Local phenomena, chapter 3, part C

Oceanic and coastal phenomena with dimensions ranging to 100 km are dealt with. The two major categories discussed are waves, their generation and dynamics and ocean-land related problems. The dynamics, of surface waves in both capillary and gravity ranges indicates that microwave technology provides a superior means of measuring simultaneously the spatial and temporal properties of ocean waves. The need for basic studies of physical phenomena in support of active microwave sensing is indicated. Active microwave scattering from surface waves is discussed in terms of wave dynamics

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Theoretical modeling of dual-frequency scatterometer response: improving ocean wind and rainfall effects

Ocean surface wind is a key parameter of the Earth’s climate system. Occurring at the interface between the ocean and the atmosphere, ocean winds modulate fluxes of heat, moisture and gas exchanges. They reflect the lower branch of the atmospheric circulation and represent a major driver of the ocean circulation. Studying the long-term trends and variability of the ocean surface winds is of key importance in our effort to understand the Earth’s climate system and the causes of its changes. More than three decades of surface wind data are available from spaceborne scatterometer/radiometer missions and there is an ongoing effort to inter-calibrate all these measurements with the aim of building a complete and continuous picture of the ocean wind variability. Currently, spaceborne scatterometer wind retrievals are obtained by inversion algorithms of empirical Geophysical Model Functions (GMFs), which represent the relationship between ocean surface backscattering coefficient and the wind parameters. However, by being measurement-dependent, the GMFs are sensor-specific and, in addition, they may be not properly defined in all weather conditions. This may reduce the accuracy of the wind retrievals in presence of rain and it may also lead to inconsistencies amongst winds retrieved by different sensors. Theoretical models of ocean backscatter have the big potential of providing a more general and understandable relation between the measured microwave backscatter and the surface wind field than empirical models. Therefore, the goal of our research is to understand and address the limitations of the theoretical modeling, in order to propose a new strategy towards the definition of a unified theoretical model able to account for the effects of both wind and rain. In this work, it is described our approach to improve the theoretical modeling of the ocean response, starting from the Ku-band (13.4 GHz) frequency and then broadening the analysis at C-band (5.3 GHz) frequency. This research has revealed the need for new understanding of the frequency-dependent modeling of the surface backscatter in response to the wind-forced surface wave spectrum. Moreover, our ocean wave spectrum modification introduced to include the influences of the surface rain, allows the interpretation/investigation of the scatterometer observations in terms not only of the surface winds but also of the surface rain, defining an additional step needed to improve the wind retrievals algorithms as well as the possibility to jointly estimate wind and rain from scatterometer observations

Wave modelling - the state of the art

This paper is the product of the wave modelling community and it tries to make a picture of the present situation in this branch of science, exploring the previous and the most recent results and looking ahead towards the solution of the problems we presently face. Both theory and applications are considered. The many faces of the subject imply separate discussions. This is reflected into the single sections, seven of them, each dealing with a specific topic, the whole providing a broad and solid overview of the present state of the art. After an introduction framing the problem and the approach we followed, we deal in sequence with the following subjects: (Section) 2, generation by wind; 3, nonlinear interactions in deep water; 4, white-capping dissipation; 5, nonlinear interactions in shallow water; 6, dissipation at the sea bottom; 7, wave propagation; 8, numerics. The two final sections, 9 and 10, summarize the present situation from a general point of view and try to look at the future developments

