Mathematical and Physical Fundamentals of Climate Change - 1st Edition - ISBN: 9780128000663, 9780128005835

Mathematical and Physical Fundamentals of Climate Change

1st Edition

Authors: Zhihua Zhang John Moore
eBook ISBN: 9780128005835
Hardcover ISBN: 9780128000663
Imprint: Elsevier
Published Date: 25th November 2014
Page Count: 494
Tax/VAT will be calculated at check-out Price includes VAT (GST)
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
30% off
30% off
30% off
30% off
30% off
20% off
20% off
60.99
42.69
42.69
42.69
42.69
42.69
48.79
48.79
99.95
69.97
69.97
69.97
69.97
69.97
79.96
79.96
75.95
53.16
53.16
53.16
53.16
53.16
60.76
60.76
Unavailable
Price includes VAT (GST)
DRM-Free

Easy - Download and start reading immediately. There’s no activation process to access eBooks; all eBooks are fully searchable, and enabled for copying, pasting, and printing.

Flexible - Read on multiple operating systems and devices. Easily read eBooks on smart phones, computers, or any eBook readers, including Kindle.

Open - Buy once, receive and download all available eBook formats, including PDF, EPUB, and Mobi (for Kindle).

Institutional Access

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Description

Mathematical and Physical Fundamentals of Climate Change is the first book to provide an overview of the math and physics necessary for scientists to understand and apply atmospheric and oceanic models to climate research.  The book begins with basic mathematics then leads on to specific applications in atmospheric and ocean dynamics, such as fluid dynamics, atmospheric dynamics, oceanic dynamics, and glaciers and sea level rise.  Mathematical and Physical Fundamentals of Climate Change provides a solid foundation in math and physics with which to understand global warming, natural climate variations, and climate models. This book informs the future users of climate models and the decision-makers of tomorrow by providing the depth they need. Developed from a course that the authors teach at Beijing Normal University, the material has been extensively class-tested and contains online resources, such as presentation files, lecture notes, solutions to problems and MATLab codes.

Key Features

  • Includes MatLab and Fortran programs that allow readers to create their own models
  • Provides case studies to show how the math is applied to climate research
  • Online resources include presentation files, lecture notes, and solutions to problems in book for use in classroom or self-study

Readership

Upper-level UG/Grad Students, post-docs, researchers in meteorology, climatology, oceanography, earth science and environmental science

Table of Contents

  • Preface: Interdisciplinary Approaches to Climate Change Research
  • Chapter 1: Fourier Analysis
    • Abstract
    • 1.1 Fourier series and fourier transform
    • 1.2 Bessel'a inequality and parseval's identity
    • 1.3 Gibbs phenomenon
    • 1.4 Poisson summation formulas and shannon sampling theorem
    • 1.5 Discrete fourier transform
    • 1.6 Fast fourier transform
    • 1.7 Heisenberg uncertainty principle
    • 1.8 Case study: arctic oscillation indices
    • Problems
  • Chapter 2: Time-Frequency Analysis
    • Abstract
    • 2.1 Windowed Fourier Transform
    • 2.2 Wavelet Transform
    • 2.3 Multiresolution Analyses and Wavelet Bases
    • 2.4 Hilbert Transform, Analytical Signal, and Instantaneous Frequency
    • 2.5 Wigner-Ville Distribution and Cohen's Class
    • 2.6 Empirical Mode Decompositions
    • Problems
  • Chapter 3: Filter Design
    • Abstract
    • 3.1 Continuous linear time-invariant systems
    • 3.2 Analog filters
    • 3.3 Discrete linear time-invariant systems
    • 3.4 Linear-phase filters
    • 3.5 Designs of FIR filters
    • 3.6 IIR filters
    • 3.7 Conjugate mirror filters
    • Problems
  • Chapter 4: Remote Sensing
    • Abstract
    • 4.1 Solar and thermal radiation
    • 4.2 Spectral regions and optical sensors
    • 4.3 Spatial filtering
    • 4.4 Spatial blurring
    • 4.5 Distortion correction
    • 4.6 Image fusion
    • 4.7 Supervised and unsupervised classification
    • 4.8 Remote sensing of atmospheric carbon dioxide
    • 4.9 Moderate resolution imaging spectroradiometer data products and climate change
    • Problems
  • Chapter 5: Basic Probability and Statistics
    • Abstract
    • 5.1 Probability space, random variables, and their distributions
    • 5.2 Jointly distributed random variables
    • 5.3 Central limit theorem and law of large numbers
    • 5.4 Minimum mean square error
    • 5.5 χ2-distribution, t-distribution, and F-distribution
    • 5.6 Parameter estimation
    • 5.7 Confidence interval
    • 5.8 Tests of statistical hypotheses
    • 5.9 Analysis of variance
    • 5.10 Linear regression
    • 5.11 Mann-Kendall trend test
    • Problems
  • Chapter 6: Empirical Orthogonal Functions
    • Abstract
    • 6.1 Random vector fields
    • 6.2 Classical EOFs
    • 6.3 Estimation of EOFs
    • 6.4 Rotation of EOFs
    • 6.5 Complex EOFs and hilbert EOFs
    • 6.6 Singular value decomposition
    • 6.7 Canonical correlation analysis
    • 6.8 Singular spectrum analysis
    • 6.9 Principal oscillation patterns
    • Problems
  • Chapter 7: Random Processes and Power Spectra
    • Abstract
    • 7.1 Stationary and non-stationary random processes
    • 7.2 Markov process and brownian motion
    • 7.3 Calculus of random processes
    • 7.4 Spectral analysis
    • 7.5 Wiener filtering
    • 7.6 Spectrum estimation
    • 7.7 Significance tests of climatic time series
    • Problems
  • Chapter 8: Autoregressive Moving Average Models
    • Abstract
    • 8.1 Arma processes
    • 8.2 Yule-Walker equation and spectral density
    • 8.3 Prediction algorithms
    • 8.4 Asymptotic theory
    • 8.5 Estimates of means and covariance functions
    • 8.6 Estimation for ARMA models
    • 8.7 Arima models
    • 8.8 Multivariate ARMA processes
    • 8.9 Application in climatic and hydrological research
    • Problems
  • Chapter 9: Data Assimilation
    • Abstract
    • 9.1 Concept of data assimilation
    • 9.2 Cressman method
    • 9.3 Optimal interpolation analysis
    • 9.4 Cost function and three-dimensional variational analysis
    • 9.5 Dual of the optimal interpolation
    • 9.6 Four-dimensional variational analysis
    • 9.7 Kalman filter
    • Problems
  • Chapter 10: Fluid Dynamics
    • Abstract
    • 10.1 Gradient, divergence, and curl
    • 10.2 Circulation and flux
    • 10.3 Green's theorem, divergence theorem, and stokes's theorem
    • 10.4 Equations of motion
    • 10.5 Energy flux and momentum flux
    • 10.6 Kelvin law
    • 10.7 Potential function and potential flow
    • 10.8 Incompressible fluids
    • Problems
  • Chapter 11: Atmospheric Dynamics
    • Abstract
    • 11.1 Two simple atmospheric models
    • 11.2 Atmospheric composition
    • 11.3 Hydrostatic balance equation
    • 11.4 Potential temperature
    • 11.5 Lapse rate
    • 11.6 Clausius-clapeyron equation
    • 11.7 Material derivatives
    • 11.8 Vorticity and potential vorticity
    • 11.9 Navier-stokes equation
    • 11.10 Geostrophic balance equations
    • 11.11 Boussinesq approximation and energy equation
    • 11.12 Quasi-geostrophic potential vorticity
    • 11.13 Gravity waves
    • 11.14 Rossby waves
    • 11.15 Atmospheric boundary layer
    • Problems
  • Chapter 12: Oceanic Dynamics
    • Abstract
    • 12.1 Salinity and mass
    • 12.2 Inertial motion
    • 12.3 Oceanic ekman layer
    • 12.4 Geostrophic currents
    • 12.5 Sverdrup's theorem
    • 12.6 Munk's theorem
    • 12.7 Taylor-proudman theorem
    • 12.8 Ocean-wave spectrum
    • 12.9 Oceanic tidal forces
    • Problems
  • Chapter 13: Glaciers and Sea Level Rise
    • Abstract
    • 13.1 Stress and strain
    • 13.2 Glen's law and generalized glen's law
    • 13.3 Density of glacier ice
    • 13.4 Glacier mass balance
    • 13.5 Glacier momentum balance
    • 13.6 Glacier energy balance
    • 13.7 Shallow-ice and shallow-shelf approximations
    • 13.8 Dynamic ice sheet models
    • 13.9 Sea level rise
    • 13.10 Semiempirical sea level models
    • Problems
  • Chapter 14: Climate and Earth System Models
    • Abstract
    • 14.1 Energy balance models
    • 14.2 Radiative convective models
    • 14.3 Statistical dynamical models
    • 14.4 Earth system models
    • 14.5 Coupled model intercomparison project
    • 14.6 Geoengineering model intercomparison project
    • Problems
  • Index

