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22 pages, 9756 KiB

Open AccessArticle

Analysis of Ku- and Ka-Band Sea Surface Backscattering Characteristics at Low-Incidence Angles Based on the GPM Dual-Frequency Precipitation Radar Measurements

by Qiushuang Yan, Jie Zhang, Chenqing Fan and Junmin Meng

Remote Sens. 2019, 11(7), 754; https://doi.org/10.3390/rs11070754 - 28 Mar 2019

Cited by 13 | Viewed by 3305

Abstract

The co-located normalized radar backscatter cross section measurements from the Global Precipitation Measurement (GPM) Ku/Ka-band dual-frequency precipitation radar (DPR) and sea surface wind; wave and temperature observations from the National Data Buoy Center (NDBC) moored buoys are used to analyze the dependence and [...] Read more.

The co-located normalized radar backscatter cross section measurements from the Global Precipitation Measurement (GPM) Ku/Ka-band dual-frequency precipitation radar (DPR) and sea surface wind; wave and temperature observations from the National Data Buoy Center (NDBC) moored buoys are used to analyze the dependence and sensitivity of Ku- and Ka-band backscatter on surface conditions at low-incidence angles. Then the potential for inverting wind and wave parameters directly from low-incidence σ⁰ measurements is discussed. The results show that the KaPR σ⁰ is more sensitive to surface conditions than the KuPR σ⁰ overall. Nevertheless; both the KuPR σ⁰ and KaPR σ⁰ are strongly correlated with wind speed (U₁₀) and average wave steepness (δ_a) with the exception of specific transitional incidence angles. Moreover, U₁₀ and δ_a could be retrieved from pointwise σ⁰ near nadir and near 18°. Near 18°; wind direction information is needed as the effect of wind direction on σ⁰ becomes increasingly significant with incidence angle. To improve the performance of U₁₀ retrieval; especially for low U₁₀; auxiliary δ_a information would be most helpful; and sea surface temperature is better taken into account. Other wave parameters; such as significant wave height; wave period and wave age; are partly correlated with σ⁰. It is generally more difficult to retrieve those parameters directly from pointwise σ⁰. For the retrieval of those wave parameters; various auxiliary information is needed. Wind direction and wave direction cannot be retrieved from pointwise σ⁰. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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18 pages, 3791 KiB

Open AccessArticle

Efficient Numerical Full-Polarized Facet-Based Model for EM Scattering from Rough Sea Surface within a Wide Frequency Range

by Jinxing Li, Min Zhang, Ye Zhao and Wangqiang Jiang

Remote Sens. 2019, 11(1), 75; https://doi.org/10.3390/rs11010075 - 03 Jan 2019

Cited by 7 | Viewed by 3258

Abstract

A full-polarized facet based scattering model (FPFSM) for investigating the electromagnetic (EM) scattering by two-dimensional electrically large sea surfaces with high efficiency at high microwave bands is proposed. For this method, the scattering field over a large sea facet in a diffuse scattering [...] Read more.

A full-polarized facet based scattering model (FPFSM) for investigating the electromagnetic (EM) scattering by two-dimensional electrically large sea surfaces with high efficiency at high microwave bands is proposed. For this method, the scattering field over a large sea facet in a diffuse scattering region is numerically deduced according to the Bragg scattering mechanism. In regard to near specular directions, a novel approach is proposed to calculate the scattered field from a sea surface based on the second order small slope approximation (SSA-II), which saves computer memory considerably and is able to analyze the EM scattering by electrically large sea surfaces. The feasibility of this method in evaluating the radar returns from the sea surface is proved by comparing the normalized radar cross sections (NRCS) and the Doppler spectrum with the SSA-II. Then NRCS results in monostatic and bistatic configurations under different polarization states, scattering angles and wind speeds are analyzed as well as the Doppler spectrum at Ka-band. Numerical results show that the FPFSM is a reliable and efficient method to analyze the full-polarized scattering characteristics from electrically large sea surface within a wide frequency range. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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16 pages, 2529 KiB

Open AccessArticle

Improving the GNSS-R Specular Reflection Point Positioning Accuracy Using the Gravity Field Normal Projection Reflection Reference Surface Combination Correction Method

by Fan Wu, Wei Zheng, Zhaowei Li and Zongqiang Liu

Remote Sens. 2019, 11(1), 33; https://doi.org/10.3390/rs11010033 - 26 Dec 2018

Cited by 15 | Viewed by 4203

Abstract

Global Navigation Satellite System Reflectometry (GNSS-R) is of great significance for the extraction and research of precise information of sea surface topography. Improving measurement accuracy is necessary for realizing spaceborne GNSS-R sea surface altimetry application. The main error source of GNSS-R distance measurement [...] Read more.

