Spaceborne synthetic aperture radar (SAR) provides high-resolution sea surface observations to characterize oceanic and atmospheric variability at submesoscales. Despite significant progress in retrieving wind fields from SAR images, challenges remain particularly for single-antenna measurements where wind speed inversion often requires an external wind direction input. This study introduces and evaluates the use of directional features derived from SAR image sublook cross-spectra to improve wind retrieval. Specifically, we explore the imaginary part of SAR mean cross-spectra (IMACS) and its differential counterpart,$\Delta $IMACS, which capture directional signatures of range-traveling intermediate wind waves. Using systematically collocated Sentinel-1A wave mode SAR images and model winds, we demonstrate that IMACS exhibits a cosine-like dependence on wind direction at given wind speeds at two incidence angles, while$\Delta $IMACS reveals unique sensitivities that complement radar backscattering and can resolve wind direction ambiguities. A novel cost function combining radar backscattering, IMACS, and$\Delta $IMACS is proposed to retrieve wind vectors directly from SAR data without external wind direction inputs. The proposed scheme is evaluated through comparisons with independent model outputs and buoy measurements, showing improved performance. These findings highlight the potential of IMACS and$\Delta $IMACS to enhance self-sufficient wind inversion, offering a promising pathway for single-polarized SAR wind retrieval.

Water surface current velocity is an important hydrologic parameter. A novel method for retrieving surface current velocities by using K-band coherent radar is proposed. First, to mitigate the impact of noise on radar echo, a convolutional neural network (CNN) is employed to extract the main wave pattern from orthogonal radar echoes. Second, to retrieve the current velocity with high temporal resolution, a method based on continuous wavelet transform is developed. The proposed method is validated by using a K-band radar and a wave channel in field experiment. For current velocities in the range of 0–1.8 m/s, the average error between the retrieved current velocities and the true velocities is less than 0.07 m/s, and the root mean square errors between them range from 0.03 to 0.16 m/s, indicating that the proposed method is reasonable. Finally, the application condition of the method is discussed.

This article presents a new simulator able to generate raw data for ocean wave radar spectrometer (OWRS). Data simulation involves three key procedures: generating 2-D sea wave height, velocity, and acceleration fields by use of a prescribed ocean wave height spectrum; calculating the 2-D sea surface normalized radar cross section (NRCS) field using a quasi-specular backscatter model; and incorporating the generated sea wave height, velocity, and acceleration fields into the radar instantaneous range equation (IRE). Our simulator’s reliability in replicating real-world ocean wave spectra has been confirmed by comparing retrieved wave spectra from simulated OWRS raw data with input reference wave spectra and real-measured radar data. The proposed simulator has several advantages over conventional simulators. Notably, OWRS data generated by the proposed simulator are complex in-phase/quadrature-phase (I/Q) raw data, instead of backscattered power modulation data as simulated by conventional simulators. Our simulator’s other advantages include its ability to reflect the effect of Doppler modulation induced by the motions of the radar platform and the sea waves in the speckle noise spectrum after processing OWRS raw data simulated by the proposed simulator, as well as its ability to embody the effect of range modulation caused by the sea surface topography, including both linear and higher order range modulation effects, in retrieved wave slope spectra. Our simulator offers a powerful tool for understanding complicated interactions between ocean wave dynamics and radar signals. Furthermore, it also provides radar engineers with a cost-effective way to evaluate potential designs for future spaceborne OWRS.

A three-component model is often used to invert the phytoplankton size class (PSC) concentration globally, especially in open oceans. Limited by the assumption of this three-component model, new efforts have been made to explore PSCs in different bathymetric regions. Mass global cruise datasets were gathered and classified into coastal, mixed, and open ocean datasets determined by the variation in bathymetric depth. A new three-component power model was established for coastal water samples (< 50 m), where the determination coefficients ($R^{2}$) were 0.95, 0.37, and 0.44 for microphytoplankton (Micro), nanophytoplankton (Nano), and picophytoplankton (Pico), respectively. We also updated the coefficients of the three-component exponential model in the open ocean (>200 m) and found that the PSC verification results performed better in the ocean north of the 40° S latitude line ($R^{2}= 0.83$, 0.70, and 0.64, respectively). A smooth function for the samples in mixed ocean waters (50–200 m) was designed to obtain PSCs with different weights between the three-component power and exponential models with relatively low accuracy ($R^{2}=0.84$, 0.37, and 0.14, respectively), which is indicative of the complex conditions in these regions. The global PSC proportion distribution is consistent with the existing knowledge in this field. Finally, we analyzed the performance and limitations of different PSC models based on the entire dataset and found that the proposed model outperformed the others, and the assumption of the three-component exponential model may fail in the Southern Ocean.

The surface wave investigation and monitoring (SWIM) aboard the China-France Oceanography Satellite (CFOSAT), a pioneer conically scanning wave spectrometer, was successfully launched on October 29, 2018. Its innovative configuration composed of one nadir and five rotating near-nadir beams is designed to simultaneously observe the directional wave spectrum at a global scale. In this study, we systematically implement the spectral analysis of the radar backscattering with the periodogram technique to obtain the fluctuation spectrum for each azimuth direction. The 2-D fluctuation spectrum of the three spectral beams ($\theta = 6^\circ $, 8°, and 10°) combines all the azimuth directions within one entire rotation of 360°. The case study demonstrates that the wave features (peak wavelength and direction) are roughly consistent between the estimated fluctuation spectrum and the collocated WaveWatch III wave slope spectrum. A marked up-to-downwave asymmetry of the fluctuation spectrum with larger spectral level in the upwave direction for all the three spectral beams is observed. A ratio is defined between the fluctuation spectrum within the [0°, 180°] sector relative to the [180°, 360°] sector. Statistics display that this ratio is greater than 1 when it denotes the up-to-downwave ratio and smaller than 1 for the down-to-upwave ratio. This observed spectrum asymmetry is linked to the asymmetric modulation from upwind to downwind. In addition, we employ such finding to help remove the 180° wave direction ambiguity from a practical point of view. Preliminary results of the direction ambiguity removal display a bias of 41.3°, 40.6°, and 36.7° for the beams. The 10° beam shows slightly better performance compared to the other two beams in terms of bias and standard deviation. This shall lay a strong basis for the operational implementation of such algorithm to resolve the direction ambiguity.

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 two-dimensional (2D) normalized backscattering radar cross section (NRCS) for 2D global ocean-surface wave detection. In this paper, the 2D 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 are 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 2D total large-scale mss map and be used as a new data resource for global applications.

Sea surface winds derived from the spaceborne rotating pencil-beam scatterometers, such as the current Chinese Haiyang-2 (HY-2) scatterometers and the Indian SCATSAT-1 scatterometer, are used in a wide range of atmospheric and oceanic applications. One key problem of the pencil-beam scatterometers is the relatively low wind quality in the nadir region, due to the poor azimuth diversity of the nadir-track observations. This article proposes to include the altimeter backscatter measurements in the wind inversion to improve the retrieved wind quality in the nadir region of HY-2B scatterometer (HSCAT). First, empirical model functions are developed to relate the C- and Ku-band altimeter backscatters to the neutral surface winds at 10-m height. Subsequently, the maximum likelihood estimator, which is commonly used to perform wind inversion for satellite scatterometers, is adapted to retrieve winds with simultaneous scatterometer and altimeter measurements. The significance of altimeter measurements in the combined wind inversion is addressed by comparing the cost functions of the combined scatterometer/altimeter wind retrieval and the nominal scatterometer inversion. The experimental results are eventually validated using moored buoy winds and the European Centre for Medium-range Weather Forecasting (ECMWF) model winds, indicating that the inclusion of altimeter backscatters has a positive impact on the wind quality over the HSCAT nadir region. Finally, the potential approaches to further improve the combined scatterometer and altimeter wind inversion are summarized.

