Synopses & Reviews
Scientific descriptions of the climate have traditionally been based on the study of average meteorological values taken from different positions around the world. In recent years however it has become apparent that these averages should be considered with other statistics that ultimately characterize spatial and temporal variability. This book is designed to meet that need. It is based on a course in computational statistics taught by the author that arose from a variety of projects on the design and development of software for the study of climate change, using statistics and methods of random functions.
Review
"Presents two major areas of application: multidimensional spectral and correlation analysis; and multivariate autoregressive modelling" --Geo Abstracts
Review
"Presents two major areas of application: multidimensional spectral and correlation analysis; and multivariate autoregressive modelling" --Geo Abstracts
Synopsis
Descriptions of climate are based on average meteorological values taken from different global positions, but these averages should be considered together with other statistics that ultimately characterize spatial and temporal variability. This book meets this need.
Description
Includes bibliographical references (p. 348-354) and index.
Table of Contents
1. Digital Filters
2. Averaging and Simple Models
3. Random Processes and Fields
4. Variability of ARMA Processes
5. Multivariate AR Processes
6. Historical Records
7. The GCM Validation
8. Second Moments of Rain
References
Index