Global Navigation Satellite System Reflectometry (GNSS-R) is of great significance for the extraction and research of precise information of sea surface topography. Improving measurement accuracy is necessary for realizing spaceborne GNSS-R sea surface altimetry application. The main error source of GNSS-R distance measurement is the error of the specular reflection point positioning, which directly affects the sea surface altimetry accuracy on the reference datum. There is an elevation error of several tens of meters between the reflection reference surface used by the existing specular reflection point geometric positioning methods and the sea surface elevation, which is importantly influenced by the earth’s gravity field. Therefore, the gravity field reflection reference surface correction is the key to improving the specular reflection point positioning accuracy. In this study, based on the correction of the GNSS-R reflection reference surface, research on improving the positioning accuracy of the specular reflection point is carried out. Firstly, in order to reduce the positioning error caused by the elevation difference between the reflection reference surface and the sea surface, the gravity field reflection reference surface correction method (GFRRSCM) which corrects the reflection reference surface from the WGS-84 ellipsoid to geoid is proposed, and the positioning accuracy is improved by 25.15 m. Secondly, the normal projection reflection reference surface correction method (NPRRSCM) is proposed to correct the specular reflection point determined by the GFRRSCM from the reflection reference plane of the radial to that of the normal. Additionally, in the process of solving the spatial geometric relationship of the reflection path, the approximate substitution error is reduced by directly solving the normal projection on the plane, and the positioning accuracy is further improved by 13.05 m towards the normal. Thirdly, based on the gravity field normal projection reflection reference surface combination correction method (GF-NPRRSCCM), the specular reflection point positioning accuracy is synthetically improved by 28.66 m. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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19 pages, 5236 KiB

Open AccessFeature PaperArticle

Investigation of EM Backscattering from Slick-Free and Slick-Covered Sea Surfaces Using the SSA-2 and SAR Images

by Honglei Zheng, Yanmin Zhang, Ali Khenchaf, Yunhua Wang, Helmi Ghanmi and Chaofang Zhao

Remote Sens. 2018, 10(12), 1931; https://doi.org/10.3390/rs10121931 - 01 Dec 2018

Cited by 4 | Viewed by 2694

Abstract

This paper is devoted to investigating the electromagnetic (EM) backscattering from slick-free and slick-covered sea surfaces at various bands (L-band, C-band, X-band, and Ku-band) by using the second-order small slope approximation (SSA-2) and the measured synthetic aperture radar (SAR) data. It is known [...] Read more.

This paper is devoted to investigating the electromagnetic (EM) backscattering from slick-free and slick-covered sea surfaces at various bands (L-band, C-band, X-band, and Ku-band) by using the second-order small slope approximation (SSA-2) and the measured synthetic aperture radar (SAR) data. It is known that the impact of slick on sea surface is mainly caused by two factors: the Marangoni damping effect and the reduction of friction velocity. In this work, the influences induced by these two factors on the sea curvature spectrum, the root mean square (RMS) height, the RMS slope, and the autocorrelation function of sea surfaces are studied in detail. Then, the slick-free and slick-covered sea surface profiles are simulated using the Elfouhaily spectrum and the Monte-Carlo model. The SSA-2 with the tapered incident wave is employed to simulate the normalized radar cross-sections (NRCSs) of sea surfaces. Furthermore, for slick-free sea surfaces, the NRCSs simulated with the SSA-2 at various bands are compared with those obtained by the first-order small slope approximation (SSA-1), the classic two-scale model (TSM), and the geophysical model functions (GMFs) at various bands, respectively. For slick-covered sea surfaces, the SSA-2-simulated NRCSs are compared with those obtained from C-band Radarsat-2 images and L-band uninhabited aerial vehicle synthetic aperture radar (UAVSAR) images, respectively. The numerical simulations illustrate that the SSA-2 can be used to study the EM backscattering from slick-free and slick-covered sea surfaces, and it has more advantages than the SSA-1 and the TSM. The works presented in this paper are helpful for understanding the EM scattering from the sea surface covered with slick, in theory. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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22 pages, 9803 KiB

Open AccessArticle

Absolute Calibration of the European Sentinel-3A Surface Topography Mission over the Permanent Facility for Altimetry Calibration in west Crete, Greece

by Stelios Mertikas, Craig Donlon, Pierre Féménias, Constantin Mavrocordatos, Demitris Galanakis, Achilles Tripolitsiotis, Xenophon Frantzis, Costas Kokolakis, Ilias N. Tziavos, George Vergos and Thierry Guinle

Remote Sens. 2018, 10(11), 1808; https://doi.org/10.3390/rs10111808 - 15 Nov 2018

Cited by 12 | Viewed by 4544

Abstract

This work presents calibration results for the altimeter of Sentinel-3A Surface Topography Mission as determined at the Permanent Facility for Altimetry Calibration in west Crete, Greece. The facility has been providing calibration services for more than 15 years for all past (i.e., Envisat, [...] Read more.

