Climate Variability Diagnosis and Prediction Methods

Author: Wu Hongbao
Publisher:
Publish Date: 2005-10-01
Features: This book provides a comprehensive and systematic introduction to the methods for diagnosing and predicting climate variability, divided into eight chapters. The first four chapters cover multivariate statistical methods, including different forms of EOF (PCA), POP, SVD, CCA, RA, as well as nonlinear PCA and CCA. The conventional linear EOF (PCA) serves as the foundation for these methods. Chapters five and six introduce frequency domain analysis methods, including power spectra, harmonics, wavelet analysis, filtering, singular spectrum analysis, and nonlinear singular spectrum analysis, with Fourier analysis being the foundation for these methods. Chapter seven discusses methods for diagnosing the predictability of climate variability, while Chapter eight covers climate prediction methods that combine ocean dynamical models with statistical atmospheric models. This book is one of the graduate textbooks for the Meteorology program at Nanjing University of Information Science & Technology. It can also serve as a reference text for related disciplines such as geography, hydrology, and oceanography. For senior scientific researchers and professionals working in meteorological services, this book offers significant reference value.