The investigation of submesoscale coastal eddies requires the products of high spatiotemporal resolution. MODIS color index (CI) products can improve spatial coverage in coastal regions to detect submesoscale signals, when observations of high-frequency radars are limited in small areas. In our study, a gradient parameter derived by CI images is used to identify submesoscale eddies by the eddy detection algorithm based on the vector geometry in the case of Subei Shoal. The results show that gradient parameters have the ability to detect submesoscale eddies. The mean radius values of anticyclonic and cyclonic eddies are 1.85 and 1.56 km, respectively. This method makes it potentially useful for investigations of ecosystem distributions in other coastal regions.

Synthetic aperture radar (SAR) has proven to be an important tool for the retrieval of ocean surface currents. However, existing spaceborne SAR systems can usually measure only one component of an ocean current vector. In this article, we propose a new concept of dual-look spaceborne SAR system for ocean surface motion remote sensing. The key of the proposed SAR system lies in the use of a technique called intrapulse beam switching (IPBS) implemented by a phased array antenna. One example for the application of the proposed IPBS-based SAR system is its combination with the Doppler centroid anomaly (DCA) method. Through the combination, the DCA method, which in its conventional version can measure only the radial component of a current vector, is generalized to measure full ocean current vectors. A system design example and its performance evaluation demonstrate that the accuracies for ocean surface velocity vector measurement better than 5 cm/s in both azimuth and range, and better than 10° in velocity direction for a mild current, and a swath width of about 100 km, can be achieved. A comparison with other beam-generating schemes indicates that a relatively large swath width, without compromising the current-measuring accuracy, can be achieved by the proposed SAR system with one single antenna array and one single physical output channel-a feature that means a high level of integration which in turn allows for the flexibility to operate this system in multiple SAR modes.

The first rotating fan beam scatterometer onboard China-France Oceanography Satellite (CFOSAT) was successfully launched on October 29, 2018. CFOSAT SCATterometer (CSCAT) is dedicated to the monitoring of sea surface wind vectors but also provides valuable data for the applications over land and Polar Regions. This article provides an overview of the relevant procedures of CSCAT data processing, including onboard signal processing and operational ground processing. Then a post-launch analysis is carried out to evaluate the first results of CSCAT L1 and L2 products. It shows that the CSCAT instrument is generally stable in terms of noise measurements and internal calibration, unless there is any important change in the system configuration. Specifically, the CSCAT backscatter (σθ) precision and wind quality are studied using a set of collocated ancillary data. The σθprecision degrades as wind speed decreases, and it is relatively low at high incidence angles (e.g., θ >46°). In particular, backscatter estimation of the horizontally polarized beam should be further improved by correcting the noise subtraction factor. The retrieved CSCAT winds are in good agreement with the European Centre for Medium Range Weather Forecasts (ECMWF) winds, the Advanced Scatterometer (ASCAT) winds, as well as the buoy winds. However, due to unresolved calibration and interbeam consistency problems, the wind quality degrades remarkably for the out-swath and the nadir-region wind vector cells, implying that the σθcalibration should be improved in the future updates.

The new Ku-band scatterometer (HSCAT-B) onboard the HY-2B satellite was launched on October 25, 2018, and soon after the C-band scatterometer (Advanced Scatterometer (ASCAT)-C) onboard the MetOp-C satellite was launched on November 6, 2018. This article aims to validate the new sea surface wind products from them, and also to summarize the common issues in current scatterometer wind products. Thus, other scatterometer data are also used for comparisons, including the C-band MetOp-B/ASCAT, and Ku-band SCATSAT-1/OSCAT2 and HY-2A/SCAT winds. In this study, the C-band and Ku-band scatterometer wind products were each reproduced using the same procedures, in terms of backscatter calibration, wind retrieval, and quality control. The scatterometer winds are compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 winds or buoy winds, and the results show that the quality of ASCAT-C winds is almost the same as the well-known ASCAT-B; the HSCAT-B winds show quite good quality and similar validating statistics as ASCAT winds. Noticeable wind-speed-dependent biases are found in all Ku-band scatterometer winds, which suggests that refinements are needed for the NSCAT-4 geophysical model function, especially in terms of wind speed dependence for all incidence angles.

The sea surface winds from the CFOSAT scatterometer (CFOSCAT) are retrieved using the maximum likelihood estimator, and the inversion residual is used to sort the good-quality winds from the poor-quality ones. A two-dimensional variational analysis ambiguity removal (2DVAR) scheme is then applied over the CFOSCAT swath such that a unique wind field is selected from the available local scatterometer wind vector ambiguities. The preliminary results of CFOSCAT Level 2 (L2) processing show that the retrieved wind speed is overestimated under low-wind conditions (w15 m/s). Moreover, the inversion residual for the sweet swath (where there are more than 10 views) is generally higher than that for the nadir/outer swath. These imply that observations with different geometries (views) at the same WVC are inconsistent with respect to the geophysical model function, and thus a comprehensive calibration is highly demanded. A more detailed assessment of the CFOSCAT wind quality will be carried out after calibration and validation campaign.

To investigate the capability of ocean wind monitoring by the C-band compact-polarimetry (CP) Synthetic Aperture Radar (SAR), we develop a theoretical model based on the fundamental mechanisms of interactions between sea surface wind-waves and radar microwave. We simulate the dependencies of the NRCSs (normalized radar cross-sections) on wind speeds and incidence angles, for up-wind (wind direction is 0o) and cross-wind (wind direction is 90o) conditions. Analysis of the model results lead to two ocean wind retrieval methods for RV-polarization and RH-polarization (pol) SAR (Synthetic Aperture Radar) data, respectively. The RV-polarized method is proposed based on the CMOD framework and a sensitivity analysis, while the RH-polarized method and model are based on application of a quadratic function. Both the theoretical model and wind retrieval methods suggest that the RV-pol should be more suitable for ocean wind especially hurricane monitoring than the RH-pol method. The database used in this study includes wind vectors observed by in situ buoys of the National Data Buoy Center (NDBC) and simulated C-band CP radar signals, created by a simulator based on imputing C-band RADARSAT-2 SAR images.

We report an investigation of ocean-surface wind speed retrieval from C-band RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) images using a new channel of coright-circular polarization (RR-pol) in compact polarimetry (CP) option. The analysis of simulated RCM quad-polarized CP SAR data and collocated in situ buoy measurements suggests that the RR-pol is much less sensitive to wind directions than the other three polarizations in the CP option. A method is proposed for the RR-pol radar signal as a function of wind speed and incidence angle. We demonstrate that C-band RR-pol has the potential for ocean high wind retrieval, especially for cyclone studies.

