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A Perspective on the Role of the Dynamical Core in the Development of Weather and Climate Models

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Numerical Techniques for Global Atmospheric Models

Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 80))

Abstract

This chapter aims to place the dynamical core of weather and climate models into the context of the model as a system of components. Building from basic definitions that describe models and their applications, the chapter details the component structure of a present-day atmospheric model. This facilitates the categorization of model components into types and the basic description of the dynamical core. An important point in this categorization is that the separation between ‘dynamics’ and ‘physics’ is not always clear; there is overlap. This overlap becomes more important as the spatial resolution of models increases, with resolved scales and parameterized processes becoming more conflated. From this categorization an oversimple, intuitive list of the parts of a dynamical core is made. Following this, the equations of motion are analyzed, and the design-based evolution of the dynamical core described in Lin (2004, Monthly Weather Review) is discussed. This leads to a more complete description of the dynamical core, which explicitly includes the specification of topography and grids on which the equations of motion are solved. Finally, a set of important problems for future consideration is provided. This set emphasizes the modeling system as a whole and the need to focus on physical consistency, on the scientific investigation of coupling, on the representation of physical and numerical dissipation (sub-scale mixing and filtering), and on the robust representation of divergent flows. This system-based approach of model building stands in contrast to a component-based approach and influences the details of component algorithms.

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Acknowledgements

I thank Todd Ringler for clarifying the use of the term ‘non-physical’ to solely refer to violation of monotonicity. I thank Christiane Jablonowski and the editors of this book for their thorough comments, which have significantly improved the quality of the chapter. I thank them for the opportunity to publish this point-of-view analysis on dynamical cores and their role in modeling systems.

I acknowledge and thank, Bram van Leer, Steve Zalesak, Jay Boris, and Elaine Oran for discussions at various points in my career that are at the basis of any contributions I have made to modeling atmospheric advection. I thank Jerry Mahlman for many years of friendship that included discussions and disagreements over the merit of finite difference and finite volume advection. I am grateful to have worked with Shian-Jiann Lin who is most able at visualizing solutions and turning them into substance. I acknowledge contributions from Stephen Cohn about physicality and discrete representation of the equations of motion. And, finally, I want to quote David Burridge who once said of atmospheric modeling, at just the right time, ‘There is no magic’. He paused. Then again, ‘There is no magic’.

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Authors and Affiliations

  1. Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, 2455 Hayward Street, Ann Arbor, MI, 48109, USA

    Richard B. Rood

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  1. Richard B. Rood
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Correspondence to Richard B. Rood .

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Editors and Affiliations

  1. Atmospheric Research, Dept. Climate/Global Dyn., National Center for, Boulder, Colorado, USA

    Peter Lauritzen

  2. Dept. Atmospheric, Oceanic &, Space Sciences, University of Michigan, Hayward St. 2455, Ann Arbor, 48109, Michigan, USA

    Christiane Jablonowski

  3. Organization 1433, MS-0370, Sandia National Laboratories, Albuquerque, New Mexico, USA

    Mark Taylor

  4. (NCAR), Inst. for Mathematics Applied to, National Center for Atmospheric Research, Boulder, Colorado, USA

    Ramachandran Nair

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Rood, R.B. (2011). A Perspective on the Role of the Dynamical Core in the Development of Weather and Climate Models. In: Lauritzen, P., Jablonowski, C., Taylor, M., Nair, R. (eds) Numerical Techniques for Global Atmospheric Models. Lecture Notes in Computational Science and Engineering, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11640-7_15

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