Mathematical Strategies for Climate and Long Range Weather Forecasting in Hierarchy of Models

1. Auflage 2019
ISBN: 978-3-319-22326-1
Verlag: Springer

Buch, Englisch, Band XXX, 300 Seiten, Book, Format (B × H): 155 mm x 235 mm

Reihe: Mathematics of Planet Earth

This book gives a research exposition of interdisciplinary topics at the cutting edge of the applied mathematics of climate change and long range weather forecasting through a hierarchy of models with contemporary applications to grand challenges such as intraseasonal weather prediction. The developments include recent physics constrained low-order models, new analog prediction models, and equation free methods to capture intermittency and low frequency variabilities in massive datasets through Nonlinear Laplacian Spectral Analysis (NLSA) which combines delayed embeddings, causal constraints, and machine learning. Applications to grand challenges such as tropical intraseasonal variability of the Madden-Julian Oscillation (MJO) and the Monsoon as well as sea ice re-emergence in the Arctic on yearly time scales. A highlight is the exposition and pedagogical development of recent intermediate stochastic skeleton models to capture the main features of the MJO through PDE ideas, stochastics, and physical reasoning and compared with observational data. The mathematical theory of model error and the use of information theory combined with linear statistical response theory in a calibration stage are applied to improve long range forecasting and multi-scale data assimilation with concrete examples.

Zielgruppe

Graduate

Autoren/Hrsg.

Majda, Andrew

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Geowissenschaften Geologie Meteorologie, Klimatologie
• Naturwissenschaften Physik Physik Allgemein Theoretische Physik, Mathematische Physik, Computerphysik
• Geowissenschaften Umweltwissenschaften Klimawandel, Globale Erwärmung

Inhaltsverzeichnis

Overview and Interdisciplinary Mathematical Geoscience Perspective on Climate and Longe Range Weather Forcasting (Majda).- Novel Nonlinear Time-Series Techniques to Capture both Intermittency and Low-Frequency Variability (Giannakis and Majda).- Predictions, Observations, and Simplified Models for Tropical Intraseasonal Variability (Majda and Stechmann).- Mathematical Strategy for Prediction with Low-Order Models (Giannakis, Harlim and Majda).- Model Errors and Information Barriers for Data Assimilation and Low-Order Prediction (Majda and Harlim).

Über Autor(innen)

Andrew J. Majda is the Morse Professor of Arts and Sciences at the Courant Institute of New York University.