Keywords:
Climatology--Data processing.
;
Climatology--Computer simulation.
;
Climatology--Mathematical models.
;
Electronic books.
Description / Table of Contents:
A Guide to Empirical Orthogonal Functions for Climate Data Analysis introduces the reader to a practical application of the methods used in the field, including data sets from climate simulations and MATLAB codes for the algorithms.
Type of Medium:
Online Resource
Pages:
1 online resource (150 pages)
Edition:
1st ed.
ISBN:
9789048137022
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=691089
DDC:
551.60285
Language:
English
Note:
A Guide to Empirical Orthogonal Functions for Climate Data Analysis -- 1 Introduction -- 2 Elements of Linear Algebra -- 2.1 Introduction -- 2.2 Elementary Vectors -- 2.3 Scalar Product -- 2.4 Linear Independence and Basis -- 2.5 Matrices -- 2.6 Rank, Singularity and Inverses -- 2.7 Decomposition of Matrices: Eigenvalues and Eigenvectors -- 2.8 The Singular Value Decomposition -- 2.9 Functions of Matrices -- 3 Basic Statistical Concepts -- 3.1 Introduction -- 3.2 Climate Datasets -- 3.3 The Sample and the Population -- 3.4 Estimating the Mean State and Variance -- 3.5 Associations Between Time Series -- 3.6 Hypothesis Testing -- 3.7 Missing Data -- 4 Empirical Orthogonal Functions -- 4.1 Introduction -- 4.2 Empirical Orthogonal Functions -- 4.3 Computing the EOFs -- 4.3.1 EOF and Variance Explained -- 4.4 Sensitivity of EOF Calculation -- 4.4.1 Normalizing the Data -- 4.4.2 Domain of Definition of the EOF -- 4.4.3 Statistical Reliability -- 4.5 Reconstruction of the Data -- 4.5.1 The Singular Value Distribution and Noise -- 4.5.2 Stopping Criterion -- 4.6 A Note on the Interpretation of EOF -- 5 Generalizations: Rotated, Complex, Extended and Combined EOF -- 5.1 Introduction -- 5.2 Rotated EOF -- 5.3 Complex EOF -- 5.4 Extended EOF -- 5.5 Many Field Problems: Combined EOF -- 6 Cross-Covariance and the Singular Value Decomposition -- 6.1 The Cross-Covariance -- 6.2 Cross-Covariance Analysis Using the SVD -- 7 The Canonical Correlation Analysis -- 7.1 The Classical Canonical Correlation Analysis -- 7.2 The Modes -- 7.3 The Barnett-Preisendorfer Canonical Correlation Analysis -- 8 Multiple Linear Regression Methods -- 8.1 Introduction -- 8.1.1 A Slight Digression -- 8.2 A Practical PRO Method -- 8.2.1 A Different Scaling -- 8.2.2 The Relation Between the PRO Methodand Other Methods -- 8.3 The Forced Manifold -- 8.3.1 Significance Analysis.
,
8.4 The Coupled Manifold -- References -- Index.
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