface at Different Microwave Bands: A Numerical Study

Wind wave spectrum describes the quasi-periodic nature of the ocean surface oscillations and plays an indispensable role in the study of microwave electromagnetic scattering from sea surface. A reliable spectrum model suitable for radar cross section (RCS) predictions at different radar frequencies is desired. This paper evaluated the performances of five common spectrum models (i.e., Fung spectrum, Durden-Vesecky spectrum, Apel spectrum, Elfouhaily spectrum, and the newest version of Hwang spectrum, H18) on the normalized radar backscattering cross section (NRBCS) simulations based on advanced integral equation model (AIEM) at L-, C-, X-, and Ku-bands versus incidence angle, wind direction, and wind speed by comparing with the model and measured data for validation. These results indicate no single wave spectrum of them is satisfying for all the four radar frequencies, e.g., Apel and H18 spectra are better for L- and C-bands, Apel spectrum for X-band, and Elfouhaily and H18 spectra for Ku-band. Given this, three average composite spectrum models are constructed using different spectral models (i.e., all five spectra, Apel + Elfouhaily + H18, and Apel + H18) to simulate NRBCSs, similar to that of the individual spectrum model. It is concluded that the combination of Apel and H18 spectra overall performs best among the individual one and other composited spectra in like-polarized NRBCSs versus incidence angles, wind directions, and wind speeds, for wind speed greater than 30 m/s where the combination of the five spectra work well at Ku-band.

Low-Frequency Sea Surface Radar Doppler Echo

The sea surface normalized radar backscatter cross-section (NRCS) and Doppler velocity (DV) exhibit energy at low frequencies (LF) below the surface wave peak. These NRCS and DV variations are coherent and thus may produce a bias in the DV averaged over large footprints, which is important for interpretation of Doppler scatterometer measurements. To understand the origin of LF variations, the platform-borne Ka-band radar measurements with well-pronounced LF variations at frequencies below wave peak (0.19 Hz) are analyzed. These data show that the LF NRCS is coherent with wind speed at 21 m height while the LF DV is not. The NRCS-wind correlation is significant only at frequencies below 0.01 Hz indicating either differences between near-surface wind (affecting radar signal) and 21-m height wind (actually measured) or contributions of other mechanisms of LF radar signal variations. It is shown that non-linearity in NRCS-wave slope Modulation Transfer Function (MTF) and inherent averaging within radar footprint account for NRCS and DV LF variance, with the exception of VV NRCS for which almost half of the LF variance is unexplainable by these mechanisms and perhaps attributable to wind fluctuations. Although the distribution of radar DV is quasi-Gaussian, suggesting virtually little impact of non-linearity, the LF DV variations arise due to footprint averaging of correlated local DV and non-linear NRCS. Numerical simulations demonstrate that MTF non-linearity weakly affects traditional linear MTF estimate (less than 10% for typical MTF magnitudes less than 20). Thus the linear MTF is a good approximation to evaluate the DV averaged over large footprints typical of satellite observations.

Rain effects on the hurricane observations over the ocean by C‐band Synthetic Aperture Radar

AbstractA composite radar scattering model composed of the atmosphere radiative transfer model, and the ocean surface Bragg wave theory is developed to analyze the impact of hurricane rain on the normalized radar‐backscatter cross section (NRCS) measured in the VV and cross‐polarized C‐band Synthetic Aperture Radar (SAR) channels. The model results are validated against SAR and SFMR measured wind speeds and rain rates for two hurricane cases. The contribution of rain to the NRCS is backscatter from two parts: the atmosphere column and the ocean surface. In the atmosphere, microwave attenuation and the rain‐induced volume backscattering are simulated by the model. We find that the impact of raindrops in the atmosphere is almost negligible for the VV polarization, but important for the cross polarization. On the ocean surface, comparisons between our model and other existing models without rain lead to the conclusion that the VV polarization NRCS can be simulated reasonably well without considering the non‐Bragg scattering mechanisms. Similar to the wave breaking mechanism, the microwave diffraction on the craters, crowns, and stalks, produced by rain drops, is also negligible for VV polarization. However, the non‐Bragg scattering is important for the cross‐polarized NRCS simulations. Finally, we performed simulations to understand the VV‐polarized NRCS behavior under different wind speeds at various rain rates.

