rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: Guide to Empirical Orthogonal Functions for Climate Data Analysis
  name:
    name part: Navarra, Antonio.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Simoncini, Valeria.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: ne
    date issued: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VI, 151 p. online resource.
  abstract: 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: Elements of Linear Algebra -- Basic Statistical Concepts -- Empirical Orthogonal Functions -- Generalizations: Rotated, Complex, Extended and Combined EOF -- Cross-Covariance and the Singular Value Decomposition -- The Canonical Correlation Analysis -- Multiple Linear Regression Methods.
  note: by Antonio Navarra, Valeria Simoncini.
  subject:
    topic: Earth sciences
  subject:
    topic: Climatology
  subject:
    topic: Atmospheric sciences
  subject:
    topic: Computer mathematics
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Climate change
  subject:
    topic: Earth Sciences
  subject:
    topic: Atmospheric Sciences
  subject:
    topic: Climate Change
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Climatology
  subject:
    topic: Computational Science and Engineering
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  classification: QC851-999
  classification: 551.5
  related item:
    title info:
      title: Springer eBooks
  identifier: 9789048137022
  identifier: http://dx.doi.org/10.1007/978-90-481-3702-2
  record info:
    record creation date: 100427
    record change date: 20151204150455.0
    record identifier: 978-90-481-3702-2