Provides a comprehensive yet accessible treatment of computer-based weather and climate prediction, for graduate students, researchers and professionals. This book provides a comprehensive yet accessible treatment of weather and climate prediction, for graduate students, researchers and professionals. It teaches the strengths, weaknesses and best practices for the use of atmospheric models. It is ideal for the many scientists who use such models across a wide variety of applications.
Provides a comprehensive yet accessible treatment of computer-based weather and climate prediction, for graduate students, researchers and professionals.This book provides a comprehensive yet accessible treatment of weather and climate prediction, for graduate students, researchers and professionals. It teaches the strengths, weaknesses and best practices for the use of atmospheric models. It is ideal for the many scientists who use such models across a wide variety of applications.
Tom Warner was a Professor in the Department of Meteorology at the Pennsylvania State University before accepting his current joint appointment with the National Center for Atmospheric Research and the University of Colorado in Boulder, Colorado. His career has involved teaching and research in numerical weather prediction and mesoscale meteorological processes. He has published on these and other subjects in numerous professional journals. His recent research and teaching has focused on atmospheric processes, operational weather prediction, and arid-land meteorology. He is the author of Desert Meteorology (2004), also published by Cambridge University Press.
Inhaltsangabe
Preface List of acronyms List of 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.
Preface List of acronyms List of 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.
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