A new wind retrieval algorithm for Jason-1 at high wind speeds

The altimeter wind speed algorithm at high wind speeds remains unsolved because of lack of observed data. In this study data at high wind speeds were generated using Yin's typhoon model, which consists of the Rankine vortex model and the angular momentum model with typhoon parameters, provided by the Joint Typhoon Warning Centre (JTWC). The accuracy of Yin's typhoon model can be validated by comparing it with recorded data from a weather station. By comparing the normalized radar backscatter cross‐section (NRCS) detected by the Jason‐1 altimeter with wind speed data inferred by Yin's typhoon model, an empirical algorithm valid for a range of wind speeds between 10 and 40 m s–1 is developed and proposed. The proposed algorithm is compared with the Jason‐1 operational algorithm and Young's altimeter wind retrieval algorithm. The study shows that, for the proposed algorithm and the operational algorithm for Jason‐1, the root mean square (RMS) errors are 3.38 and 3.60 m s–1, respectively, and the average relative errors are 18% and 19%, respectively, for wind speeds less than 27 m s–1. Hence, the proposed algorithm is in agreement with the operational algorithm for the Jason‐1 altimeter for wind speeds in the range 10–27 m s–1. However, the Jason‐1 operational algorithm is inaccurate for wind speeds above 27 m s–1 because the wind speeds used in the algorithm training process came from scatterometer wind products, and are significantly lower than those in strong wind and heavy rain conditions. Comparison of the proposed algorithm and Young's algorithm shows that the RMS errors are 6.27 and 15.18 m s–1, respectively, and the average relative errors are 16% and 59%, respectively, for wind speeds greater than 20 m s–1. The Holland typhoon model cannot accurately determine the outer wind field of typhoons since it extends cyclonic wind speeds to infinity. Young's altimeter wind retrieval algorithm depends on the Holland typhoon model, and the latter results in some errors. Compared with Young's altimeter wind retrieval algorithm, the proposed algorithm retrieves wind speeds with better accuracy. Therefore, the proposed algorithm, suitable for retrieving sea surface wind speeds in typhoons and other strong wind conditions, can be considered as supplementary to the Jason‐1 operational algorithm.

An analytical algorithm with a wave age factor for altimeter wind speed retrieval

Based on the specular reflection theory of electromagnetic waves at rough sea surface and the wind wave spectrum model with a wave age factor, the sea surface wind speeds are retrieved from the normalized radar backscatter cross‐section (NRCS) measured by TOPEX/Poseidon (T/P) Ku‐band altimeter using the mean square slope (MSS) calculated from the spectrum models of the wind waves and the gravity‐capillary waves. A relationship between wave age and non‐dimensional wave height is applied to compute the wave age factor using the significant wave height (SWH) and wind speeds obtained from buoy or altimeter simultaneously. The study indicates that the wave age factor has a significant impact on the retrieval of altimeter wind speed. Compared with the operational algorithm for retrieving altimeter wind speed, the wind speed retrieved from the new analytical algorithm based on the wind wave spectrum model with the wave age factor, proposed in this study, can match the buoy measurements better. The effects of the wave age factor on altimeter wind speed retrieval are also shown quantitatively through a series of experiments and measurements. The comparison with the operational algorithm indicates that both the bias and root mean square error (RMSE) between wind speeds retrieved by the proposed analytical algorithm and those observed by the buoy decrease significantly. In the Gulf of Mexico, with the new analytical algorithm, more accurate altimeter wind speeds are retrieved.