This work presents calibration results for the altimeter of Sentinel-3A Surface Topography Mission as determined at the Permanent Facility for Altimetry Calibration in west Crete, Greece. The facility has been providing calibration services for more than 15 years for all past (i.e., Envisat, Jason-1, Jason-2, SARAL/AltiKa, HY-2A) and current (i.e., Sentinel-3A, Sentinel-3B, Jason-3) satellite altimeters. The groundtrack of the Pass No.14 of Sentinel-3A ascends west of the Gavdos island and continues north to the transponder site on the mountains of west Crete. This pass has been calibrated using three independent techniques activated at various sites in the region: (1) the transponder approach for its range bias, (2) the sea-surface method for the estimation of altimeter bias for its sea-surface heights, and (c) the cross-over analysis for inspecting height observations with respect to Jason-3. The other Pass No.335 of Sentinel-3A descends from southwest of Crete to south and intersects the Gavdos calibration site. Additionally, calibration values for this descending pass are presented, applying sea-surface calibration and crossover analysis. An uncertainty analysis for the altimeter biases derived by the transponder and by sea-surface calibrations is also introduced following the new standard of Fiducial Reference Measurements. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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40 pages, 17135 KiB

Open AccessArticle

Fifteen Years of Cal/Val Service to Reference Altimetry Missions: Calibration of Satellite Altimetry at the Permanent Facilities in Gavdos and Crete, Greece

by Stelios P. Mertikas, Craig Donlon, Pierre Féménias, Constantin Mavrocordatos, Demitris Galanakis, Achilles Tripolitsiotis, Xenophon Frantzis, Ilias N. Tziavos, George Vergos and Thierry Guinle

Remote Sens. 2018, 10(10), 1557; https://doi.org/10.3390/rs10101557 - 27 Sep 2018

Cited by 26 | Viewed by 5124

Abstract

Satellite altimetry provides exceptional means for absolute and undisputable monitoring of changes in sea level and inland waters (rivers and lakes), over regional to global scales, with accuracy and with respect to the center of mass of the Earth. Altimetry system’s responses have [...] Read more.

Satellite altimetry provides exceptional means for absolute and undisputable monitoring of changes in sea level and inland waters (rivers and lakes), over regional to global scales, with accuracy and with respect to the center of mass of the Earth. Altimetry system’s responses have to be continuously monitored for their quality, biases, errors, drifts, etc. with calibration. Absolute calibration of altimeters is achieved by external and independent to satellite facilities on the ground. This is the mainstay for a continuous, homogenous, and reliable monitoring of the earth and its oceans. This paper describes the development of the Permanent Facility for Altimetry Calibration in Gavdos/Crete, Greece, as of 2001 along with its infrastructure and instrumentation. Calibration results are presented for the reference missions of Jason-1, Jason-2, and Jason-3. Then, this work continues with the determination of relative calibrations with respect to reference missions for Sentinel-3A, HY-2A, and SARAL/AltiKa. Calibration results are also given for Jason-2 and Jason-3 altimeters using the transponder at the CDN1 Cal/Val site on the mountains of Crete, with simultaneous comparisons against sea-surface calibration and during their tandem mission. Finally, the paper presents procedures for estimating uncertainties for altimeter calibration to meet the Fiducial Reference Measurement standards. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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20 pages, 8022 KiB

Open AccessArticle

Sea Surface Monostatic and Bistatic EM Scattering Using SSA-1 and UAVSAR Data: Numerical Evaluation and Comparison Using Different Sea Spectra

by Honglei Zheng, Ali Khenchaf, Yunhua Wang, Helmi Ghanmi, Yanmin Zhang and Chaofang Zhao

Remote Sens. 2018, 10(7), 1084; https://doi.org/10.3390/rs10071084 - 07 Jul 2018

Cited by 18 | Viewed by 3549

Abstract

The microwave scatterometer is one of the most effective instruments in ocean remote sensing, which urges the need for some theoretical models to accurately estimate the scattering coefficient of the sea surface. For the simulation of the scattering from an ocean surface, the [...] Read more.

The microwave scatterometer is one of the most effective instruments in ocean remote sensing, which urges the need for some theoretical models to accurately estimate the scattering coefficient of the sea surface. For the simulation of the scattering from an ocean surface, the sea spectrum, or its inverse Fourier transform, autocorrelation function is essential. Currently, many sea spectral models have been proposed for describing sea waves. However, which spectrum should be adopted during electromagnetic (EM) computations? A systematic comparison of these models is needed to evaluate their accuracies. In this paper, we focus on numerical simulations of scattering from a rough sea surface in monostatic and bistatic configurations by using six different sea spectral models and the first-order small slope approximation (SSA-1). First, sea spectral models proposed by Elfouhaily et al., Hwang et al., Romeiser et al., Apel et al., Fung et al., and Pierson et al., are compared with each other from different points of view, e.g., the omnidirectional parts, the angular spreading functions, the autocorrelation functions, and the slope variances. We find that the spectra given by Elfouhaily and Hwang could reflect realistic wind sea waves more accurately. Then, the scattering coefficients are simulated in fully monostatic and bistatic configurations. Regarding the monostatic scattering, the results simulated using EM scattering models are compared with those obtained from the measured UAVSAR data in the L band and the empirical model CMOD5 in the C band. Comparisons are made for various incident angles, wind speeds, and wind directions. Meanwhile, special attention is paid to low to moderate incident angles. The comparisons show that, it is difficult to find one certain spectral model to simulate scattering coefficient accurately under all wind speeds or wind directions. Accurate estimations will be obtained using different methods according to different situations. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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19 pages, 5547 KiB