The China-France Oceanography Satellite (CFOSAT) to be launched in October 2018 will carry two innovative payloads, i.e., the surface wave investigation and monitoring instrument and the rotating fan-beam scatterometer [CFOSAT scatterometer (CFOSCAT)]. Both instruments, operated in Ku-band microwave frequency, are dedicated to the measurement of sea surface wave spectra and wind vectors, respectively. This paper provides an overview of the system definition and characteristics of the CFOSCAT instrument. A prelaunch analysis is carried out to estimate the scatterometer backscatter and wind quality based on the developed CFOSCAT simulator prototype. The overall simulation includes two parts: first, a forward model is developed to simulate the ocean backscatter signals, accounting for both instrument and geophysical noise. Second, a wind inversion processor is used to retrieve wind vectors from the outputs of the forward model. The benefits and challenges of the novel observing geometries are addressed in terms of the CFOSCAT wind retrieval. The simulations show that the backscatter accuracy and the retrieved wind quality of CFOSCAT are quite promising and meet the CFOSAT mission requirements.

This paper presents a comprehensive procedure to improve the wind geophysical model function (GMF) for the Global Navigation Satellite System Reflectometry (GNSS-R) instrument onboard the TechDemoSat-1 satellite. The observable used to define the GMF is extracted from the measured delay-Doppler maps (DDMs) by correcting for the nongeophysical effects within the measurements. Besides the instrument and the geometric effects as provided in the bistatic radar equation, a calibration term that accounts for the uncalibrated receiver antenna gain and the unknown transmitter antenna gain is proposed to optimize the calculation of GNSS-R observables. Such calibration term is presented as a function of observing elevation and azimuth angles and is shown to remarkably reduce the measurement uncertainties. First, an empirical wind-only GMF is developed using the collocated Advanced Scatterometer (ASCAT) winds and European Centre for Medium-Range Weather Forecasts (ECMWF) model wind output. This empirical GMF agrees well with the model output. Then, the sensitivity of the observable to waves is analyzed using the collocated ECMWF wave parameters. The results show that it is difficult to include mean square slope (MSS) in the development of an empirical GMF, since the difference between ECMWF MSS and the MSS sensed by GNSS-R varies with incidence angle and wind speed. However, it is relevant to take significant wave height (Hs) in account, particularly for low wind conditions. Consequently, a wind/Hsapproach is proposed for improved wind retrievals.

We present a new algorithm for suppressing azimuth ambiguities when measuring surface currents with an along-track interferometric (ATI) synthetic aperture radar in heterogeneous scenes, such as coastal waters or rivers. The key of the proposed algorithm involves a careful analysis of a parameter called the eigenvalue spectrum entropy (EVSE), which is defined as the entropy of the eigenvalue spectrum of the ATI covariance matrix computed in the Doppler domain. The physical meaning of EVSE is that it serves as a descriptor for the degree to which an unambiguous signal component and an ambiguous one are mixed. With the help of EVSE, azimuth ambiguities can be suppressed. Simulation results demonstrate that as compared with the conventional ATI method without azimuth ambiguity suppression, the proposed algorithm allows for a pronounced improvement in the current measuring accuracy. Other advantages of the proposed algorithm lie in the fact that it is not only adaptive, due to its ability to automatically capture the useful Doppler band whose width and position may both vary for different radar and scene parameters, but it also needs a minimal number of user inputs, making it a quite attractive algorithm for routine implementation.

The Ku-band rotating fan-beam scatterometer (RFSCAT) onboard the China-France Oceanography Satellite (CFOSAT) is dedicated to the measurement of sea surface wind vectors. The flight model of RFSCAT has been assembled and tested, and the data processing algorithms have been developed. This paper provides an overview of the design and characteristics of RFSCAT instrument, and then a prelaunch analysis is carried out to estimate the scatterometer backscatter and wind accuracy. The overall study includes two parts: first, a forward model is developed to simulate the ocean backscatter signals under certain wind conditions; second, a wind inversion processor is used to retrieve sea surface wind vectors from the outputs of the forward model. Simulations show that the backscatter accuracy and the retrieved wind quality of RFSCAT are quite promising and meet the scientific requirements of the mission.

We use multiple satellite observations and numerical simulation to investigate the upper ocean response to Typhoon Kalmaegi in 2014 in the South China Sea (SCS). In this study, significant sea surface temperature (SST) decreasing is observed, which is caused by typhoon-induced vertical mixing and upwelling. The maximum SST cooling is 2 °C on the right of the typhoon track since inertial currents rotate in the same direction as the surface wind vectors. We also find an interesting phenomenon that salinity decreases ranging between 0.3 and 0.6 psu on the left side of the typhoon track. We use numerical simulations and in-situ observations to further confirm that salinity reduction is caused by heavy rainfall.

The conventional linear modulation transfer function (MTF) was derived using HH-polarized marine radar observations in deepwater conditions. It is possible to constrain this MTF for ocean surface wave spectra retrieval in coastal shallow waters. In this letter, we propose a new MTF with both range and azimuth dependence based on VV-polarized radar measurements acquired from heterogeneous coastal wave fields. This new MTF is determined using a radar-observed image spectrum and in situ buoy-measured wave frequency spectrum. To assess the proposed MTF, we compare the buoy-measured 1-D wavenumber spectrum with those obtained using different MTFs. Compared to the conventional linear MTF, the new MTF-derived wavenumber spectrum is closer to buoy measurements. The retrieved peak and mean wave periods are also validated using concurrent wave buoy measurements. It is shown that the retrieval accuracies of peak and mean wave periods of the new MTF are better than those of the conventional MTF. The bias and root mean square errors of the peak and mean wave periods of the new MTF are 0.52 and 0.95 s and 0.26 and 0.48 s, respectively. This suggests that the proposed new MTF is more appropriate for retrieving integral wave parameters than the conventional linear MTF.

A new method is proposed to retrieve wave height from an X-band marine radar image sequence, without external measurements for reference. The X-band marine radar image sequence is first decomposed by empirical orthogonal function (EOF), and then the sea surface height profile is reconstructed and scaled from the first EOF mode. The radial profiles that are close to the peak wave direction are used to extract the zero-crossing wave periods and relative wave heights. The spectral width parameter is deduced from the histogram of a dimensionless wave period. Based on a joint probability distribution function (pdf) of a dimensionless wave period and wave height, the theoretical pdf of the wave height is derived. A shape parameter is defined for the theoretical pdf and the histogram of the relative wave heights, and then the calibration coefficient is estimated. The method is validated by comparing the significant wave heights retrieved from two different X-band marine radar systems with those measured by buoy; the correlation coefficient, the root-mean-square error, and the bias between them are 0.78, 0.51 m, and -0.19 m for HH polarization, while they are 0.77, 0.51 m, and 0.19 m for VV polarization, respectively. The sources of error of the method are discussed.

The emergence of sea surface current has a significant impact on electromagnetic (EM) backscattering signals. This may be one of important synthetic aperture radar (SAR) imaging mechanisms of ocean currents. Fractal sea surface ocean wave-current model is derived based on the mechanism of wave current interaction in this paper. A effective EM backscattering model of one dimensional drifting fractal sea surface is presented. numerical results show that both magnitude and direction of ocean current have effects on EM backscattering signals from one dimensional ocean wave-current coupled fractal sea surface. The existence of ocean currents which paralleling to the direction of wave can weaken EM backscattering signal intensity. EM backscattering signal intensity can be strengthened by ocean currents propagating in the opposing direction of wave.

