ebooks in fluid mechanics

Ocean Circulation in Three Dimensions

Barry A. Klinger, Thomas W. N. Haine
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11 March 2019

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14 March 2019
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Notable advances of the last quarter-century have deepened our appreciation of the three-dimensional nature of the ocean's large-scale circulation. This circulation has important implications for ocean chemistry and biology, atmospheric science, and climate. Ocean Circulation in Three Dimensions surveys both observations and theories of the time-mean circulation, enabling readers to see the relevance and limitations of leading theories, as well as the patterns linking the behavior of different oceans. The book covers “classical” topics of horizontal circulation, and expands them to include shallow wind-driven overturning, the deep global “conveyer belt”, high latitudes, the role of eddies, and the ocean's role in heat transport. Solutions to exercises are available online for instructor use. This textbook is ideal for students of physical oceanography, chemical oceanography and climate. It is also suitable for readers from related fields as it includes a summary of introductory topics.

4 - Regression and Model Selection
from Part II - Machine Learning and Data Analysis
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
Book:

Data-Driven Science and Engineering

Published online:

15 February 2019

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28 February 2019, pp 117-153
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5 - Clustering and Classification
from Part II - Machine Learning and Data Analysis
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
Book:

Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 154-194
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Part IV - Reduced Order Models
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 373-374
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Frontmatter
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp i-iv
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11 - Reduced Order Models (ROMs)
from Part IV - Reduced Order Models
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
Book:

Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 375-402
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Glossary
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 436-442
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12 - Interpolation for Parametric ROMs
from Part IV - Reduced Order Models
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 403-435
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Part III - Dynamics and Control
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 227-228
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Index
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 471-472
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3 - Sparsity and Compressed Sensing
from Part I - Dimensionality Reduction and Transforms
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 84-114
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7 - Data-Driven Dynamical Systems
from Part III - Dynamics and Control
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
Book:

Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 229-275
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10 - Data-Driven Control
from Part III - Dynamics and Control
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 345-372
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Bibliography
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 443-470
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Preface
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp ix-xii
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9 - Balanced Models for Control
from Part III - Dynamics and Control
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 321-344
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2 - Fourier and Wavelet Transforms
from Part I - Dimensionality Reduction and Transforms
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 47-83
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6 - Neural Networks and Deep Learning
from Part II - Machine Learning and Data Analysis
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 195-226
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Part II - Machine Learning and Data Analysis
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 115-116
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8 - Linear Control Theory
from Part III - Dynamics and Control
Steven L. Brunton, University of Washington, J. Nathan Kutz, University of Washington
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Data-Driven Science and Engineering

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15 February 2019

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28 February 2019, pp 276-320
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3653 results in ebooks in fluid mechanics

Ocean Circulation in Three Dimensions

4 - Regression and Model Selection

5 - Clustering and Classification

Part IV - Reduced Order Models

Frontmatter

11 - Reduced Order Models (ROMs)

Glossary

12 - Interpolation for Parametric ROMs

Part III - Dynamics and Control

Index

3 - Sparsity and Compressed Sensing

7 - Data-Driven Dynamical Systems

10 - Data-Driven Control

Bibliography

Preface

9 - Balanced Models for Control

2 - Fourier and Wavelet Transforms

6 - Neural Networks and Deep Learning

Part II - Machine Learning and Data Analysis

8 - Linear Control Theory

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Ocean Circulation in Three Dimensions