Internal wave location and parameters estimation from ENVISAT SAR images

Detection of solitary ocean internal waves from SAR images by using U-Net and KDV solver technique

Evidence of short internal waves trailing strong internal solitary waves in the northern South China Sea from synthetic aperture radar observations

It was shown recently that three different types of short‐period internal wave (IW) synthetic aperture radar (SAR) signatures occur on the Iberian Shelf depending on parameters of surface active films. Large‐scale modulation of film characteristics by currents associated with internal tidal waves can also produce a signature in ERS SAR images. On the western Iberian Shelf short‐period IWs typically propagate in groups of packets that are believed to be generated by the evolution of internal tidal waves over the shelf. Here onshore propagating short‐period IWs can exhibit different SAR signatures within the same wave packet according to their position relative to the phase of the internal tidal wave. These transitions of signature mode can be explained by large‐scale variations of film parameters produced by the internal tidal waves. At low‐to‐moderate winds, leading waves in the IW packets usually exhibit double sign signatures, which evolve to negative sign signatures for the subsequent waves in the packets. At very low, near‐threshold winds the IW signatures can be in the form of the double sign type undergoing transition to positive sign signatures when compared to the background behind the IW packet. This is a consequence of different threshold wind speeds for excitation of Bragg waves at different film pressures. An increase of unperturbed film pressure in the direction of the ranking order of solitons in a packet of short‐period IWs, which is predicted by a theoretical model and in agreement with measurements of film elasticity, is demonstrated. Observations of SAR signature mode transitions are concluded to be consistent with previous model results, and a diagram describing mode transitions of the IW signatures in relation to film pressure and wind speed is presented.

Internal solitary waves are a typical marine phenomenon, and the research on feature detection and parameter inversion of internal waves has important implications for marine engineering and military affairs. Internal waves in SAR images appear as distinct alternating bright and dark stripes, so it is possible to detect and invert internal wave parameters using SAR images. In this paper, we use the median-Gaussian filter and Canny operator to detect internal waves in SAR images, and use a numbering and connection algorithm to fill in the broken wave crest lines. The results show that this method effectively solves the problem of internal wave detection and provides convenience for further inversion of internal wave parameters and the construction of artificial intelligence methods for identifying internal waves.

Internal waves have been observed by lots of high resolution satellite images, such as Synthetic Aperture Radar (SAR) and optical images of SPOT and Landsat. These images are usually expensive. In this study, some free but lower spatial resolution satellite images are applied to observe the internal wave phenomena. The internal waves in the Sulu Sea are detected from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard the Orbview-2 satellite. The SeaWiFS image has a spatial resolution of 1.1 km. It is acceptable to observe the internal wave phenomena while the soliton width is larger than the image resolution. The results show that the internal solitary in the Sulu Sea can be observed successfully with SeaWiFS chlorophyll images. The internal waves in the Sulu Sea have amplitudes of 10 to 90 m and wavelengths of 5 to 16 km. The large-amplitude internal solitary waves may significantly influence the near-surface chlorophyll concentration. The chlorophyll concentration would be lower when the depression internal waves passed through. A theoretic model is proposed and tested to estimate the amplitudes of internal waves from chlorophyll concentration images.

Internal waves (IWs) are a common characteristic of oceans and serve a crucial role in transmitting energies between large-scale tides and small-scale mixing. This study developed a deep-learning-based method for extracting IW signatures on multiple satellite imagery from synthetic aperture radar (SAR) and optical sensors in sun-synchronous and geostationary orbits with varying spatial resolution. We collected 1115 satellite images, including 116 ENVISAT ASAR (Advanced SAR), 839 MODIS (MODerate-resolution Imaging Spectroradiometer), and 160 Himawari-8 AHI (Advanced Himawari Imager) images with clear IW signatures in the South China Sea (SCS), Sulu Sea, and Celebes Sea for model training. Considering the distinct IW characteristics under different imaging mechanisms, the specially tailored IW Extraction network (IWE-Net) leverages three modifications to improve the accuracy and robustness: online data augmentation, squeeze and excitation blocks, and Matthews correlation coefficient loss. The overall mean Precision, Recall, and F1-score of the IWE-Net model are 85.75%, 85.67%, and 85.71%, demonstrating the model is accurate for IW signature extraction.We also proved the transferability of our method to sea areas worldwide, long-term periods, and Sentinel satellite sensors completely independent of the model training. Globally, the number of IW images and extracted pixels show an obvious tidal-related double-peak distribution. Furthermore, we processed 15461 MODIS images in the northeastern SCS to present a holistic IW distribution map over the past 22 years. An unreported IW silent zone caused by drastic topography changes has been discovered, indicating the great potential of deep learning in information retrieval from remote sensing imagery.