Directional wavenumber characteristics of short sea waves

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2000Interest in short waves on the ocean surface has been growing over the last three decades because they play an important role in surface electromagnetic (e.m.) scattering. Currently radars and scatterometers which use e.m. scattering to remotely examine the ocean can produce estimates of the surface wind field, surface currents, and other scientifically important ocean processes. These estimates are based on models which depend on a thorough understanding of electromagnetic scattering mechanisms, and of the three-dimensional surface wave field. Electromagnetic scattering theory is well developed, but the short wavelength portion of the surface wave field has only recently been experimentally explored. A single, consistent, and accurate model of the energy distribution on the ocean surface, also known as the wave height spectrum, has yet to be developed. A new instrument was developed to measure the height of waves with 2-30 cm wavelengths at an array of locations which can be post-processed to generate an estimate of the two-dimensional wave height spectrum. This instrument (a circular wire wave gage buoy) was deployed in an experiment which gathered not only in situ measurements of the two-dimensional wave height spectrum, but also coincident scatterometer measurements, allowing the comparison of current e.m. scattering and surface wave height spectrum models with at sea data. The experiment was conducted at the Buzzards Bay Tower located at the mouth of Buzzards Bay in Massachusetts. A rotating X-band scatterometer, a sonic anemometer, and a capacitive wire wave gage were mounted on the tower. The wave gage buoy was deployed nearby. The resulting data supports a narrowing trend in the two-dimensional spectral width as a function of wavenumber. Two current spectral models support this to some extent, while other models do not. The data also shows a similar azimuthal width for the scatterometer return and the width of the short wavelength portion of the wave height spectrum after it has been averaged and extrapolated out to the appropriate Bragg wavelength. This appears to support current e.m. composite surface (two-scale) theories which suggest that the scattered return from the ocean at intermediate incidence angles is dominated by Bragg scattering which depends principally on the magnitude and shape of the two-dimensional wave height spectrum. However, the mean wind direction (which corresponds well with the peak of the scatterometer energy distribution) and the peak of 20 minute averages of the azimuthal energy distribution were out of alignment in two out of three data sets, once was by nearly 90°. There are a number of tenable explanations for this including instrument physical limitations and the possibility of significant surface currents, but none that would explain such a significant variation. Given that there are so few measurements of short wave directional spectra, however l these results should be considered preliminary in the field and more extensive measurements are required to fully understand the angular distribution of short wave energy and the parameters upon which it depends.Funding: the MIT Ocean Engineering Department, the WHOI Rienhart Coastal Research Center, the WHOI Education Office, the National Defense Science and Engineering Graduate Fellowship Program, and grant N0001493-1-0726 from the Office of Naval Research

Scattering of Ocean Surfaces in Microwave Remote Sensing by Numerical Solutions of Maxwell Equations

Sea-surface scattering has long been studied using various analytical methods. These analytical methods include the two scale method (TSM), the small-slope approximation (SSA), the small-perturbation method (SPM), the Advanced Integral Equation Method (AIEM), and the Geometrical/Physical Optics (GO/PO) method. These analytical methods rely on making approximations and assumptions in the modelling process. Some of these assumptions undermine their applicability in a wide range of situations. The input for analytical methods are usually the ocean spectrum. In real implementations, there are 2 sources of uncertainty in such approaches: (1) the analytical methods have a limited range of applicability to the surface scattering problem; the approximations made in these methods are questionable and (2) the various ocean spectra are another source of uncertainty. We earlier applied a numerical method in 3-dimensions (NMM3D) to the scattering problem of soil surfaces. Through comparison with measured data, we established the accuracy and applicability of NMM3D. We see a drastic increase of ocean remote sensing applications in recent years. It is thus feasible to extend NMM3D to the sea-surface scattering problem. Compared to soil, sea water has a much higher permittivity, e.g., 75+61i at L-band. The large permittivity dictates the need for using a much denser mesh for the sea surface. In addition, the root mean square (rms) height of the sea surface is large under moderate to high ocean wind speeds, which requires a large simulation area to account for the influence of long scale wave like gravity waves. Compared to the two-scale model commonly used for the ocean scattering problem, NMM3D does not need an ad-hoc split wavenumber in the ocean spectrum. Combined with a fast computational algorithm, it was shown that NMM3D can produce accurate results compared to measured data like the Aquarius missions. TSM could also match well with Aquarius provided with a pre-selected splitting wavenumber. But it was observed that the result of TSM changes with different splitting wavenumbers. It is seen that TSM is fairly heuristic while NMM3D can serve as an exact method for the scattering problem. On the other hand, through our study of NMM3D, we found that with a fine grid, the final impedance matrix converges slowly and also it becomes hard to perform simulations for a large surface. This has provoked us to (1) solve low convergence problem for a dense mesh and (2) resolve difficulties in simulations of large surfaces. Inspired by the existing impedance boundary condition (IBC) method, we proposed a neighborhood impedance boundary condition (NIBC) method to solve the slow convergence problem caused by the dense grid. Different from IBC where the surface electric field and the surface magnetic field are related locally, NIBC relates the surface electric field to the magnetic field within a preselected bandwidth BW. Through numerical simulations, we found that the condition number can be reduced using NIBC. Errors of NIBC are controllable through changing BW. We applied NIBC to various wind speeds and surface types and found NIBC to be quite accurate when surface currents only suffer an error norm of less than 1%.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145797/1/qiaot_1.pd

