Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: "(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers." Aslib Book Guide Vol 63, No. 9, 1998 "(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching." EOS Transactions, D.A. Jay, 1999 "(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations." Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 "(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries." E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999

This book is intended as a handbook for professionals and researchers in the areas of Physical Oceanography, Ocean and Coastal Engineering and as a text for graduate students in these fields. It presents a comprehensive study on surface ocean waves induced by wind, including basic mathematical principles, physical description of the observed phenomena, practical forecasting techniques of various wave parameters and applications in ocean and coastal engineering, all from the probabilistic and spectral points of view. The book commences with a description of mechanisms of surface wave generation by wind and its modern modeling techniques. The stochastic and probabilistic terminology is introduced and the basic statistical and spectral properties of ocean waves are developed and discussed in detail. The bulk of material deals with the prediction techniques for waves in deep and coastal waters for simple and complex ocean basins and complex bathymetry. The various prediction methods, currently used in oceanography and ocean engineering, are described and the examples of practical calculations illustrate the basic text. An appendix provides a description of the modern methods of wave measurement, including the remote sensing techniques. Also the wave simulation methods and random data analysis techniques are discussed. In the book a lot of discoveries of the Russian and East European scientists, largely unknown in the Western literature due to the language barrier, are referred to.

Describes the stochastic method for ocean wave analysis - vital information for design and operation of ships.

Early in 1979, a group of wave researchers proposed a wave model inter comparison study to clarify the interrelations existing among the various wave models which have been developed in past years for real-time wave forecasting, wave statistics compilations, or hindcast case studies. The idea was immediately welcomed by the wave modeling community, and, finally, nine wave modeling groups from the United States, Japan, and Europe participated in the exercise. The principal results of this work are presented here jointly by the Sea Wave Modeling Project (swAMP) Group (the members of which are listed in Appendix A). Descriptions of the models used in the study are given in Part II of this volume. A more complete documentation of the entire set of numerical experiments is given in Part 2 of the Sea Wave Modeling Project (SWAMP group, 1982). The main purpose of the intercomparison study was to test our present understanding of the physics of . wind-generated surface waves from the viewpoint of wave modeling. Specifically, we wished to clarify the basic interdependence between understanding the physics of surface waves, repre senting the physics numerically, and predicting quantitatively the detailed space-time evolution of a two-dimensional surface wave spectrum for a given wind field. It was not our intent to carry out a model competition. In this sense there were no winners or losers: all models could claim specific strong points, and all displayed weaknesses in some areas.

The goals of wind wave research are relatively well defined: to be able to predict the wind wave field and its effect on the environment. That environment could be natural (beaches, the atmosphere etc.) or imposed by human endeavour (ports, harbours, coastal settlements etc.). Although the goals are similar, the specific requirements of these various fields differ considerably.This book attempts to summarise the current state of this knowledge and to place this understanding into a common frame work. It attempts to take a balanced approach between the pragmatic engineering view of requiring a short term result and the scientific quest for detailed understanding. Thus, it attempts to provide a rigorous description of the physical processes involved as well as practical predictive tools.

Classical Extreme Value Theory-the asymptotic distributional theory for maxima of independent, identically distributed random variables-may be regarded as roughly half a century old, even though its roots reach further back into mathematical antiquity. During this period of time it has found significant application-exemplified best perhaps by the book Statistics of Extremes by E. J. Gumbel-as well as a rather complete theoretical development. More recently, beginning with the work of G. S. Watson, S. M. Berman, R. M. Loynes, and H. Cramer, there has been a developing interest in the extension of the theory to include, first, dependent sequences and then continuous parameter stationary processes. The early activity proceeded in two directions-the extension of general theory to certain dependent sequences (e.g., Watson and Loynes), and the beginning of a detailed theory for stationary sequences (Berman) and continuous parameter processes (Cramer) in the normal case. In recent years both lines of development have been actively pursued.