Call number:
AWI A13-04-0126
Description / Table of Contents:
This comprehensive text and reference work on numerical weather prediction covers for the first time, not only methods for numerical modeling, but also the important related areas of data assimilation and predictability. It incorporates all aspects of environmental computer modeling including an historical overview of the subject, equations of motion and their approximations, a modern and clear description of numerical methods, and the determination of initial conditions using weather observations (an important new science known as data assimilation). Finally, this book provides a clear discussion of the problems of predictability and chaos in dynamical systems and how they can be applied to atmospheric and oceanic systems. Professors and students in meteorology, atmospheric science, oceanography, hydrology and environmental science will find much to interest them in this book, which can also form the basis of one or more graduate-level courses.
Type of Medium:
Monograph available for loan
Pages:
XXII, 341 S. : graph. Darst., Kt.
Edition:
1st publ. 2003,Reprint. 2004
ISBN:
0521796296
Language:
English
Note:
Contents:
Foreword. -
Acknowledgements. -
List of abbreviations. -
List of variables. -
1 Historical overview of numerical weather prediction. -
1.1 Introduction. -
1.2 Early developments. -
1.3 Primitive equations, global and regional models, and nonhydrostatic models. -
1.4 Data assimilation: determination of the initial conditions for the computer forecasts. -
1.5 Operational NWP and the evolution of forecast skill. -
1.6 Nonhydrostatic mesoscale models. -
1.7 Weather predictability, ensemble forecasting, and seasonal to interannual prediction. -
1.8 The future. -
2 The continuous equations. -
2.1 Governing equations. -
2.2 Atmospheric equations of motion on spherical coordinates. -
2.3 Basic wave oscillations in the atmosphere. -
2.4 Filtering approximations. -
2.5 Shallow water equations, quasi-geostrophic filtering, and filtering of inertia-gravity waves. -
2.6 Primitive equations and vertical coordinates. -
3. Numerical discretization of the equations of motion. -
3.1 Classification of partial differential equations (PDEs). -
3.2 Initial value problems: numerical solution. -
3.3 Space discretization methods. -
3.4 Boundary value problems. -
3.5 Lateral boundary conditions for regional models. -
4 Introduction to the parameterization of subgrid-scale physical processes. -
4.1 Introduction. -
4.2 Subgrid-scale processes and Reynolds averaging. -
4.3 Overview of model parameterizations. -
5 Data assimilation. -
5.1 Introduction. -
5.2 Empirical analysis schemes. -
5.3 Introduction to least squares methods. -
5.4 Multivariate statistical data assimilation methods. -
5.5 3D-Var, the physical space analysis scheme (PSAS), and their relation to OI. -
5.6 Advanced data assimilation methods with evolving forecast error covariance. -
5.7 Dynamical and physical balance in the initial conditions. -
5.8 Quality control of observations. -
6 Atmospheric predictability and ensemble forecasting. -
6.1 Introduction to atmospheric predictability. -
6.2 Brief review of fundamental concepts about chaotic systems. -
6.3 Tangent linear model, ad joint model, singular vectors, and Lyapunov vectors. -
6.4 Ensemble forecasting: early studies. -
6.5 Operational ensemble forecasting methods. -
6.6 Growth rate errors and the limit of predictability in mid-latitudes and in the tropics. -
6.7 The role of the oceans and land in monthly, seasonal, and interannual predictability. -
6.8 Decadal variability and climate change. -
Appendix A The early history of NWP. -
Appcndix B Coding and checking the tangent linear and the adjoint models. -
Appendix C Post-processing of numerical model output to obtain station weather forecasts. -
References. -
Index.
Location:
AWI Reading room
Branch Library:
AWI Library
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