Open AccessArticle

Validation of Improved Significant Wave Heights from the Brown-Peaky (BP) Retracker along the East Coast of Australia

by Fukai Peng and Xiaoli Deng

Remote Sens. 2018, 10(7), 1072; https://doi.org/10.3390/rs10071072 - 05 Jul 2018

Cited by 13 | Viewed by 3074

Abstract

Improved significant wave heights (SWHs) along the east coast of Australia have been estimated using the parameters resolved by a Brown-peaky (BP) retracker through reprocessing of three years of Jason-1 altimetric waveforms. The BP-estimated SWHs are validated against eight waverider buoys along the [...] Read more.

Improved significant wave heights (SWHs) along the east coast of Australia have been estimated using the parameters resolved by a Brown-peaky (BP) retracker through reprocessing of three years of Jason-1 altimetric waveforms. The BP-estimated SWHs are validated against eight waverider buoys along the coast, and compared with the SWHs estimated by the standard four-parameter maximum likelihood estimator (MLE4). When assessing 1 Hz coastal SWHs for distances from 12 km to the coast, mean standard deviations (STDs) of BP SWHs vary from ca. 0.5 m to 0.9 m, while those of MLE4 SWHs increase from ca. 0.6 m to ca. 2.3 m, indicating a dramatically drop in the quality of MLE4-derived SWHs at the coast. The BP retracker has retrieved ca. 80% of 1 Hz coastal SWHs, which are more than those (ca. 50%) by the standard MLE4. The validation of 1 Hz SWHs is performed by calculating the along-altimeter-track pointwise bias, STD and correlation coefficient between altimetry and buoys. The results show that within 30 km off the coast the BP dataset has better agreement with buoy’s wave heights than the SGDR MLE4 dataset in terms of the BP’s small absolute biases and STDs, as well as high correlation coefficients. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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17 pages, 2046 KiB

Open AccessArticle

Modified Multi-Mode Target Tracker for High-Frequency Surface Wave Radar

by Mengxiao Zhao, Xin Zhang and Qiang Yang

Remote Sens. 2018, 10(7), 1061; https://doi.org/10.3390/rs10071061 - 04 Jul 2018

Cited by 9 | Viewed by 2888

Abstract

In high-frequency surface wave radar (HFSWR), part of the radiation signal inevitably propagates upward and illuminates the target through the ionosphere due to the poor controllability of the antenna’s vertical pattern. As a result, a target may have several echoes from different propagation [...] Read more.

In high-frequency surface wave radar (HFSWR), part of the radiation signal inevitably propagates upward and illuminates the target through the ionosphere due to the poor controllability of the antenna’s vertical pattern. As a result, a target may have several echoes from different propagation modes, which affect target detection and tracking and is usually unmanageable in existing HFSWR systems. Without the information of the elevation angle, it is difficult to distinguish the propagation mode of measurements during the target detection phase. This paper makes the first attempt to propose a multi-mode target tracker for HFSWR to solve this problem during the target tracking phase. The multipath probability data association (MPDA) tracker is capable of exploiting multipath target signatures of discrete propagation modes and has been widely used. Based on this, we construct a modified multi-mode probability data association tracker for HFSWR to suppress false tracks caused by multiple propagation modes. Numerical simulations demonstrate that this novel tracker can effectively and accurately track the target from the measurements under multiple propagation modes in HFSWR. The processing results of the actual data collected in Weihai, China indicate that this tracker is of great significance for practical applications. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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25 pages, 5922 KiB

Open AccessArticle

Short-Term Forecasting of Coastal Surface Currents Using High Frequency Radar Data and Artificial Neural Networks

by Lei Ren, Zhan Hu and Michael Hartnett

Remote Sens. 2018, 10(6), 850; https://doi.org/10.3390/rs10060850 - 31 May 2018

Cited by 15 | Viewed by 3659

Abstract

Accurate and timely information of surface currents is crucial for various operations such as search and rescue, marine renewable energy extraction and oil spill treatment. Conventional approaches to study coastal surface currents are numerical models and observation platforms such as radars and satellites. [...] Read more.

