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OLS Field Name OLS Field Data
Main Title Modeling methods for marine science /
Author Glover, David M.,
Other Authors
Author Title of a Work
Jenkins, William J.
Doney, Scott Christopher.
Publisher Cambridge University Press,
Year Published 2011
OCLC Number 690090203
ISBN 9780521867832; 0521867835
Subjects Marine sciences--Mathematical models.
Internet Access
Description Access URL
Contributor biographical information http://catdir.loc.gov/catdir/enhancements/fy1201/2011284602-b.html
Publisher description http://catdir.loc.gov/catdir/enhancements/fy1201/2011284602-d.html
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EKCM  GC10.4.M36G57 2011 CEMM/GEMMD Library/Gulf Breeze,FL 03/29/2016
Collation xv, 571 pages : illustrations, maps ; 26 cm
Notes Includes bibliographical references (pages 552-563) and index.
Contents Notes This is a textbook on modelling, data analysis and numerical techniques for advanced students and researchers in chemical, biological, geological and physical oceanography. 1. Resources, MATLAB primer, and introduction to linear algebra -- 1.1. Resources -- 1.2. Nomenclature -- 1.3. MATLAB primer -- 1.4. Basic linear algebra -- 2. Measurement theory, probability distributions, error propagation and analysis -- 2.1. Measurement theory -- 2.2. normal distribution -- 2.3. Doing the unspeakable: throwing out data points? -- 2.4. Error propagation -- 2.5. Statistical tests and the hypothesis -- 2.6. Other distributions -- 2.7. central limit theorem -- 2.8. Covariance and correlation -- 2.9. Basic non-parametric tests -- 2.10. Problems -- 3. Least squares and regression techniques, goodness of fit and tests, and nonlinear least squares techniques -- 3.1. Statistical basis for regression -- 3.2. Least squares fitting a straight line -- 3.3. General linear least squares technique -- 3.4. Nonlinear least squares techniques -- 4. Principal component and factor analysis -- 4.1. Conceptual foundations -- 4.2. Splitting and lumping -- 4.3. Optimum multiparameter (OMP) analysis -- 4.4. Principal component analysis (PCA) -- 4.5. Factor analysis -- 4.6. Empirical orthogonal functions (EOFs) -- 5. Sequence analysis I: Uniform series, cross- and autocorrelation, and Fourier transforms -- 5.1. Goals and examples of sequence analysis -- 5.2. ground rules: stationary processes, etc. -- 5.3. Analysis in time and space -- 5.4. Cross-covariance and cross-correlation -- 5.5. Convolution and implications for signal theory -- 5.6. Fourier synthesis and the Fourier transform -- 6. Sequence analysis II: Optimal filtering and spectral analysis -- 6.1. Optimal (and other) filtering -- 6.2. fast Fourier transform (FFT) -- 6.3. Power spectral analysis -- 6.4. Nyquist limits and data windowing -- 6.5. Non-uniform time series -- 6.6. Wavelet analysis -- 7. Gridding, objective mapping, and kriging -- 7.1. Contouring and gridding concepts -- 7.2. Structure functions -- 7.3. Optimal estimation -- 7.4. Kriging examples with real data -- 8. Integration of ODEs and 0D (box) models -- 8.1. ODE categorization -- 8.2. Examples of population or box models (0D) -- 8.3. Analytical solutions -- 8.4. Numerical integration techniques -- 8.5. numerical example -- 9. model building tutorial -- 9.1. Motivation and philosophy -- 9.2. Scales -- 9.3. First Example: The Lotka-Volterra model -- 9.4. second example: exploring our two-box phosphate model -- 9.5. third example: multi-box nutrient model of the world ocean. 10. Model analysis and optimization -- 10.1. Basic concepts -- 10.2. Methods using only the cost function -- 10.3. Methods adding the cost function gradient -- 10.4. Stochastic algorithms -- 10.5. ecosystem optimization example -- 11. Advection-diffusion equations and turbulence -- 11.1. Rationale -- 11.2. basic equation -- 11.3. Reynolds decomposition -- 11.4. Stirring, straining, and mixing -- 11.5. importance of being non -- 11.6. numbers game -- 11.7. Vertical turbulent diffusion -- 11.8. Horizontal turbulent diffusion -- 11.9. effects of varying turbulent diffusivity -- 11.10. Isopycnal coordinate systems -- 12. Finite difference techniques -- 12.1. Basic principles -- 12.2. forward time, centered space (FTCS) algorithm -- 12.3. example: tritium and 3He in a pipe -- 12.4. Stability analysis of finite difference schemes -- 12.5. Upwind differencing schemes -- 12.6. Additional concerns, and generalities -- 12.7. Extension to more than one dimension -- 12.8. Implicit algorithms -- 13. Open ocean 1D advection-diffusion models -- 13.1. Rationale -- 13.2. general setting and equations -- 13.3. Stable conservative tracers: solving for K/w -- 13.4. Stable non-conservative tracers: solving for J/w -- 13.5. Radioactive non-conservative tracers: solving for w -- 13.6. Denouement: computing the other numbers -- 14. One-dimensional models in sedimentary systems -- 14.1. General theory -- 14.2. Physical and biological diagenetic processes -- 14.3. Chemical diagenetic processes -- 14.4. modeling example: CH4 at the FOAM site. 15. Upper ocean 1D seasonal models -- 15.1. Scope, background, and purpose -- 15.2. physical model framework -- 15.3. Atmospheric forcing -- 15.4. The physical model's internal workings -- 15.5. Implementing the physical model -- 15.6. Adding gases to the model -- 15.7. Implementing the gas model -- 15.8. Biological oxygen production in the model -- 16. Two-dimensional gyre models -- 16.1. Onward to the next dimension -- 16.2. two-dimensional advection-diffusion equation -- 16.3. Gridding and numerical considerations -- 16.4. Numerical diagnostics -- 16.5. Transient tracer invasion into a gyre -- 16.6. Doubling up for a better gyre model -- 16.7. Estimating oxygen utilization rates -- 16.8. Non-uniform grids -- 17. Three-dimensional general circulation models (GCMs) -- 17.1. Dynamics, governing equations, and approximations -- 17.2. Model grids and numerics -- 17.3. Surface boundary conditions -- 17.4. Sub-grid-scale parameterizations -- 17.5. Diagnostics and analyzing GCM output -- 18. Inverse methods and assimilation techniques -- 18.1. Generalized inverse theory -- 18.2. Solving under-determined systems -- 18.3. Ocean hydrographic inversions -- 18.4. Data assimilation methods -- 19. Scientific visualization -- 19.1. Why scientific visualization? -- 19.2. Data storage, manipulation, and access -- 19.3. perception of scientific data -- 19.4. Using MATLAB to present scientific data -- 19.5. Some non-MATLAB visualization tools -- 19.6. Advice on presentation graphics -- Getting started with MATLAB -- Good working practices -- Doing it faster -- Choose your algorithms wisely -- Automating tasks -- Graphical tricks -- Plotting oceanographic sections -- Reading and writing data.
Place Published Cambridge ; New York
PUB Date Free Form 2011
BIB Level m
Medium unmediated
Content text
Carrier volume
Cataloging Source OCLC/T
LCCN 2011284602
OCLC Time Stamp 20160324121644
Language eng
Origin OCLC
Type CAT
OCLC Rec Leader 07718cam 2200505 a 45020