A weakly nonhydrostatic, two‐layer numerical model based on the Boussinesq equations is presented which is capable of describing, among others, the generation and propagation of nonlinear weakly dispersive internal waves in the Strait of Gibraltar. The model depends on one space coordinate only, but it retains several features of a fully three‐dimensional model by including a realistic bottom profile, a variable channel width, and a trapezoidal channel cross section. The nonlinear primitive Boussinesq equations include horizontal diffusion, bottom friction, and friction between the two water layers. The model is driven by a height difference of the mean interface depth between the Atlantic and the Mediterranean boundaries and by semidiurnal tidal oscillations of the barotropic transport. The model presented in this paper describes (1) the mean and tidal flow in the Strait of Gibraltar, (2) the variation of the depth of the interface during a tidal cycle, (3) the generation of strong depressions of the interface at the western sides of the Spartel Sill and the Camarinal Sill, (4) the generation of strong eastward propagating internal bores, and (5) their disintegration into trains of internal solitary waves. The surface convergence patterns associated with depressions of the interface at the Camarinal Sill, internal bores, and internal solitary waves are calculated and compared with roughness patterns visible on synthetic aperture radar (SAR) images of the first European Remote Sensing Satellite ERS 1. In total, 155 ERS 1 SAR scenes from 94 satellite overflights over the Strait of Gibraltar, which were acquired in the period from January 1992 to March 1995, have been analyzed. It is shown that the proposed model is capable of explaining the observed temporal and spatial evolution of surface roughness patterns associated with eastward propagating internal waves inside the Strait of Gibraltar as well as the observed east‐west asymmetry of the internal wave field.

This paper addresses the problem of the characterization of oceanic internal wave packets from SAR images. Wavelet analysis provides a new strategy for examining internal wave signatures, and offers the flexibility which results from the introduction of well-suited basis functions. The continuous wavelet transform (CWT) is employed in a scale-space analysis of SAR image profiles to locate and characterize the local scaling properties and the wave parameters of internal waves.

The patterns of internal waves are common occurrences in remote sensing images of the ocean. Internal waves are usually induced by undulating terrain on the sea floor or moving sources in the stratified ocean, especially in an offshore sea or straits in which there exists a relatively significant density stratification of the seawater. In this paper, a new method for simulating the synthetic aperture radar (SAR) images of the internal wave wake excited by underwater vehicles is presented. The flow field of the wake is solved directly using the Reynolds averaged Navier–Stokes solver, and the ambient waves on the sea surface are considered as random wind waves. To consider a continuously stratified ocean, a special multiphase flow model is implemented, which can be used to obtain arbitrary stratified structures numerically. To estimate the scattering distribution of the wakes on the sea surface, an improved facet scattering model is proposed, in which the hydrodynamic modulation of the ambient waves by the wake is considered. Based on the results calculated by the scattering model, the velocity-bunching integral is implemented to simulate the intensity of SAR images of a disturbed sea surface having embedded internal wave wakes.

Detection of distributed targets such as internal wave or ship wake on sea surface in Synthetic Aperture Radar (SAR) images is an important application of ocean microwave remote sensing. The chaotic characteristic of sea clutter gives some clues to targets detection on sea surface. Speckle, the inherent noise of SAR image, will affect the predictive accuracy of sea clutter adversely and reduce the detection performance of radar. In order to apply the chaotic characteristic of sea clutter to targets detection in SAR images more effectively, an improved chaos-based detection method is proposed in this paper. First, speckle noise is suppressed by undecimated wavelet transform (UWT), and then targets are detected on the basis of the chaotic characteristic of sea clutter from the denoised SAR images. Experimental results prove that the method proposed in this paper is effective for the distributed targets detection in SAR ocean images.

Shipboard observations during deepwater drilling operations by the Discoverer 534 and a simultaneous oceanographic measurement program have confirmed the presence of large internal waves in the Andaman Sea, offshore Thailand. The Discoverer 534 has provided measurements of dri11ship response to internal wave activity in water depths ranging from 1900 ft to greater than 3400 ft; internal wave currents as high as 2.6 knots have been measured. As a result of the analysis of internal wave and dri11ship data it is concluded that internal waves may have an impact on dri11ship operations, and knowledge of their forces on offshore structures will be required to design production facilities in some deep water areas of the world. INTRODUCTION The purpose of this paper is to bring to the attention of the offshore industry a new environmental loading factor which may influence future deepwater operations: internal waves. Exxon experience has verified that internal waves are present in the Andaman Sea, and a search of the literature indicates that internal waves exist in all the world's oceans (1). The Discoverer 534 under contract to Esso Exploration Inc., operated successfully in the Andaman Sea in water depths ranging from 1900 ft to greater than 3400 ft. While internal waves were present during much of the operating period, they had no significant impact on drillship operations. However, because internal waves of magnitude greater than those observed by the Discoverer 534 are possible, Exxon Production Research Co. initiated a measurement and modeling program to obtain a detailed engineering description of internal waves. The measurement program, conducted during October 1976, was designed to simultaneously measure internal waves and the corresponding dril1ship response. A subsequent internal wave modeling effort is now underway. In the sections which follow we (1) briefly review the properties of internal waves, (2) discuss the measurements of internal waves in the Andaman Sea, and (3) describe typical dril1ship response to moderately sized internal waves. CHARACTERISTICS OF INTERNAL WAVES Background Internal waves are water waves which propagate beneath the ocean's surface. Just as surface waves propagate along the boundary layer formed between the ocean and the atmosphere, internal waves propagate along the boundary layer between water of greater and lesser density. Such boundary layers are associated with the oceanic thermocline and are normally characterized by warm, less saline water lying over cold, more saline water. Internal waves may exist in any body of water which is stratified by temperature and/or mineral content. However, energy sources must be available to generate the waves. For example, current flow over uneven bathymetry, shear current flow, and atmospheric disturbances may cause internal waves to form. Internal waves may have a finite amplitude everywhere in the water column except at the bottom where it is zero. The internal wave amplitude on the ocean's surface is usually very small, preventing easy surface observation of them. The maximum amplitude is normally found near the average depth of the main thermocline.

