Analysis of Climate Variability

This book is a collection of various applications of statistical concepts in climatology.

Stresses the application of statistical techniques Discussing numerous examples dealing with the analysis of observed data and with the evaluation of model results

Klappentext

Various problems in climate research, which require the use of advanced statistical techniques, are considered in this book. The examples emphasize the notion that the knowledge of statistical techniques alone is not sufficient. Good physical understanding of the specific problems in climate research is needed to guide the researcher in choosing the right approach to obtain meaningful answers. The second edition of this book, originally based on contributions given during a school sponsored by the European Union on the Italian island of Elba, continues to be based on these general principles. The general outline has been kept the same, covering aspects such as the examination of the observational record, stochastic climate models, analytical techniques, e.g. EOF, teleconnections and so on, but the chapters have been revised and updated, in some cases extensively, to cover the advances in the field in the years since the first edition.

Inhalt
1 The Development of Climate Research.- 2 Misuses of Statistical Analysis in Climate Research.- 3 Climate Spectra and Stochastic Climate Models.- 4 The Instrumental Data Record: Its Accuracy and Use in ttempts to Identify the CO2 Signal.- 5 Interpreting High-Resolution Proxy Climate Data The Example of Dendroclimatology.- 6 Analysing the.Boreal Summer Relationship Between Worldwide Sea-Surface Temperature and Atmospheric Variability.- 7 The Simulation of Weather Types in GCMs: A Regional Approach to Control-Run Validation.- 8 Statistical Analysis of GCM Output.- 9 Field Intercomparison.- 10 The Evaluation of Forecasts.- 11 Stochastic Modeling of Precipitation with Applications to Climate Model Downscaling.- 12 Teleconnection Patterns.- 13 Spatial Patterns: EOFs and CCA.- 14 Patterns in Time: SSA and MSSA.- 15 Multivariate Statistical Modeling: POP-Model as a First Order Approximation.- References.- Abbreviations.