1. Physics-dynamics coupling in weather, climate, and Earth system models: Challenges and recent progress
- Author
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Piet Termonia, Florian Lemarié, Nigel Wood, Christiane Jablonowski, Markus Gross, Martin Willett, Bob Beare, Hans Johansen, Colin M. Zarzycki, Hui Wan, Almut Gassmann, Ruby Leung, Sylvie Malardel, Koichi Sakaguchi, Philip J. Rasch, Peter M. Caldwell, Peter H. Lauritzen, David L. Williamson, Eric Blayo, M. J. P. Cullen, Daniel Klocke, Diana R. Thatcher, Departamento de Oceanografia Fisica CICESE [Mexico], Centro de Investigacion Cientifica y de Education Superior de Ensenada [Mexico] (CICESE), Pacific Northwest National Laboratory (PNNL), Lawrence Livermore National Laboratory (LLNL), National Center for Atmospheric Research [Boulder] (NCAR), Hans Ertel Zentrum für Wetterforschung [Offenbach], Deutscher Wetterdienst [Offenbach] (DWD), University of Michigan [Ann Arbor], University of Michigan System, United Kingdom Met Office [Exeter], College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Mathematics and computing applied to oceanic and atmospheric flows (AIRSEA), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS), European Centre for Medium-Range Weather Forecasts (ECMWF), Institut Royal Météorologique de Belgique [Bruxelles] (IRM), Leibniz-Institut für Atmosphärenphysik (IAP), Universität Rostock-Leibniz Association, Lawrence Berkeley National Laboratory [Berkeley] (LBNL), ANR-16-CE01-0007,COCOA,Méthodes mathématiquement et physiquement consistantes pour le couplage océan-atmosphère(2016), ANR-14-CE23-0010,HEAT,Modélisation atmosphérique hautement efficace(2014), and Institut Royal Météorologique de Belgique [Bruxelles] - Royal Meteorological Institute (IRM)
- Subjects
Atmospheric Science ,PDF-BASED MODEL ,010504 meteorology & atmospheric sciences ,VARIABLE-RESOLUTION CESM ,0208 environmental biotechnology ,Parameterization ,physics.ao-ph ,02 engineering and technology ,01 natural sciences ,Atmospheric Sciences ,PLANETARY BOUNDARY-LAYER ,GLOBAL-MODEL ,Fluid dynamics ,Meteorology & Atmospheric Sciences ,OCEAN MODEL ,Model errors ,Model evaluation ,0105 earth and related environmental sciences ,Physics ,[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,GENERAL-CIRCULATION MODELS ,Applied Mathematics ,Dynamics (mechanics) ,Model comparison ,modeling ,Mechanics ,020801 environmental engineering ,Earth system science ,Climate Action ,PART I ,Coupling (physics) ,SPECTRAL ELEMENT ,13. Climate action ,Earth and Environmental Sciences ,ORDER TURBULENCE CLOSURE ,[MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA] ,performance ,COMMUNITY ATMOSPHERE MODEL ,Coupled models ,Numerical analysis - Abstract
Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions.
- Published
- 2018
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