Details

No. of pages:
494
Language:
English
Copyright:
© Elsevier 2015
Published:
Imprint:
Elsevier
eBook ISBN:
9780128005835
Hardcover ISBN:
9780128000663

About the Author

Zhihua Zhang

Zhihua Zhang is a Tenured Research Professor & Senior Scientist and an associate director of Polar Climate and Environment Key Laboratory in Beijing Normal University, China. His research interests are Mechanisms of Climate Change, Climatic Time Series Analysis, Signal & Image Processing, and Applied Mathematics. Recently, he has published more than 40 first-authored papers and is editoring a special volume on carbon emissions reduction for the Journal of Cleaner Production as the managing guest editor. Zhihua Zhang is an Editor-in-Chief of “American Journal of Climate Change”, an associate editor of “Arabian Journal of Geosciences”, an Editorial Board Member of “Advances in Meteorology”, an Associate Editor of “EURASIP Journal on Advances in Signal Processing”, an Editorial Board Member of “International Journal of Global Warming”, and an Editorial Board Member of “Journal of Applied Mathematics”. Zhihua Zhang’s research is supported by National Key Science Program for Global Change Research, Fundamental Research Funds for the Central Universities (Key Program) and NSFC.

Affiliations and Expertise

Tenured Research Professor and Senior Scientist, Beijing Normal University, China

John Moore

John C. Moore is a Research Professor at Universities of Lapland (Finland) and Uppsala (Sweden), a Chief Scientist & Research Professor, Beijing Normal University (China), Guest professor at Polar Research Institute of China, as well as the Director of Polar Climate and Environment Key Laboratory. John C. Moore has published over 100 papers, where six papers have been published in Proceedings of the National Academy of Sciences (PNAS). John C. Moore’s research includes climate change; past sea level change and prediction, natural and anthropogenic climate forcing, impacts of extreme climate events, and computer modelling of glacier flow and evolution. John C. Moore was Finnish representative on the International Arctic Science Committee, Glaciology Group. John Moore is the Editor-in-Chief of “American Journal of Climate Change” and an Editorial Board Member of “The Cryosphere”. John C. Moore’s research is supported by European Science Foundation, EU Northern Periphery Program, National Key Science Program for Global Change Research (China), Finnish Academy, and NSFC

Affiliations and Expertise

Research Professor, University of Lapland, Finland; Chief Scientist & Research Professor, Beijing Normal University, China