Book contents
- Frontmatter
- Contents
- Preface
- Acronyms and abbreviations
- Principal symbols
- 1 Introduction
- 2 The governing systems of equations
- 3 Numerical solutions to the equations
- 4 Physical-process parameterizations
- 5 Modeling surface processes
- 6 Model initialization
- 7 Ensemble methods
- 8 Predictability
- 9 Verification methods
- 10 Experimental design in model-based research
- 11 Techniques for analyzing model output
- 12 Operational numerical weather prediction
- 13 Statistical post processing of model output
- 14 Coupled special-applications models
- 15 Computational fluid-dynamics models
- 16 Climate modeling and downscaling
- Appendix: Suggested code structure and experiments for a simple shallow-fluid model
- References
- Index
3 - Numerical solutions to the equations
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- Acronyms and abbreviations
- Principal symbols
- 1 Introduction
- 2 The governing systems of equations
- 3 Numerical solutions to the equations
- 4 Physical-process parameterizations
- 5 Modeling surface processes
- 6 Model initialization
- 7 Ensemble methods
- 8 Predictability
- 9 Verification methods
- 10 Experimental design in model-based research
- 11 Techniques for analyzing model output
- 12 Operational numerical weather prediction
- 13 Statistical post processing of model output
- 14 Coupled special-applications models
- 15 Computational fluid-dynamics models
- 16 Climate modeling and downscaling
- Appendix: Suggested code structure and experiments for a simple shallow-fluid model
- References
- Index
Summary
The current chapter summarizes various topics related to the numerical solution of the model equations, for resolvable scales of motion. This part of an atmospheric model that treats the resolvable scales is called the dynamical core, and is distinct from the representations of the subgrid-scale, parameterized physical processes. An especially important topic is how the numerical approximations that are used to solve the equations can affect the model solution. These nonphysical effects should be thoroughly understood by all model users. Even though basic concepts are described here, and examples provided, this presentation of numerical methods is far from exhaustive. A comprehensive text on this subject, such as Durran (1999), should be consulted if more depth is needed. Step-by-step derivations are frequently left to the reader.
Numerical methods used for solving the equations have naturally evolved over the last few decades, partly because of the results of research and partly because of changes in the available computational resources. Various factors are involved in the decision about the numerical methods to use for a particular modeling application, including computational efficiency (speed), accuracy, memory requirements, and code-structure simplicity. The last factor is especially important if the model is going to be used for research, especially by students. Simple methods that are not typically used in current operational models are sometimes described here for pedagogical purposes.
The following brief overview of concepts will help the reader to better understand the specialized material in later sections.
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- Numerical Weather and Climate Prediction , pp. 17 - 118Publisher: Cambridge University PressPrint publication year: 2010