Effects of nonlinear energy transfer on short surface waves

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95667/1/jgrc11584.pd

Dual-beam interferometry for ocean surface current vector mapping

The recent use of along-track interferometry (ATI) in synthetic aperture radar (SAR) has shown promise for synoptic measurement of ocean surface currents. ATI-SARs have been used to estimate wave fields, currents, and current features. This paper describes and analyzes a dual-beam along-track interferometer to provide spatially resolved vector surface velocity estimates with a single pass of an aircraft. The design employs a pair of interferometer beams, one squinted forward and one squinted aft. Each interferometric phase is sensitive to the component of surface Doppler velocity in the direction of the beam. Therefore, a proper combination of these measurements provides a vector surface velocity estimate in one pass of the aircraft. The authors find that precise measurements dictate widely spaced beams and that the spatial resolution for the squinted SAR is essentially identical to the sidelooking case. Practical instrument design issues are discussed, and an airborne system currently in development is described. Through computer simulation, they observe the azimuthal displacement of interferometric phases by moving surfaces identical to those of conventional SAR and find that such displacement can bias the estimated surface velocity.Peer Reviewe

SEASAT-A scientific contributions

SEASAT-A planned instrument complement and capabilities are reported together with an estimate of expected scientific contributions from satellite oceanic measurements

A nonlinear approach to ocean wave spectrum extraction from bistatic HF-radar data

In this thesis, a new approach to the extraction of the directional ocean wave spectrum from bistatic high frequency (HF) radar data is proposed. The proposed method relies on the simplification of the second-order bistatic radar cross-section, analogous to the one presented by Shahidi and Gill [1] for the monostatic case, to facilitate the use of nonlinear optimization methods, such as regularized nonlinear least-squares. Initially, the historic development of the techniques related to the extraction of the ocean wave spectrum from HF radar data is provided in order to contextualize the work of this thesis. Then, an overview of the theory related to ocean waves and the bistatic radar cross-section is shown. Later, the nonlinear optimization method used in this thesis, Tikhonov regularization in Hilbert spaces, is explained, as well as the theoretical background necessary to understand the method. Once the theory is laid out, the simplification of the second-order bistatic HF radar cross section is presented. The simplification consists of a change of variables that allow the use of the “sifting” property of the Dirac delta function. This reduces the dependence of the second-order bistatic cross-section to a single variable. After the simplification process is shown, the methodology for extracting the directional ocean wave spectrum from bistatic HF radar data is discussed. As a proof-of-concept, the method is initially applied to the second-order bistatic cross section, without the presence of noise. The method successfully extracted the directional ocean wave spectrum without assuming any function model for the nondirectional ocean wave spectrum, and assuming a cosine-power model for the directional spreading function. Next, the first-order bistatic HF radar cross section is added to the second-order cross section, and the proposed method is applied, still without noise present. The proposed method was also able to extract the directional ocean wave spectrum and very low error is added by the inclusion of the first-order cross section. Finally, different levels of noise are added to the cross section including the first and second- orders, and the presented method is applied for the extraction. Again, the method yields good results, with acceptable levels of error for the different noise levels. This new approach to the extraction of the directional ocean wave spectrum from bistatic HF radar data presents, to the author’s knowledge, the first nonlinear extraction method for bistatic HF radar data. Further developments of the technique, such as the use of different nonlinear extraction methods, or a general directional spreading function, are suggested