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
6 - Model initialization
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
As we have seen in Chapter 3, solving the equations that govern the physical systems that we are modeling is an initial- and boundary-value problem. The lateral, upper, and lower boundary conditions are discussed in Chapters 3 and 5. In this chapter will be described the procedure by which observations are processed to define initial conditions for the model dependent variables, from which the model integration begins. This process is called model initialization. There are essentially two requirements for the initialization. First, the dependent variables defined on the model grid must faithfully represent conditions in the real atmosphere (e.g., fronts should be in the correct location), and second, the gridded mass-field variables (temperature, pressure) and momentum-field variables (velocity components) should be dynamically consistent, as defined by the model equations. An example of the mass–momentum consistency requirement is that, on the synoptic scale, the gridded initial conditions should be in approximate hydrostatic and geostrophic balance. If they are not, the model will generate potentially large-amplitude inertia–gravity waves after the initialization shock, and these nonphysical waves will be overlaid on the meteorological part of the model solution until the adjustment process is complete. The final adjusted condition will prevail after the inertia–gravity waves have been damped, or have propagated off the grid of a LAM. However, the model solution will be typically unusable during this adjustment period, which is one reason for the common, historical recommendation that model output not be used for about the first 12 h of the integration.
- Type
- Chapter
- Information
- Numerical Weather and Climate Prediction , pp. 198 - 251Publisher: Cambridge University PressPrint publication year: 2010