Accurate and timely information of surface currents is crucial for various operations such as search and rescue, marine renewable energy extraction and oil spill treatment. Conventional approaches to study coastal surface currents are numerical models and observation platforms such as radars and satellites. However, both have limits. To efficiently obtain high accuracy short-term forecasting states of oceanic parameters of interest, a robust soft computing approach—Artificial Neural Networks (ANN)—was applied to predict surface currents in a tide- and wind-dominated coastal area. Hourly observed surface currents from a Coastal Ocean Dynamic Application Radar (CODAR) system, and tide and wind data from forecasting models were used to establish ANN models for Galway Bay area. One of the fastest algorithms, resilient back propagation, was used to adapt all weights and biases. This study focused on investigating the sensitivity of an ANN model to a series of different input datasets. Results indicate that correlation between ANN forecasts and observation was greater than 0.9 for both surface velocity components with one-hour lead time. Strong correlation (

\geq

0.75) was obtained between predicted results and radar data for both surface velocity components with three-hour lead time at best. However, forecasting accuracy deteriorated rapidly with longer lead time. By comparison with previous data assimilation models, in this research, best performance was achieved from ANN model’s peak times of the tidally dominant surface velocity component. The forecasts presented in this research show clear improvements over previous attempts at short-term forecasting of wind- and tide-dominated currents using ANN. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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18 pages, 975 KiB

Open AccessArticle

Radar Target Recognition Using Salient Keypoint Descriptors and Multitask Sparse Representation

by Ayoub Karine, Abdelmalek Toumi, Ali Khenchaf and Mohammed El Hassouni

Remote Sens. 2018, 10(6), 843; https://doi.org/10.3390/rs10060843 - 28 May 2018

Cited by 25 | Viewed by 4208

Abstract

In this paper, we propose a novel approach to recognize radar targets on inverse synthetic aperture radar (ISAR) and synthetic aperture radar (SAR) images. This approach is based on the multiple salient keypoint descriptors (MSKD) and multitask sparse representation based classification (MSRC). Thus, [...] Read more.

In this paper, we propose a novel approach to recognize radar targets on inverse synthetic aperture radar (ISAR) and synthetic aperture radar (SAR) images. This approach is based on the multiple salient keypoint descriptors (MSKD) and multitask sparse representation based classification (MSRC). Thus, to characterize the targets in the radar images, we combine the scale-invariant feature transform (SIFT) and the saliency map. The purpose of this combination is to reduce the number of SIFT keypoints by keeping only those located in the target area (salient region); this speeds up the recognition process. After that, we compute the feature vectors of the resulting salient SIFT keypoints (MSKD). This methodology is applied for both training and test images. The MSKD of the training images leads to constructing the dictionary of a sparse convex optimization problem. To achieve the recognition, we adopt the MSRC taking into consideration each vector in the MSKD as a task. This classifier solves the sparse representation problem for each task over the dictionary and determines the class of the radar image according to all sparse reconstruction errors (residuals). The effectiveness of the proposed approach method has been demonstrated by a set of extensive empirical results on ISAR and SAR images databases. The results show the ability of the proposed method to predict adequately the aircraft and the ground targets. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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14 pages, 26661 KiB

Open AccessArticle

Evaluation of ISS-RapidScat Wind Vectors Using Buoys and ASCAT Data

by Jungang Yang and Jie Zhang

Remote Sens. 2018, 10(4), 648; https://doi.org/10.3390/rs10040648 - 23 Apr 2018

Cited by 10 | Viewed by 4207

Abstract

The International Space Station scatterometer (named ISS-RapidScat) was launched by NASA on 20 September 2014 as a continuation of the QuikSCAT climate data record to maintain the availability of Ku-band scatterometer data after the QuikSCAT missions ended. In this study, the overall archived [...] Read more.

The International Space Station scatterometer (named ISS-RapidScat) was launched by NASA on 20 September 2014 as a continuation of the QuikSCAT climate data record to maintain the availability of Ku-band scatterometer data after the QuikSCAT missions ended. In this study, the overall archived ISS-RapidScat wind vectors in the wind speed range of 0–24 m/s are evaluated by the global moored buoys’ wind observations, including the U.S. National Data Buoy Center (NDBC), the Tropical Atmosphere Ocean (TAO), and the Pilot Research Moored Array in the Tropical Atlantic (PIRATA), the Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction (RAMA), and Advanced Scatterometer (ASCAT) wind data in the same period of ISS-RapidScat by calculating the statistical parameters, namely, the root mean square error (RMSE), bias (mean of residuals), and correlation coefficient (R) between the collocated data. The comparisons with the global moored buoys show that the RapidScat wind vectors are consistent with buoys’ wind measurements. The average errors of the RapidScat wind vectors are 1.42 m/s and 19.5°. The analysis of the RapidScat wind vector errors at different buoy wind speeds in bins of 1 m/s indicates that the errors of the RapidScat wind speed reduce firstly, and then increase with the increasing buoy wind speed, and the errors of the RapidScat wind direction decrease with increasing buoy wind speed. The comparisons of the errors of the RapidScat wind speed and direction at different months from April 2015 to August 2016 show that the accuracies of the RapidScat wind vectors have no dependence on the time, and the biases of the RapidScat wind speed indicate that there is an annual periodic signal of wind speed errors which are due to the annual cycle variation of ocean winds. The accuracies of the RapidScat wind vectors at different times in one day are also analyzed and the results show that the accuracy of the RapidScat wind vectors at different times of the day is basically consistent and with no diurnal variation. In order to evaluate the ISS-RapidScat wind vectors of the global oceans, the differences (RapidScat-ASCAT) in the wind speed range of 0–30 m/s are analyzed in the different months from October 2014 to August 2016, and the average RMSEs of differences between ISS-RapidScat and ASCAT wind vectors are less than 1.15 m/s and 15.21°. In general, the evaluation of the all-over archived ISS-RapidScat wind vectors show that the accuracies of the ISS-RapidScat wind vectors satisfy the general scatterometer’s mission requirement and are consistent with ASCAT wind data. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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14 pages, 2877 KiB