Tide has been monitored by tide-gauge stations and spaceborne radar altimeters. A new method to estimate the characteristics of coastal tide from X-band marine radar image sequences is proposed. The significant wave height (SWH) is firstly retrieved from X-band marine radar image sequence, and then filtered to remove the influences of noises. The main tide period is retrieved by analyzing the spectrum of the time series of filtered SWH. The change rate of the tide elevation can be obtained from the change rate of the amplitude of filtered SWH. The method is validated by comparing with the predictions from an ocean tide model.

Stepped-Frequency Microwave Radiometer (SFMR) measurements and Precipitation Radar (PR) data on Tropical Rainfall Measuring Mission (TRMM) are collocated to acquire the normalized radar cross sections (NRCS) at low incidence angles. At the same time, the whitecap coverages are concluded from averaging previous results. Using the formation of Kudryavtsev et al, the NRCS of whitecap is obtained. The simulation and retrieval of the sea waves with whitecap are acquired. It is indicated that the sea wave spectrum with whitecap can be corrected with the help of wind speed provided by the rotating scatterometer on the same satellite.

Oil spill has been a crucial hazard to the coastal environment. A major difficulty of Synthetic Aperture Radar (SAR) based oil-spill detection algorithms is the classification between mineral oil and biogenic look-alikes. Polarimetric SAR features provides helpful information in disguising mineral oil and its look-alikes. In this study, we focused on the extraction and selection of fully polarimetric SAR features for the classification between mineral and biogenic look-alikes. Three mainly used supervised classifiers including Support vector machine (SVM), Artificial neural network (ANN) and Maximum likelihood classification (ML) were comparatively studied. In the experiment, classification performance increases with the growth of the feature number initially, but still fluctuates or decreases after the sufficient features are considered. It was also discovered that among all the classifiers, support vector machine performed best.

The accurate observation and prediction of tides are important in coastal waters. A new method is proposed to estimate tidal constituents in nearshore waters from X-band marine radar image sequences, based on the modulation of wave height by tide. The relative wave height is retrieved from the first principal component of the X-band marine radar image sequence, and a self-adaption method is used to remove the low-quality data under very low sea state. To eliminate the influence of atmospheric planetary waves, a type I Chebyshev bandpass filter is applied to the time series of the derived wave heights. Relative tidal amplitudes and phases are then obtained through harmonic analysis of the filtered wave heights, and true tidal amplitudes are derived through a linear relation, while true tidal phases are obtained by cross-spectral analysis. The errors of the amplitudes of M2, S2, K1, and O1 tides retrieved from X-band marine radar image sequences are 0.15-1.12, 2.22-3.83, 3.06-4.29, and 4.50-9.47 cm, respectively, as compared with those predicted by a numerical model; the errors of M2 tidal phase are 3.27°-4.59°. It shows that the proposed method is appropriate for long and continuous observations of X-band marine radar.

We present a ocean surface waves and winds simultaneous retrieval method for the RADARSAT-2 fully polarimetric synthetic aperture radar (FP-SAR) imaging mode. This algorithm integrates FP-SAR wind vector retrieval model with nonlinear mapping relations between ocean wave spectrum and SAR image spectrum, to synergistically retrieve wind field and wave directional spectrum. The method does not require a priori information on the sea state. The proposed method can simultaneously acquire ocean surface wave and wind information.

Over the last several years, considerable efforts have been devoted to investigate hurricane surface winds using SAR observations [1]-[6]. Compared to optical satellite sensors, synthetic aperture radar (SAR) has advantages for observation of ocean surface winds, with high resolution and large spatial coverage, in almost all-weather conditions. Measurements of the inner-core intensities and tangential wind profiles are generally provided by NOAA aircraft flying though the hurricanes [7]. However, aircraft only can provide single point observations along the flight track. Thus, there can be some variance in the aircraft-measured tangential wind profiles, particularly for those hurricanes with asymmetric wind structures. For example, for a non-symmetric hurricane with an elliptic eye, we can assume that the true maximum wind speed exists somewhere on the major axis direction. Therefore, if the aircraft flies along the minor axis of this hurricane, instead of the major axis, the maximum wind and the radius of maximum wind (RMW) observations are probably not accurate. In this study, we determine the hurricane eye center and its extent, and propose a model to estimate hurricane intensity and structure parameters. A specific objective is to describe the tangential wind profile corresponding to the reintensification phase in the hurricane eyewall replacement cycle (ERC).

The geophysical model function is generally employed to invert the surface wind speed using scatterometer or synthetic aperture radar (SAR) measurements over the ocean. The GMF relates the normalized radar cross-section (NRCS) to the incidence angle and wind vector. The rain effect on NRCS is not considered in the GMF. In raining areas, the NRCS of the ocean surface is altered by rain. Rain contamination introduces errors to wind speed retrieved by scatterometer, particularly at high incidence angles [1]. Moreover, under extreme weather conditions, significant differences exist between the SAR retrieved wind speed and those measured by Stepped-Frequency Microwave Radiometer (SFMR) measurements in hurricane eyewall regions [2], due to the intense rainfall there. The challenges in satellite retrievals of ocean winds related to precipitation effects has been elaborated in [3].

A new algorithm to retrieve wave parameters, such as significant wave height (SWH), peak wave period, wavelength, and wave direction, from marine X-band radar image sequences is proposed. To analyze the heterogeneous nearshore wave field, the empirical orthogonal function is used to extract the principal components (PCs) of the radar image sequence. To retrieve the SWH, a linear relationship between SWH and the standard deviation of PC is established. The maximum entropy power spectral density (PSD) of the first PC is used to derive the peak wave period. The PSD on spatial scale is used to estimate two perpendicular components of the wavelength, and then, the wavelength and wave direction are determined by geometric relationship. Inversion schemes are validated by comparing with data from the in situ buoy; the root-mean-square error between the wave parameters retrieved from radar image sequences and measured by the buoy is 0.21 m for SWH and 0.84 s for the peak wave period, and the biases for these are 0.01 m and 0.33 s.

Recent studies show the promising ability of cross-polarization synthetic aperture radar (SAR) for high-wind-speed monitoring. However, no dual-polarization (dual-pol) geophysical model functions (GMFs) have thus far been established. In this paper, we first address the difference between dual-pol and quad-pol VH radar returns with respect to wind speed and show the necessity of having a VH dual-pol GMF for ScanSAR images, for remote sensing of mesoscale wind processes, such as hurricanes. By collocating VH dual-pol RADARSAT-2 SAR measurements with in situ buoy winds, a VH dual-pol GMF was developed after introducing a denoise procedure to increase the signal-to-noise ratio for SAR measurements. Study results suggest that the VH dual-pol radar returns have a linear monotonic piecewise increasing dependence on wind speed, with decreasing scatter in high winds. Successful application of the GMF to high-wind-speed retrieval for hurricane Gustav in 2008 suggests that VH mode SAR images do not exhibit signal saturation or the speed ambiguity problem that affects copolarization SAR images for high-wind-speed retrieval. This result supports the potential future application of VH dual-pol SAR images to hurricane monitoring.

