Computer Modelling in Atmospheric and Oceanic Sciences: Building Knowledge / Edition 1

Computer Modelling in Atmospheric and Oceanic Sciences: Building Knowledge / Edition 1

ISBN-10:
3540203532
ISBN-13:
9783540203537
Pub. Date:
11/19/2004
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3540203532
ISBN-13:
9783540203537
Pub. Date:
11/19/2004
Publisher:
Springer Berlin Heidelberg
Computer Modelling in Atmospheric and Oceanic Sciences: Building Knowledge / Edition 1

Computer Modelling in Atmospheric and Oceanic Sciences: Building Knowledge / Edition 1

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Overview

This textbook is about quasi-realistic models in atmospheric and oceanic sciences. Understanding the basis and limitations of these models is important since far reaching decisions about the environment are based on these models. It is novel in that it goes beyond a technical discussion of these quasi-realistic models and emphasizes their role and utility in generating new useful knowledge about the system. The book is written in a generally understandable way, with technical details relegated to a set of comprehensive appendices. The line of reasoning is illustrated by numerous examples, from both applied and fundamental research. It is a source of information for graduate students and scientists alike working in the field of environmental sciences.


Product Details

ISBN-13: 9783540203537
Publisher: Springer Berlin Heidelberg
Publication date: 11/19/2004
Edition description: 2004
Pages: 304
Product dimensions: 6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1 Introduction.- 2 Computer Models.- 3 Models and Data.- 4 The Dynamics of Tides and Climate.- 5 Modeling in Applied Environmental Sciences — Forecasting, Analysis and Scenarios.- 6 Modeling in Fundamental Environmental Sciences — Simulation and Hypothesis Testing.- 7 Issues and Conclusions.- Appendices.- A Fluid Dynamics.- A.1 The Balance Equations.- A.1.1 Mass Balances.- A.1.2 Momentum Balance.- A.1.3 Energy Balance.- A.2 Thermodynamic Specification.- A.3 The Phenomenological Flux Laws.- A.4 Boundary Conditions.- A.5 A Closer Look at the Balance Equations.- A.5.1 Cloud Formation.- A.5.2 Radiation.- A.5.3 Phohemical Reactions.- A.6 Reynolds Decomposition.- A.7 Parameterization of Interior Fluxes.- A.7.1 Eddy Diffusivities.- A.7.2 Eddy Viscosities.- A.8 Parameterization of Boundary Layer Fluxes.- A.8.1 The Constant Flux Layer.- A.8.2 The Planetary Boundary Layer.- A.9 Approximations.- A.9.1 Anelastic Approximation.- A.9.2 Shallow Water Approximation.- A.10 Representations.- A.10.1 Vertical Coordinates.- A.10.2 Decoupling.- B Numerics.- B.1 Discretization.- B.2 Partial Differential Equations.- B.2.1 Elliptic Problems.- B.2.2 Parabolic Problems.- B.2.3 Hyperbolic Problems.- B.3 Staggered Grids.- B.4 Spectral Models.- B.5 Finite Element Models.- C Statistical Analysis.- C.1 Random Variables and Processes.- C.1.1 Probability Function.- C.1.2 Bivariate Random Variables.- C.1.3 Random Processes.- C.2 Characteristic Parameters.- C.2.1 Expectation Values.- C.2.2 Empirical Orthogonal Functions.- C.2.3 Decomposition of Variance.- C.2.4 Skill Scores.- C.3 Inference.- C.3.1 Basic Aspects of Estimation.- C.3.2 Estimation of Auto-covariance Functions.- C.3.3 Estimation of Spectra.- C.3.4 Estimation of EOFs.- C.3.5 Hypothesis Testing.- D Data Assimilation.- D.1 Estimation.- D.2 Filtering.- D.2.1 Kalman Filter.- D.2.2 Optimal or Statistical Interpolation.- D.2.3 Nudging.- D.2.4 Blending and Direct Insertion.- D.2.5 Minimization.- D.3 Smoothing.- D.3.1 Adjoint Method.- D.3.2 Inverse Method.- D.3.3 Parameter Estimation.- References.
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