Open AccessArticle

SAR Mode Altimetry Observations of Internal Solitary Waves in the Tropical Ocean Part 1: Case Studies

by Adriana M. Santos-Ferreira, José C. B. Da Silva and Jorge M. Magalhaes

Remote Sens. 2018, 10(4), 644; https://doi.org/10.3390/rs10040644 - 22 Apr 2018

Cited by 21 | Viewed by 5826

Abstract

It is well known that internal waves (IWs) of tidal frequency (i.e., internal tides) are successfully detected in sea surface height (SSH) by satellite altimetry. Shorter period internal solitary waves (ISWs), whose periods (and spatial scales) are an order of magnitude smaller than [...] Read more.

It is well known that internal waves (IWs) of tidal frequency (i.e., internal tides) are successfully detected in sea surface height (SSH) by satellite altimetry. Shorter period internal solitary waves (ISWs), whose periods (and spatial scales) are an order of magnitude smaller than tidal internal waves, have been generally assumed too small to be detected with conventional altimeters. This is because conventional (pulse-limited) radar altimeter footprints are somewhat larger than or of similar size, at best, as the typical wavelengths of the ISWs. Here we demonstrate that the synthetic aperture radar altimeter (SRAL) on board the Sentinel-3A can detect short-period ISWs. A variety of signatures owing to the surface manifestations of the ISWs are apparent in the SRAL Level-2 products over the ocean. These signatures are identified in several geophysical parameters, such as radar backscatter (sigma0), sea level anomaly (SLA), and significant wave height (SWH). Radar backscatter is the primary parameter in which ISWs can be identified owing to the measurable sea surface roughness perturbations in the along-track sharpened SRAL footprint. The SRAL footprint is sufficiently small to capture radar power fluctuations over successive wave crests and troughs, which produce rough and slick surface patterns arrayed in parallel bands with scales of a few kilometers. The ISW signatures are unambiguously identified in the SRAL because of the exact synergy with OLCI (Ocean Land Colour Imager) images, which in cloud-free conditions allow clear identification of the ISWs in the sunglint OLCI images. We show that both sigma0 and SLA yield realistic estimates for routine observation of ISWs with the SRAL, which is a significant improvement from previous observations recently reported for conventional pulse-limited altimeters (Jason-2). Several case studies of ISW signatures are interpreted in light of our knowledge of radar backscatter in the internal wave field. An analysis is presented for the tropical Atlantic Ocean off the Amazon shelf to infer the frequency of the phenomena, being consistent with previous satellite observations in the study region. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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19 pages, 5249 KiB

Open AccessArticle

An Orthogonal Projection Algorithm to Suppress Interference in High-Frequency Surface Wave Radar

by Zezong Chen, Fei Xie, Chen Zhao and Chao He

Remote Sens. 2018, 10(3), 403; https://doi.org/10.3390/rs10030403 - 06 Mar 2018

Cited by 9 | Viewed by 4778

Abstract

High-frequency surface wave radar (HFSWR) has been widely applied in sea-state monitoring, and its performance is known to suffer from various unwanted interferences and clutters. Radio frequency interference (RFI) from other radiating sources and ionospheric clutter dominate the various types of unwanted signals [...] Read more.

