This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation.
The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.Includes a comprehensive cover of theory, models and algorithms of state-of-the-art multivariate time series analysis
Discusses a lot of latest research advances in climate and environmental science
Provides a step-by-step guide on how to apply time series analysis tools in latest climate and environmental research
Is self-contained and accessible for researchers and advanced students in a wide range of disciplines
Zhihua Zhang
Time-frequency analysis Stochastic modeling and optimization Global and regional climate change Strategies for climate change mitigation Algorithms in climate science Algorithms in environmental science climate change