Azimuthal harmonic coefficients of the microwave backscattering from a non-Gaussian ocean surface with the first-order SSA model

In this paper, the first-order small slope approximation is applied to a rough sea surface with non-Gaussian statistics, for which the third- and the fourth-order statistics are taken into account in the calculation of the radar cross section. From the Cox and Munk slope distribution, the higher order statistic moments are derived, and behaviors of the corresponding correlation functions are assumed. We show that the fourth order (related to the peakedness or kurtosis) is isotropic, whereas the third order (related to the skewness) has a behavior as cos(/spl psi/), where /spl psi/ is the wave direction along the wind direction. Thus, using the Elfouhaily et al. sea height spectrum, related to the second-order statistics, we show that the normalized radar backscattering cross section (NRBCS) can be expanded as an even Fourier series in cos(n/spl phi/) (where n is a positive integer), for which the harmonic coefficients require only a single integration over the radial distance. This result is consistent with experimental data done for microwave frequencies. In addition, we show for microwave frequencies (like C- and Ku-bands) that the Fourier series can be truncated up to the second order, since the higher order harmonic coefficients vanish. The NRBCS is also compared with empirical backscattering models CMOD2-I3 and SASS-II, valid in C- and Ku-bands, according to the scattering angle and the wind direction. The first-order harmonic coefficient predicts the surface asymmetry along the upwind and downwind directions, whereas the second-order harmonic coefficient describes the surface asymmetry along the upwind and crosswind directions.

On the determination of characteristics of the interior ocean dynamics from radar signatures of internal solitary waves

In this paper we discuss two different methods of inferring characteristics of the interior ocean dynamics from radar signatures of internal solitary waves visible on synthetic aperture radar (SAR) images. The first one consists in the recognition and the interpretation of sea surface patterns of internal solitary waves; the second one consists in the analysis of the modulation depth of the normalized radar backscattering cross section (NRCS) associated with internal solitary waves. For this purpose we consider a data set composed of SAR and in situ measurements carried out from 1991 to 1997 in the region of the Strait of Messina. The recognition and the interpretation of sea surface patterns of internal solitary waves in the Strait of Messina can be used to study characteristics of the density distribution in the area: The internal wave field varies with seasonal variations in the vertical density stratification and with remotely induced variations, i.e., variations induced by the larger‐scale circulation, in the horizontal density distribution. In order to inquire into the possibility of inferring parameters of the interior ocean dynamics by analyzing the modulation of the NRCS associated with internal solitary waves, several numerical simulations are carried out using a radar imaging model. These simulations are performed by assuming different wind conditions and internal wave parameters. It is shown that an accurate knowledge of wind conditions is crucial for deriving internal wave parameters and hence parameters of the interior ocean dynamics from the modulation of measured NRCS associated with internal solitary waves.

Using ERS-2 SAR images for routine observation of marine pollution in European coastal waters

More than 660 synthetic aperture radar (SAR) images acquired over the southern Baltic Sea, the North Sea, and the Gulf of Lion in the Mediterranean Sea by the Second European Remote Sensing Satellite (ERS-2) have been analyzed since December 1996 with respect to radar signatures of marine pollution and other phenomena causing similar signatures. First results of our analysis reveal that the seas are most polluted along the main shipping routes. The sizes of the detected oil spills vary between <0.1 km 2 and >56 km 2. SAR images acquired during descending (morning) and ascending (evening) satellite passes show different percentages of oil pollution, because most of this pollution occurs during night time and is still visible on the SAR images acquired in the morning time. Moreover, we found a higher amount of oil spills on SAR images acquired during summer (April–September) than on SAR images acquired during winter (October–March). We attribute this finding to the higher mean wind speed encountered in all three test areas during winter. By using an ERS-2 SAR image of the North Sea test area we show how the reduction of the normalized radar backscattering cross section (NRCS) by an oil spill depends on wind speed.