High-frequency surface wave radar (HFSWR) has been widely applied in sea-state monitoring, and its performance is known to suffer from various unwanted interferences and clutters. Radio frequency interference (RFI) from other radiating sources and ionospheric clutter dominate the various types of unwanted signals because the HF band is congested with many users and the ionosphere propagates interference from distant sources. In this paper, various orthogonal projection schemes are summarized, and three new schemes are proposed for interference cancellation. Simulations and field data recorded by experimental multi-frequency HFSWR from Wuhan University are used to evaluate the cancellation performances of these schemes with respect to both RFI and ionospheric clutter. The processing results may provide a guideline for identifying the appropriate orthogonal projection cancellation schemes in various HFSWR applications. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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3352 KiB

Open AccessArticle

Comparative Study on Assimilating Remote Sensing High Frequency Radar Surface Currents at an Atlantic Marine Renewable Energy Test Site

by Lei Ren and Michael Hartnett

Remote Sens. 2017, 9(12), 1331; https://doi.org/10.3390/rs9121331 - 19 Dec 2017

Cited by 2 | Viewed by 4606

Abstract

A variety of data assimilation approaches have been applied to enhance modelling capability and accuracy using observations from different sources. The algorithms have varying degrees of complexity of implementation, and they improve model results with varying degrees of success. Very little work has [...] Read more.

A variety of data assimilation approaches have been applied to enhance modelling capability and accuracy using observations from different sources. The algorithms have varying degrees of complexity of implementation, and they improve model results with varying degrees of success. Very little work has been carried out on comparing the implementation of different data assimilation algorithms using High Frequency radar (HFR) data into models of complex inshore waters strongly influenced by both tides and wind dynamics, such as Galway Bay. This research entailed implementing four different data assimilation algorithms: Direct Insertion (DI), Optimal Interpolation (OI), Nudging and indirect data assimilation via correcting model forcing into a three-dimensional hydrodynamic model and carrying out detailed comparisons of model performances. This work will allow researchers to directly compare four of the most common data assimilation algorithms being used in operational coastal hydrodynamics. The suitability of practical data assimilation algorithms for hindcasting and forecasting in shallow coastal waters subjected to alternate wetting and drying using data collected from radars was assessed. Results indicated that a forecasting system of surface currents based on the three-dimensional model EFDC (Environmental Fluid Dynamics Code) and the HFR data using a Nudging or DI algorithm was considered the most appropriate for Galway Bay. The largest averaged Data Assimilation Skill Score (DASS) over the ≥6 h forecasting period from the best model NDA attained 26% and 31% for east–west and north–south surface velocity components respectively. Because of its ease of implementation and its accuracy, this data assimilation system can provide timely and useful information for various practical coastal hindcast and forecast operations. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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Open AccessArticle

Hindcasting and Forecasting of Surface Flow Fields through Assimilating High Frequency Remotely Sensing Radar Data

by Lei Ren and Michael Hartnett

Remote Sens. 2017, 9(9), 932; https://doi.org/10.3390/rs9090932 - 08 Sep 2017

Cited by 5 | Viewed by 4514

Abstract

In order to improve the forecasting ability of numerical models, a sequential data assimilation scheme, nudging, was applied to blend remotely sensing high-frequency (HF) radar surface currents with results from a three-dimensional numerical, EFDC (Environmental Fluid Dynamics Code) model. For the first time, [...] Read more.

In order to improve the forecasting ability of numerical models, a sequential data assimilation scheme, nudging, was applied to blend remotely sensing high-frequency (HF) radar surface currents with results from a three-dimensional numerical, EFDC (Environmental Fluid Dynamics Code) model. For the first time, this research presents the most appropriate nudging parameters, which were determined from sensitivity experiments. To examine the influence of data assimilation cycle lengths on forecasts and to extend forecasting improvements, the duration of data assimilation cycles was studied through assimilating linearly interpolated temporal radar data. Data assimilation nudging parameters have not been previously analyzed. Assimilation of HF radar measurements at each model computational timestep outperformed those assimilation models using longer data assimilation cycle lengths; root-mean-square error (RMSE) values of both surface velocity components during a 12 h model forecasting period indicated that surface flow fields were significantly improved when implementing nudging assimilation at each model computational timestep. The Data Assimilation Skill Score (DASS) technique was used to quantitatively evaluate forecast improvements. The averaged values of DASS over the data assimilation domain were 26% and 33% for east–west and north–south velocity components, respectively, over the half-day forecasting period. Correlation of Averaged Kinetic Energy (AKE) was improved by more than 10% in the best data assimilation model. Time series of velocity components and surface flow fields were presented to illustrate the improvement resulting from data assimilation application over time. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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Open AccessArticle

Ocean Oil Spill Classification with RADARSAT-2 SAR Based on an Optimized Wavelet Neural Network

by Dongmei Song, Yaxiong Ding, Xiaofeng Li, Biao Zhang and Mingyu Xu

Remote Sens. 2017, 9(8), 799; https://doi.org/10.3390/rs9080799 - 03 Aug 2017

Cited by 51 | Viewed by 7360

Abstract

Oil spill accidents from ship or oil platform cause damage to marine and coastal environment and ecosystems. To monitor such spill events from space, fully polarimetric (Pol-SAR) synthetic aperture radar (SAR) has been greatly used in improving oil spill observation. Aiming to promote [...] Read more.