Hurricane tangential wind profiles are routinely observed by aircraft reconnaissance in order to estimate the surface winds. However, these wind profile estimates are occasionally biased because along-track aircraft observations might not determine the nonaxisymmetric hurricane structure characteristics. In this paper, we resolve this problem by calculating the mean wind speed in all radial directions using cross-polarization SAR wide-swath images. Moreover, we propose a one-half modified Rankine vortex (OHMRV) model to describe the hurricane wind profile, particularly for those wind profiles with a wind speed maximum and an inflection point possibly associated with the degeneration of the inner wind maximum in the hurricane reintensification phase. OHMRV characterizes the hurricane wind profile and represents a model that complements the previously established single-modified Rankine vortex model and the double-modified Rankine vortex model. Moreover, the OHMRV-derived wind profiles are used to estimate hurricane intensity and structure parameters, such as the maximum wind speed and the radius of maximum wind. For validation of the method, the estimated ISPs are compared with measurements by the stepped-frequency microwave radiometer on board the National Oceanic and Atmospheric Administration aircraft. These parameters contribute to a description of hurricane inner-core intensity and structure associated with eyewall replacement cycles.

In this Paper presentation, compare the normal Radar backscatter coefficient between oil spill area, clean sea area, Ship, platform area and Enteromorpha area. The result display the backscatter coefficient of oil spill area is lower than clean sea and the Enteromorpha area, ship, platform area is higher than clean sea.

We presents a new method for retrieving tropical cyclone vector winds using C-band dual-polarization SAR observations. The co-polarized geophysical model function (CMOD5.N) and a cross-polarized wind speed retrieval model for dual-polarization (C-2POD) are employed to construct a cost function. minimization of the cost function allows optimum estimates for the wind speeds and directions. The wind direction ambiguities are removed by a parametric two dimensional sea-surface inflow angle model.

We present a innovative physically-based approach to detect oil platforms by using compact polarimetric (CP) synthetic aperture data. We utilize two RADARSAT-2 fine quad-polarization SAR images of Gulf of Mexico to estimate the CP covariance matrix. The resulting CP data is used to reconstruct pseudo quad-polarization covariance matrix. The Stokes parameters are evaluated using the reconstructed pseudo quad-polarization covariance matrix elements. We further calculate the relative phase with two Stokes parameters. The relative phase is a logical scalar descriptor which can be used to detect the oil platforms. The detected oil platforms are validated with ground truth from NOAA. The proposed method provides a simple and effective mapping technique for oil platform detection.

This paper discusses the potential for automatic ocean surveillance using compact linear polarization (CL-pol) synthetic aperture radar (SAR), with large area coverage. Here, the target is a wind farm in the North Sea. The relative phase, as derived from CL-pol SAR, is employed for detection of the wind turbines, apart from the wind turbines' wakes, based on fine-mode quad-polarization (quad-pol) RADARSAT-2 (RS-2) images. The relative phase of CL-pol measurements improves the contrast between the wind turbines and their wakes, because it has opposite signs for these two entities. Moreover, there is almost no variation in the relative phase with respect to wind speed or incidence angle. The results are verified by high-sea-state cases, up to 8.7-m significant wave height and 24.3-m/s wind speed, and also 641 quad-pol RS-2 SAR images collocated with 52 National Data Buoy Center buoys at different incidence angles and sea states. Thus, the relative phase of CL-pol SAR provides new light into the problem of operational autodetection of man-made targets, under high-sea-state conditions, over large areas.

The determination of significant wave height (SWH) from marine X-band radar image sequences is based on an empirical relationship with the signal-to-noise ratio (SNR). To reduce the dependence of in-situ calibrations, the variations of SNR with the range from the radar station and the relative azimuth between the antenna looking angle and the wave propagation direction are analyzed. Then a method was developed to correlate the SNR with the fluctuations of the sea surface elevations, by taking out the variations of SNR with range and azimuth. Moreover, the method is validated using marine X-band radar image sequences from a field experiment, comparisons of the corrected SNR with a buoy show that the method gives a more accurate estimation of SWH than the uncorrected SNR does. Besides, the method can remove the influence of the noise caused by light rain as well.

Mechanical energy input into the ocean from the atmosphere is primarily produced via the ocean surface waves. First, the total wind generation surface wave energy is estimated as nearly 80 TW (1 TM = 1012W), based on an empirical formulation and the wave age (β) retrieved from the Earth Remote Sensing-1/2 satellite scatterometer observations. Second, the distribution of the wind-generated surface wave energy density shows that the main input occurs in the westerlies in the Southern Hemisphere and could reach up to 3.58 W/m2with an average value of 0.24 W/m2in the global ocean during a seven-day period. Third, we find that the downward energy flux rate from wind to surface waves can reach around 24% in the Southern Ocean and storm tracks in the northwest Pacific and Atlantic Oceans where the wind waves dominate, but a low downward rate of around 7% in tropical oceans with an average of 11% over the global oceans is observed.

By using ten years of collocated Precipitation Radar and buoy data, the relationships between Ku-band normalized radar cross section (σ°) and integrated wind and wave parameters (e.g., significant wave height, wave period, wave steepness, and wave age) at low incidence angles are analyzed for different sea states using correlation and dependence analysis. The results show that the relationships are significantly different for different sea states. Second, the potential for inverting these parameters directly from a single σ° is investigated. The results reveal that the retrieval of wind speed above 10 m (U10) is most suitable for a nonpure-swell sea and that the performance of significant wave height (Hs) retrieval decreases with the ratio of swell to wind waves. For wave period and wavelength, a feasible inversion can only be performed for a wind-wave-dominated sea. Wave steepness (δa) is strongly correlated with σ° in all sea states and can even be higher than that forU10in pure-swell seas. It is suggested from the present data set that real wave age (β) may be retrieved from a swell-dominated sea and, therefore, has a low-value cutoff. Furthermore, the extent to whichU10retrieval depends on sea state is examined by calculating the correlation coefficient between σ° residuals and various standard wave parameters and, then, by determining the partial correlation coefficient between σ° and each wave parameter controlled byU10. Both results indicate that wind direction is better taken into account above 13.5°. Moreover, an auxiliary parameter related to wave slope, such as wave steepness, would help to improve retrieval performance. Significant wave height data are of secondary use, but an implementation with real wave age information might not significantly improve wind speed retrieval. To improve the performance ofHsand wave period retrieval, auxiliary information, such as wind speed, wave steepness, or wave age, is needed. Finally, multivariable empirical models are proposed.

We present an efficient algorithm for retrieving the ocean-surface wind vector from C-band Radar Satellite RADARSAT-2 fully polarimetric synthetic aperture radar (SAR) measurements based upon the copolarized geophysical model function, i.e., CMOD5.N, and the cross-polarized ocean backscatter model, i.e., C-2PO. The analysis of fine quad-polarization mode single-look complex SAR data and collocated in situ moored buoy observations reveals that the polarimetric correlation coefficient between co- and cross-polarization channels has odd symmetry with respect to the wind direction. This characteristic is different from the feature that normalized radar cross sections for quad-polarization have even symmetry regarding the wind direction. We first use the C-2PO model to directly retrieve wind speeds without any external wind-direction and radar-incidence-angle inputs. Subsequently, the retrieved wind speeds, along with incidence angles and CMOD5.N, are employed to invert the wind direction, still with ambiguities. The odd-symmetry property is then applied to remove the wind direction ambiguities. Thus, it is shown that fully polarimetric SAR measurements provide complementary directional information for the ocean-surface wind fields. This method has the potential to improve wind vector retrievals from space.