—The distribution of internal waves in the East China Sea and the Yellow Sea has been studied by screening 170 ERS SAR images and 202 SPOT images for sea surface signatures of internal waves. The occurrence of internal wave signatures is correlated with the phase of the spring-neap tidal cycle and with the time of the year which yields information on the stratification of the water column. Internal waves, East China Sea, Yellow Sea, synthetic aperture radar, ERS, SPOT. I. I NTRODUCTION The East China Sea and the Yellow Sea are sea areas where little information exists on the generation, propagation and distribution of internal waves (IWs), see [1], [2], and [ 3 ]. The first systematic study of the distribution of IWs in these sea areas was carried out by Hsu et al. in 2000 [1], who analysed radar images for IW signatures which were acquired by the synthetic aperture radar (SAR) onboard the satellites ERS-1 and ERS-2 between 1993 and 1997. In the present study we have extended his investigation by including ERS SAR images that were acquired after 1997 and by using images that were acquired in the visible bands from the French SPOT satellites. This has increased the data base considerably and made it possible not only to generate much more detailed maps of the distribution of IWs in the East China Sea and the Yellow Sea, but also to study how the occurrence of IWs depends on the phase of spring-neap tidal cycle and on the time of the year. The occurrence of IWs is an indicator for the stratification of the ocean column, i. e., for the existence of a pycnocline. In winter the water columns in the China Sea and the Yellow Sea are usually well mixed due to the prevailing cold winds from the north and thus no internal wave signatures are observed. II.

The generation of an internal wave packet by the interaction of a large-amplitude internal solitary wave with an underwater bank is studied by using a numerical model and a synthetic aperture radar (SAR) image acquired by the European Remote Sensing satellite ERS-2 over the Andaman Sea. It is shown that, if the internal solitary wave has a sufficiently large amplitude, overturning and wave breaking occurs which gives rise to the generation of a secondary internal wave packet. The results obtained from the model calculations are supported by the ERS-2 SAR observations.

The results of studying a variability of internal-gravity-wave characteristics and their signatures based on satellite data are presented. Observations of the wave processes under study over the Russian Federation Pacific coast in the period from 2015 to 2017 are considered. High-periodic Himawari-8 satellite images and thematic products of their processing are used. The methods and algorithms for retrieving parameters of internal gravity waves and their cloud manifestations are described. Trends for various characteristics of wave processes under study are constructed. The typical variability of parameters of internal gravity waves and their signatures is revealed on the basis of the longest lasting episodes of their observation. The results of analysis of coefficients of correlation between the various characteristics of the wave processes under study are presented. Similar episodes of observing signatures of internal gravity waves for the time period under study are established. The processes occurring in the “atmosphere–underlying surface” system and their influence on the creation of favorable conditions for the generation and propagation of wave processes under study are discussed.

Internal solitary waves (IWs) in the northwest Bay of Bengal were studied using ENVISAT ASAR imageries. Simultaneous in situ observations were also carried out to study the characteristics of the internal waves. Internal wave features have often been observed over the ocean area between 18.5°–19.5° N and 84.5°–85.5° E. The direction of propagation of IWs is generally toward the coast with wavelengths ranging from 0.4 to 1.1 km. The phase speeds of the IWs vary from 0.12 to 1.3 m/s. Internal wave amplitudes computed using Korteweg and de Vries model show good agreement with in situ data. Based on their direction of propagation and time series analysis, IWs generated were found to be of tidal forcing origin over local topographic features. IWs of different types like wave packets or wave trains and single solitons of weak manifestations were observed depending on the phase and the tidal amplitude as well as the stratification of the ocean, which in turn vary due to the dynamic and complex nature of Bay of Bengal, as it experiences strong monsoon winds and low pressure systems with calm weather in between them. The internal waves are often observed during non-monsoon period over this region. During monsoon period, continuous vertical mixing takes place due to strong winds causing unfavorable conditions for IW formation and so the observation of IWs during monsoons is rather rare.