Oil spill accidents from ship or oil platform cause damage to marine and coastal environment and ecosystems. To monitor such spill events from space, fully polarimetric (Pol-SAR) synthetic aperture radar (SAR) has been greatly used in improving oil spill observation. Aiming to promote ocean oil spill classification accuracy, we developed a new oil spill identification method by combining multiple fully polarimetric SAR features data with an optimized wavelet neural network classifier (WNN). Two sets of RADARSAT-2 fully polarimetric SAR data are applied to test the validity of the developed method. The experimental results show that: (1) the convergence ability of optimized WNN can be enhanced, improving overall classification accuracy of ocean oil spill, in comparison to the classification results based on a common un-optimized WNN classifier; and (2) the joint use of the multiple fully Pol-SAR features as the inputs of the classifier can achieve better classification result than that only with single fully Pol-SAR feature. The developed method can improve classification accuracy by 4.96% and 7.75%, compared with the classification results with un-optimized WNN and only with one single fully polarimetric SAR feature. The classification overall accuracy based on the proposed approach can reach 97.67%. Experimental results have proven that the proposed approach is effective and applicable to classify the ocean oil spill. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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12 pages, 7104 KiB

Open AccessLetter

Tidal Mixing Signatures in the Hong Kong Coastal Waters from Satellite-Derived Sea Surface Temperature

by R. Dwi Susanto, Jiayi Pan and Adam T. Devlin

Remote Sens. 2019, 11(1), 5; https://doi.org/10.3390/rs11010005 - 20 Dec 2018

Cited by 8 | Viewed by 4519

Abstract

Tidal mixing in the coastal waters of Hong Kong was investigated using a combination of in situ observations and high-resolution satellite-derived sea surface temperature (SST) data. An indicator of tide-induced mixing is a fortnightly (spring-neap cycle) signature in SST due to nonlinear interactions [...] Read more.

Tidal mixing in the coastal waters of Hong Kong was investigated using a combination of in situ observations and high-resolution satellite-derived sea surface temperature (SST) data. An indicator of tide-induced mixing is a fortnightly (spring-neap cycle) signature in SST due to nonlinear interactions between the two principal diurnal and the two principal semi-diurnal tides. Both semi-diurnal and diurnal tides have strong tidal amplitudes and currents near Hong Kong. As a result, both the near-fortnightly (Mf) and fortnightly (MSf) tides are enhanced due to nonlinear tidal signal interactions. In addition, these fortnightly tidal signals are modulated by seasonal variability, with the maximum seasonal modulation of fortnightly tides occurring during the monsoon transition periods in May and October. The largest fortnightly signals are found in the southwestern part of the Pearl River estuary. Tidal constituent properties vary by space and depth, and high-resolution SST plays a pivotal role in resolving the spatial characteristics of tidal mixing. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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1770 KiB

Open AccessLetter

Extreme Wave Height Events in NW Spain: A Combined Multi-Sensor and Model Approach

by Pablo Lorente, Marcos G. Sotillo, Lotfi Aouf, Arancha Amo-Baladrón, Ernesto Barrera, Alice Dalphinet, Cristina Toledano, Romain Rainaud, Marta De Alfonso, Silvia Piedracoba, Ana Basañez, Jose Maria García-Valdecasas, Vicente Pérez-Muñuzuri and Enrique Álvarez-Fanjul

Remote Sens. 2018, 10(1), 1; https://doi.org/10.3390/rs10010001 - 21 Dec 2017

Cited by 68 | Viewed by 4726

Abstract

The Galician coast (NW Spain) is a region that is strongly influenced by the presence of low pressure systems in the mid-Atlantic Ocean and the periodic passage of storms that give rise to severe sea states. Since its wave climate is one of [...] Read more.

The Galician coast (NW Spain) is a region that is strongly influenced by the presence of low pressure systems in the mid-Atlantic Ocean and the periodic passage of storms that give rise to severe sea states. Since its wave climate is one of the most energetic in Europe, the objectives of this paper were twofold. The first objective was to characterize the most extreme wave height events in Galicia over the wintertime of a two-year period (2015–2016) by using reliable high-frequency radar wave parameters in concert with predictions from a regional wave (WAV) forecasting system running operationally in the Iberia-Biscay-Ireland (IBI) area, denominatedIBI-WAV. The second objective was to showcase the application of satellite wave altimetry (in particular, remote-sensed three-hourly wave height estimations) for the daily skill assessment of the IBI-WAV model product. Special attention was focused on monitoring Ophelia—one of the major hurricanes on record in the easternmost Atlantic—during its 3-day track over Ireland and the UK (15–17 October 2017). Overall, the results reveal the significant accuracy of IBI-WAV forecasts and prove that a combined observational and modeling approach can provide a comprehensive characterization of severe wave conditions in coastal areas and shows the benefits from the complementary nature of both systems. Full article

(This article belongs to the Special Issue Radar Remote Sensing of Oceans and Coastal Areas)

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