Stochastic Modelling in Physical Oceanography
The study of the ocean is almost as old as the history of mankind itself. When the first seafarers set out in their primitive ships they had to understand, as best they could, tides and currents, eddies and vortices, for lack of understanding often led to loss of live. These primitive oceanographers were, of course, primarily statisticians. They collected what empirical data they could, and passed it down, ini­ tially by word of mouth, to their descendants. Data collection continued throughout the millenia, and although data bases became larger, more re­ liable, and better codified, it was not really until surprisingly recently that mankind began to try to understand the physics behind these data, and, shortly afterwards, to attempt to model it. The basic modelling tool of physical oceanography is, today, the partial differential equation. Somehow, we all 'know" that if only we could find the right set of equations, with the right initial and boundary conditions, then we could solve the mysteries of ocean dynamics once and for all.
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Stochastic Modelling in Physical Oceanography
The study of the ocean is almost as old as the history of mankind itself. When the first seafarers set out in their primitive ships they had to understand, as best they could, tides and currents, eddies and vortices, for lack of understanding often led to loss of live. These primitive oceanographers were, of course, primarily statisticians. They collected what empirical data they could, and passed it down, ini­ tially by word of mouth, to their descendants. Data collection continued throughout the millenia, and although data bases became larger, more re­ liable, and better codified, it was not really until surprisingly recently that mankind began to try to understand the physics behind these data, and, shortly afterwards, to attempt to model it. The basic modelling tool of physical oceanography is, today, the partial differential equation. Somehow, we all 'know" that if only we could find the right set of equations, with the right initial and boundary conditions, then we could solve the mysteries of ocean dynamics once and for all.
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Stochastic Modelling in Physical Oceanography

Stochastic Modelling in Physical Oceanography

Stochastic Modelling in Physical Oceanography

Stochastic Modelling in Physical Oceanography

Overview

The study of the ocean is almost as old as the history of mankind itself. When the first seafarers set out in their primitive ships they had to understand, as best they could, tides and currents, eddies and vortices, for lack of understanding often led to loss of live. These primitive oceanographers were, of course, primarily statisticians. They collected what empirical data they could, and passed it down, ini­ tially by word of mouth, to their descendants. Data collection continued throughout the millenia, and although data bases became larger, more re­ liable, and better codified, it was not really until surprisingly recently that mankind began to try to understand the physics behind these data, and, shortly afterwards, to attempt to model it. The basic modelling tool of physical oceanography is, today, the partial differential equation. Somehow, we all 'know" that if only we could find the right set of equations, with the right initial and boundary conditions, then we could solve the mysteries of ocean dynamics once and for all.

Product Details

ISBN-13: 9781461275336
Publisher: Birkhäuser Boston
Publication date: 09/30/2011
Series: Progress in Probability , #39
Edition description: Softcover reprint of the original 1st ed. 1996
Pages: 466
Product dimensions: 6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

Particle Displacements in Inhomogeneous Turbulence.- Massively Parallel Simulations of Motions in a Gaussian Velocity Field.- Comparison Tests for the Spectra of Dependent Multivariate Time Series.- A Statistical Approach to Ocean Model Testing and Tuning.- Applications of Shastic Particle Models to Oceanographic Problems.- Sound through the Internal Wave Field.- Shastic Modeling of Turbulent Flows.- Neptune Effect: Statistical Mechanical Forcing of Ocean Circulation.- Short-Time Correlation Approximations for Diffusing Tracers in Random Velocity Fields: A Functional Approach.- Particles, Vortex Dynamics and Shastic Partial Differential Equations.- Nongaussian Autoregressive Sequences and Random Fields.- Feature and Contour Based Data Analysis and Assimilation in Physical Oceanography.- Topics in Statistical Oceanography.- Shastic Forcing of Quasi-Geostrophic Eddies.- Maximum Likelihood Estimators in the Equations of Physical Oceanography.- Chaotic Transport by Mesoscale Motions.- Chaotic Transport and Mixing by Ocean Gyre Circulation.
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