Radar imaging of Kelvin arms of ship wakes

The wave pattern generated by a moving ship is formed by two dominant features: the turbulent wake and a 'V'-shaped pattern trailing the ship, consisting of the two Kelvin arms. In this paper we investigate the radar imaging mechanism of Kelvin arms, which are formed by the cusp waves. A composite surface model for the radar backscattering at the ocean surface is used. The radar signatures of Kelvin arms can be attributed to tilt and hydrodynamic modulation of Bragg waves by the cusp waves. The proposed model allows the computation of the normalized radar backscattering cross-section (NRCS) as a function of radar frequency, polarization, incidence angle, wind speed and direction, and wavelength, direction, and slope of the cusp waves. By using this imaging model, radar signatures of cusp waves are calculated for several spaceborne Synthetic Aperture Radars (SARs): (1) the SEASAT L-band HH-polarized SAR, (2) the ERS-1/-2 VV-polarized SAR, (3) the RADARSAT C-band HH-polarized SAR, and (4) the X-, C- and L-band multipolarization SARs of the Space Radar Laboratory flown on the space shuttle during the SIRC/X-SAR mission in 1994. The results of the simulations are compared with SEASAT and SIR-C/X-SAR imagery of ship wake patterns. It is shown that the dependence of the observed radar signatures of Kelvin arms on radar look direction is consistent with the proposed imaging theory and that the measured relative mean NRCS values induced by Kelvin arms can be fairly well reproduced by the proposed model. The simulations indicate that ship wake signatures should be more clearly visible on SEASAT L-band SAR than on ERS-1/-2 or RADARSAT C-band SAR images. The radar signatures of Kelvin arms are strongest at low wind speeds and are not very sensitive to wind direction.

Mesoscale wind measurements using recalibrated ERS SAR images

The precision images (PRI) of the synthetic aperture radars (SAR) on board the European Remote Sensing Satellites ERS‐1 and ERS‐2 are used to derive mesoscale wind fields over the ocean. For calculation of the wind speed the C‐band model (CMOD4) is used, which was originally developed by Stoffelen and Anderson [1993] for the European Space Agency (ESA) to derive wind fields from measurements of the wind scatterometer (SCAT). In the case of the ERS‐1/2 SAR the CMOD4 is used to compute the wind speed from the normalized radar backscatter cross section (NRCS) and the incidence angle of the radar beam, both computed from the SAR.PRI data. The third input variable is the wind direction, which is estimated from the wind streaks in the images or from ground truth measurements. The SAR data are affected by a power loss, caused by saturation of the analog to digital converter (ADC) of the SAR. Therefore the images have to be recalibrated. Errors in the derived wind speed are mainly due to ADC saturation and uncertainties of the input wind direction. These errors are estimated for various wind conditions. Mesoscale wind fields computed from ERS‐1/2 SAR.PRI images taken between the Shetland Islands and the west coast of Norway are compared to ground truth measurements and modeled wind fields from the German weather service (DWD). Wind fields of the nonhydrostatic mesoscale model Geesthacht simulation model of the atmosphere (GESIMA) are compared to the derived wind field of the ERS‐1 SAR.PRI image at the island Rügen in the Baltic Sea.

An improved composite surface model for the radar backscattering cross section of the ocean surface: 1. Theory of the model and optimization/validation by scatterometer data

An improved composite surface model for the calculation of the normalized radar backscattering cross section (NRCS) of the ocean surface at moderate incidence angles is presented. The model is based on Bragg scattering theory. A Taylor expansion of the NRCS in the two‐dimensional surface slope yields nonzero second‐order terms which represent a first approximation for the effect of the geometric and hydrodynamic modulation of the Bragg scattering facets by all waves that are long compared to these facets. The corresponding expectation value of the NRCS varies with the wave height spectral density of all these waves, and it depends in a well‐defined way on frequency, polarization, incidence angle, and azimuthal look direction of the radar. We show that measured NRCS values at frequencies ranging from 1 GHz (L band) through 34 GHz (Ka band) and wind speeds between 2 and 20 m/s can be well reproduced by the proposed model after some reasonable tuning of the input ocean wave spectrum. Also, polarization effects and upwind/downwind differences of the NRCS appear to be relatively well represented. The model can thus be considered as an advanced wind scatterometer model which is based on physical principles rather than on empirical relationships. The most promising field of application, however, will be the calculation of NRCS variations associated with local distortions of the wave spectrum by surface current gradients or wind effects.