A neural-network model was developed to retrieve the wave steepness (δ), which was used to represent the sea state (particularly wave state), from the European Remote Sensing (ERS) scatterometer onboard ERS-1/2. Using the retrieved δ and scatterometer wind speed, we calculated and examined the drag coefficient (CD) over the global ocean. The results show thatCDchanges significantly when wave steepness is included in the calculation. Combining wave steepness and wind speed increasesCDby nearly 14% on average. That change is spatially variable, ranging from -18.76% for the tropical Eastern Pacific Ocean to 104% for the Southern Ocean.

Shipboard X-Band radar images acquired on June 24th, 2009 are used to study internal solitary waves (ISWs) characteristics at northeast of the South China Sea (SCS). The studied images show one ISW in a packet. A methodology based on the Radon Transform (RT) technique is introduced to calculate internal wave parameters such as direction of propagation, internal wave velocity from backscatter image. The result shows that the ISW amplitude is more than 100 meters and it approximately propagates northwestward continent shelf at a speed of 3.04 m/s. Compared with the other researches, especially only with satellite remote sensing images, the ISW propagation speed we got seems higher than other results. A new explanation is presented among different remote sensing images. The periods of most internal waves at northeast of SCS acquired from SAR images aren't regular M2 tidal period (T = 12.4h), but less than 12.4h. This may be the reason that the ISW propagation speed we got from X-band radar images is higher than others from SAR images.

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.

Four C-band fully polarimetric synthetic aperture radar (POLSAR) images of ocean waves from the RADARSAT-2 SAR are used to measure ocean slopes and wave spectra. A new technique has been developed to measure wave slopes in the SAR azimuth and range directions. The POLSAR ocean wave parameter measurements were validated with in situ observations from an NOAA National Data buoy Center (NDBC) buoy. The results show that wave parameters measured using the new method are in good agreement with in situ NDBC measurement products.

The purpose of this study is to discuss the influence of nonlinearity upon X-band radar observations. For simplicity, the analytical dispersion relationship of finite amplitude ocean wave theory was applied and discussed. We found that the shallow water dispersion relation curve covers more ocean wave energy than deep water and linear dispersion relationship. However, the shallow water dispersion relationship filter can not derive the ocean spectrum from radar image spectrum. The accurate measurement of ocean wave amplitude and water depth may be contributed to the results. More data are needed to analyze the reasons.

In this presentation, it is studied that the response of the Kuroshio to forcing provided by three wind products: Comprehensive Ocean-Atmosphere Data Set (COADS); Hellerman & Rosenstein objective analysis data set (HR) and observations made by the ERS radar scatterometer. The sea surface currents of the Kuroshio in the Luzon Strait in winter and summer simulated by the Princeton Ocean Model with the three kind of wind fields are compared with the 20-year (1984-2003) mean surface drifter tracks from MEDs/GTS (Marine Environmental Data Service/Global Telecommunications System, Canada). The simulated surface currents from COADS and ERS wind fields are found to be closer to the mean surface drifter tracks in winter. However, the surface current from HR wind field cannot present the surface current pattern of the drifter tracks. And the model results from ERS wind field show a more accuracy surface current which can be seen from the remote sensing data analyzed by Yuan and Han (2006). In summer, the three wind products all can provide a good wind stress and the surface currents from them show the major features of the current field patterns of the drifter tracks. The distribution of the eddies driven by the three kind of wind fields are analyzed in winter and summer time, respectively.

A new model is proposed to estimate significant wave heights from ERS-1/2 scatterometer data. We find that the relationship between wave parameters and the radar backscattering cross section is similar to that between the radar backscattering cross section and wind. The model for the relation between significant wave height and the radar cross section is obtained by a neural network algorithm. When the average wave period is less than 7s, the root mean square of significant wave height retrieved from ERS-1/2 data is 0.51 m. When the average wave period is more than 7 s, it is 0.72 m.

An retrieval algorithm is developed for wind speed inside hurricanes or typhoons from microwave radiometers, SSM/I and AMSR. We match use GEM numerical weather forecast model outputs for wind speed in comparisons with SSM/I and AMSR data. The algorithm using AMSR data is better than that for SSM/I, because AMSR has two low frequencies radiometers, 6 and 10 GHz, and they are more suitable than the high frequency radiometers to retrieve wind speeds in cases involving rain. The RMS for our algorithm is less than 2 m/s or 10%. The algorithm shows improvement over recent algorithms for retrieving wind speeds inside hurricanes or typhoons.

Polarimetric scattering mechanisms of ocean surface are important for improving ocean surface scattering model and detecting objects on the ocean surface, especially at large incidence angles and wave breaking. We proposed polarimetric parameters technique to analyze the scattering mechanisms of ocean surface. Lacks of the related data, we only analyzed the variances of polarimereic parameters with incidence angles for C, L and P-band at low ocean state. The results show the polarimetric parameters are different at different incidence angles and different radar work bands. It further indicates that the same ocean surface will present different scattering mechanisms at different radar work conditions.

A new ocean wave retrieval method for the along-track interferometric synthetic aperture radar (ATI-SAR) phase image is presented. The new algorithm, named parametric retrieval algorithm (PRA), uses the full nonlinear mapping relations as proposed by He and W. Alpers (2003). It differs from previous retrieval algorithms in that it does not requireaprioriinformation on the sea state and also calibration of the ATI-SAR phase image. The advantage of PRA is that it jointly retrieves information of wave parameters and wind speed. The method has been validated by collocating two X-band HH-polarized ATI-SAR phase image and one C-band HH-polarized ATI-SAR phase image spectra with spectral buoy measurements. The wave parameters and wind speed estimated from PRA are in agreement well with buoy observations. The proposed method can be employed by future satellite missions such as TerraSAR.

A neural network wind speed (WS) retrieval algorithm was developed using 6.9 and 10.7, as well as 36.5 GHz for both horizontal and vertical polarized brightness temperature (Tb) of Advanced Microwave Scanning Radiometer-E (AMSR-E) aboard AQUA. The artificial xneural networks (ANN) technique is employed to find the transfer function relating the input AMSR-E six channels Tb and output (WS) parameter. Input data consist of nearly 12 months (January 2005 - December 2005) of AMSR-E observed brightness temperature and surface marine observations of WS from National Data Buoy Center (NDBC) and Tropical Atmosphere Ocean Project (TAO). The performance of the algorithm is assessed with independent surface marine observations. The retrieval results demonstrate that the combination bright temperatures of lower frequencies such as 6.9 and 10.7 GHz, as well as higher frequencies such as 36.5 GHz from AMSR-E as input parameters provides reasonable estimates of wind speed. The root mean square (rms) error between estimated WS from AMSR-E observations and the buoy measurements is 1.53 m/s.

Based on polarization ratio from ENVISAT ASAR, we compared the wind vectors retrieved from CMOD5 with alpha= 0.6, alpha = 0.5, our polarization ratio,VV HWGMF with our polarization ratio and HH HWGMF with results from QuikSCAT and buoy, respectively. We found that CMOD5 with alpha= 0.5 polarization ratio is best one for retrieving high wind speed from RADARSAT SAR; and error between QuikSCAT and HH HWGMF is the least. The polarization ratio and GMF for high wind need be improved.

