𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

A Guide to Empirical Orthogonal Functions for Climate Data Analysis

✍ Scribed by Antonio Navarra, Valeria Simoncini (auth.)


Publisher
Springer Netherlands
Year
2010
Tongue
English
Leaves
151
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


Climatology and meteorology have basically been a descriptive science until it became possible to use numerical models, but it is crucial to the success of the strategy that the model must be a good representation of the real climate system of the Earth. Models are required to reproduce not only the mean properties of climate, but also its variability and the strong spatial relations between climate variability in geographically diverse regions. Quantitative techniques were developed to explore the climate variability and its relations between different geographical locations. Methods were borrowed from descriptive statistics, where they were developed to analyze variance of related observations-variable pairs, or to identify unknown relations between variables.

A Guide to Empirical Orthogonal Functions for Climate Data Analysis uses a different approach, trying to introduce the reader to a practical application of the methods, including data sets from climate simulations and MATLAB codes for the algorithms. All pictures and examples used in the book may be reproduced by using the data sets and the routines available in the book .

Though the main thrust of the book is for climatological examples, the treatment is sufficiently general that the discussion is also useful for students and practitioners in other fields.

✦ Table of Contents


Front Matter....Pages i-vi
Introduction....Pages 1-3
Elements of Linear Algebra....Pages 5-23
Basic Statistical Concepts....Pages 25-37
Empirical Orthogonal Functions....Pages 39-67
Generalizations: Rotated, Complex, Extended and Combined EOF....Pages 69-96
Cross-Covariance and the Singular Value Decomposition....Pages 97-106
The Canonical Correlation Analysis....Pages 107-121
Multiple Linear Regression Methods....Pages 123-146
Back Matter....Pages 147-151

✦ Subjects


Meteorology/Climatology; Mathematical Applications in Earth Sciences; Computational Science and Engineering; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Climate Change


πŸ“œ SIMILAR VOLUMES


Learning R: A Step-by-Step Function Guid
✍ Richard Cotton πŸ“‚ Library πŸ“… 2013 πŸ› O'Reilly Media 🌐 English

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming conce

A Guide to Functional Analysis
✍ Krantz S.G. πŸ“‚ Library πŸ“… 2013 πŸ› Mathematical Association of America 🌐 English

This book is a quick but precise and careful introduction to the subject of functional analysis. It covers the basic topics that can be found in a basic graduate analysis text. But it also covers more sophisticated topics such as spectral theory, convexity, and fixed-point theorems. A special featur

A Beginner's Guide to Python for Data An
✍ Henry Harvin πŸ“‚ Library πŸ“… 2023 πŸ› India Education LLP 🌐 English

Want complete instructions on the Python library and its elements? Get solutions with practical case studies and implications of Python in data analysis through this book. β€œA Beginner's Guide to Python for Data Analysis” will help you to learn about the different aspects of Python along with its imp

A practical guide to data analysis for p
✍ Louis Lyons πŸ“‚ Library πŸ“… 1991 πŸ› Cambridge University Press 🌐 English

This textbook is intended for undergraduates who are carrying out laboratory experiments in the physical sciences for the first time. It is a practical guide on how to analyze data and estimate errors. The necessary formulas for performing calculations are given, and the ideas behind them are expl