In this presentation, the polarization ratios were calculated from AIRSAR polarimetric SAR data and ENVISAT ASAR dual-polarization data; and their empirical CC parameters which depend on incidence angle were obtained. Five C band HH polarization RADARSAT-1 SAR images are used to validate these polarization ratios and we found that the empirical parameter alpha = 0.5 is superior to other possible parameter alpha values.

A fuzzy c-mean clustering algorithm to detect ships is proposed using fully polarimetric SAR data. The algorithm is unsupervised. It does not need the statistical decision and the performance is not data specific, as often arises with CFAR methods. A distance measure, based on a complex Wishart distribution, is applied using the fuzzy c-means clustering algorithm. The algorithm makes use the statistical properties of polarimetric data, and takes advantage of a clustering algorithm. It is thus expected that the algorithm could include fully polarimetric backscattering information for ship detection. Its effectiveness is demonstrated by applying it to detect the targets in a set of AIRS AR data.

Red tides cause the serious problems in the East China Sea (ECS). Environmental and economic impacts of red tides have increased in the recent years. Thus, considerable efforts have been spent on red tides research. Ocean color remote sensing is one of the useful techniques, and the research of retrieving the concentrations of the water components has been applied in the areas. Because of the complex of the water properties, the pigment concentrations are hard to retrieve. Some algorithms, including of experiment algorithms and semi-analytic algorithms, have been developed or used to retrieve pigment concentrations. However, no suitable algorithm can be used directly to retrieve pigment concentrations in the red tides areas of the ECS now. In this paper we present a semi-analytic algorithm to retrieve the chlorophyll-a concentrations in the red tides areas of the ECS. Based on the measurements of the red-tide cruises in the ECS during 2002-2005, we have developed a spectral simulation model. Then the semi-analytic algorithm with MODIS wavelengths has been developed based on the simulation data. Different bands combinations have been trained to make the algorithm the best performance. The in situ measurements have been applied to validate the algorithm. When the concentrations of the total suspended matters are lower than 7 gm-3, the relative mean error of the algorithm is 38.34% and the correlative coefficient between the retrieved chlorophyll-a concentrations and in situ data is 0.8. The results show that the retrieved data agree well with the in situ ones. The algorithm can be used to retrieve the chlorophyll-a concentrations in the red tides areas of the ECS.

Radar backscattered signals over the ocean are dampened in extremely high winds, which leads to a wind speed ambiguity problem during the process of wind retrieval from synthetic aperture radar (SAR). This problem was firstly studied by Shen et al. (2007), where we proposed a wind speed ambiguity removal scheme for the two wind speed solutions that may exist for any given normalized radar cross section (NRCS) and wind direction. This approach is based on the operational geophysical model function (GMF) CMOD5. Recently, new C-band GMFs for high wind have been developed, among which, a HH polarized GMF was established for the first time. In this study, the wind speed ambiguity problem will be studied within the context of the available high wind GMFs, which are, CMOD5, CMOD4HW, HWGMF_V and HWGMF_H. For the wind retrieval from HH polarized SAR images, a hybrid empirical polarization ratio is generally adopted. To compare the different behavior of various GMF models, this polarization ratio is used to transform the HH polarized GMF into a VV field. Although the wind speed ambiguity problem is found in most GMFs, the saturation wind speed where radar backscattered signals start to decrease is different for the various GMFs. We show that consideration of the wind speed ambiguity problem is important for high wind retrieval from SAR images, especially for category 5 hurricanes.

In this letter, a new wind-vector algorithm is presented that uses radar backscatter sigma0measurements at two adjacent subscenes of RADARSAT-1 synthetic aperture radar (SAR) images, with each subscene having slightly different geometry. Resultant wind vectors are validated using in situ buoy measurements and compared with wind vectors determined from a hybrid wind-retrieval model using wind directions determined by spectral analysis of wind-induced image streaks and observed by colocated QuikSCAT measurements. The hybrid wind-retrieval model consists of CMOD-IFR2 [applicable to C-band vertical-vertical (VV) polarization] and a C-band copolarization ratio according to Kirchhoff scattering. The new algorithm displays improved skill in wind-vector estimation for RADARSAT-1 SAR data when compared to conventional wind-retrieval methodology. In addition, unlike conventional methods, the present method is applicable to RADARSAT-1 images both with and without visible streaks. However, this method requires ancillary data such as buoy measurements to resolve the ambiguity in retrieved wind direction

A theory of internal wave synthetic aperture radar (SAR) imaging has been improved by applying Korteweg-de Vries (KdV) equation, Bragg back scatter model, and replacing surface wave action equation with high frequency ocean wave spectrum balance equation. An analytical expression for an ocean internal wave SAR image will be obtained. Based on the new theory, the effects of wind on internal waves SAR images are studied with theoretical and scale analysis. The results indicate that the effects of wind are comparable with the hydrodynamic parameters, and the signature of internal waves can be imaged on the SAR only when oceanic state is low. The results agree well with some observations.

During the past decade, the ability to determine detailed information of ocean surface wind from Synthetic Aperture Radar (SAR) has been generally accepted. It is expected that SAR will provide all-day and all-weather wind parameters with high spatial resolution and high accuracy, which would provide valuable data to marine weather forecasters and SAR model designers. However, the methodology for retrieving wind fields from SAR is far from complete. Present procedures require that a prior wind direction must be available in order to get wind speed information from SAR images. Errors in wind direction can result in significant biases in the SAR-retrieved wind speed. The prior wind direction can be acquired from measurements of other instruments (scatterometer, buoys etc.), from meteorological model outputs, or from wind-induced slicks if evident in the SAR images. The latter method may be limited by the image; many SAR images don't have any obvious wind-induced slicks. He et al. [2005] developed a new gradient method model (GM), which can retrieve wind directions from SAR images without trying to infer slicks. However, thus far, this method can only be used in relatively uniform wind field situations. In this paper, two modifications to the GM method have been developed by introducing an optimal analysis method. Wind speed and direction (with ambiguity) can be retrieved directly. In this method, sigma0from two overlapped sub-blocks of the SAR image are used to retrieve wind parameters, which would violate the original GM method, because it cannot be used in highly varied winds, such as hurricanes. The chief advantage of this method is that wind speed can be retrieved without additional reference wind directional information. The wind direction ambiguity can be removed by background geophysical information of the SAR image or by in-situ measurements. Two cases are considered to illustrate this new method. One is a simulated image with relatively uniform wind field, and the other is a Radarsat-1 image which captures the eye of hurricane Isabel before it made landfall in North Carolina in 2003 as a category 2 storm. In both cases, the retrieved wind result is shown to compare well with Quickscat measurements andin-situdata. However, error exists for highly-varied wind field, especially for the retrieved wind direction. Future investigation will focus on this limitation, and also conduct further comparisons.

Most of Chinese adjacent seawaters are case 2 waters, while the absorption characteristics of water constituents are quite important parameters on the development of semi-analytic bio-optical algorithms. In this article, based on the in-situ data from the cruise in the Pearl River estuary and sea areas nearby during March to May in 2001, we analyzed the absorption coefficients of the three components (phytoplankton, CDOM and de-pigment particles). Exponential method was chosen to simulate the waveband relations of phytoplankton pigments absorption coefficients aph(lambda) by taking 675 nm as the reference wavelength. The empirical model between aph(675) and chlorophyll-a concentrationswas also developed with a good correlation of 0.93. We also calculated the empirical spectral slope value of the CDOM (Sg=0.0170) and that of de-pigment particles absorption coefficients (Sd=0.0116) with the relative standard errors below 10.0%. The verified results, which are tested with the dataset of the same zone at different depth, showed that this spectral model was strongly suitable for this region.

A new method is presented to retrieve near-sea surface instantaneous air temperature and dew point temperature. Satellite data include the air temperature and point temperature at 1000 mb are inversed by TOVS data. Sea surface temperature is derived from AVHRR data. Ship-measured data come from the observations of NEAR-GOOS (North-East Asia Regional- Global Ocean observing) experiment. Then two different artificial neural network models are developed to retrieve near- sea surface instantaneous air temperature and dew point temperature. For the single parameter neural network model (SANN) model, the root mean square (RMS) error of near-sea surface instantaneous air temperature and dew point temperature are 1.85degC and 2.59degC respectively, but those for multi-parameter neural network (MANN) model are 1.92degcand 2.67degC respectively. The results indicate that the retrieval accuracy of the SANN model is superior to that of the MANN model and prove that there is a close relationship between near- sea surface air temperature and dew point temperature.

Here, we present a new method to measure ocean wave slopes in the range direction using dual-polarization SAR image intensity, without need for estimation of the polarization orientation angles. This method is different from those developed by Shuler et al. and Pottier.. In addition, it eliminates the effect of the not well known hydrodynamic modulation on retrieving ocean surface spectra from SAR data Comparisons will be made between ocean wave spectra measured using ENVISAT C band dual-polarization (HH and VV) backscatter data and in situ buoys maintained by NOAA National Data Buoy Center (NDBC). I. INTRODUCTION

Eleven tidal constituents: O/sub 1/, K/sub 1/, P/sub 1/, Q/sub 1/, M/sub 2/, S/sub 2/, N/sub 2/, K/sub 2/, M/sub 4/, MS/sub 4/ and M/sub 6/ are extracted from 10-year TOPEX/Poseidon altimetry data along track points in the East China Sea. Then the eight major tidal constituents (O/sub 1/, K/sub 1/, P/sub 1/, Q/sub 1/, M/sub 2/, S/sub 2/, N/sub 2/ and K/sub 2/) are assimilated into a two-dimension non-linear tidal model with the adjoint method. In this paper, two different experiments are applied for different kinds of assimilating data and the results show that, assimilating the altimetry data and the in situ data simultaneously is better than assimilating the altimetry data alone. And the bias between calculations and observations are provided. The deviations of M/sub 2/ are 3.5 cm in amplitude and 2.9 deg in phase-lag. Those of O/sub 1/ are 1.3 cm and 5.8 deg accordingly. The co-tidal charts of the eight constituents are also drawn. The general patterns are in good agreement with those literatures cited.

Ocean wind speed and wind direction are estimated simultaneously using the normalized radar cross sections /spl sigma//sup 0/ corresponding to two neighboring (25-km) blocks, within a given synthetic aperture radar (SAR) image, having slightly different incidence angles. This method is motivated by the methodology used for scatterometer data. The wind direction ambiguity is removed by using the direction closest to that given by a buoy or some other source of information. We demonstrate this method with 11 ENVISAT Advanced SAR sensor images of the Gulf of Mexico and coastal waters of the North Atlantic. Estimated wind vectors are compared with wind measurements from buoys and scatterometer data. We show that this method can surpass other methods in some cases, even those with insufficient visible wind-induced streaks in the SAR images, to extract wind vectors.

The scattering fields of 2D sea fractal surface with finite conductivity illuminated by ellipse polarization wave in Cartesian coordinate system have been evaluated in part one. We derive here the relation expression between scattering fields and d illumination fields with 3/spl times/3 matrix in local coordinate system. The radar cross section (RCS) on different polarization is obtained and numerically simulated. It shows that the results of our scattering model are in agreement with those of other literatures for some special case. We get some conclusions: (1) valued of radar cross sections of cross polarization (VH and HV) are less than those of co-polarization (VV and HH) but cannot be neglected; (2) when the incidence angle /spl theta//sub 1/, and the scattering angle /spl theta//sub 2/ are determined, the angle of the scattering plane out of the illuminating plane /spl theta//sub 3/ varies from 0/spl deg/ to 180/spl deg/, different relations among /spl theta//sub 1/, /spl theta//sub 2/ and /spl theta//sub 3/ in different relationships between /spl sigma//sub vs,vt//sup 0/, /spl sigma//sub h/spl delta//,h/sub i//sup 0/ and /spl sigma//sub v/spl delta//,h/sub i//sup 0/, /spl sigma//sub h/spl delta//,v/sub i//sup 0/ are derived, we can use these inequalities to predict the critical angle /spl theta//sub 3/ where the relation between RCS of VV and HH,VH and HV polarization will exchange, respectively; (3) the effects of depolarization can be neglected though we derived the expressions for them.

Recently, many analytical expressions of scattering fields of sea fractal surface with infinite conductivity were derived. In order to simulate multi-polarization SAR imaging of sea surface and consider the effects of polarization on remote sensing of sea surface, we derive the scattering fields from 2D sea fractal surface with finite conductivity illuminated by ellipse polarization wave at Kirchhoff approximation. Then we present the scattering matrix of this model and numerically simulate the bistatic radar cross section (RCS) of 2D sea fractal surface. It shows that the result of applying our model coincides with that of relevant literatures. Our work is divided into two parts. In the first part, we derive the scattering fields in Cartesian coordinates. And in the second part, we evaluate the scattering matrix of this model and then give the numerical results and discuss them.

Wind speed and direction are estimated from backscatter /spl sigma//sup 0/ measurements at two adjacent subscenes of RADARSAT-1 synthetic aperture radar (SAR) images, each subscene with slightly different incidence angles. Resultant wind vectors are validated using in situ buoy measurements, and compared with SAR-derived wind vectors obtained by using the wind directions determined from a spectral analysis of SAR images and colocated QuikSCAT measurements, as inputs to a hybrid model wind retrieval model. The implemented hybrid model consists CMOD-IFR2 (applicable to C-band, VV polarization) and the C-band copolarization ratio for Kirchhoff scattering. The new algorithm displays improved skill in wind vector estimation from RADARSAT-1 SAR data.

Conventional horizontal or vertical polarization synthetic aperture radar (SAR) images seldom perform well in detecting azimuthally traveling ocean waves. However, theoretical analyses suggest that linear-polarimetric backscatter measurements may be more sensitive to these waves and, therefore, that a SAR with linear polarization is expected to give a better measurement of azimuthally traveling ocean waves. We derive the polarization-orientation modulation transform function and tilt modulation transform function of the linear-polarimetric SAR. Through numerical simulations based on these formulations, we examine the effects of radar and ocean wave parameters on linear-polarimetric SAR image spectra. We suggest a method to eliminate the 180/spl deg/ directional ambiguity in determining the true wave direction. Our numerical simulations show that the correlation between ocean wave spectra and SAR image spectra is improved for larger radar incidence angles and longer ocean waves. For real aperture radar, we suggest that the polarimetric modulation allows measurement of waves traveling in the azimuth direction. Moreover, as suggested by Schuler et al., this may be the dominant modulation for many SAR aircraft measurements, particularly for moderate sea states.