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Abstract:

Coupled climate models are multiphysics models comprising multi-ple separately developed codes that are combined into a single physical system. This composition of codes is amenable to a scripting solution, and Python is a language that offers many desirable properties for this task. We have prototyped a Python coupling and control infrastruc-ture for version 3.0 of the Community Climate System Model (ccsm3). Our objective was to improve dramatically ccsm3's already exible coupling facilities to enable research uses of the model not currently 91̽»¨ed. We report the progress in the first steps in this effort: the construction of Python bindings for the Model Coupling Toolkit, a key piece of third-party coupling middleware used in ccsm3, and a Python-based ccsm3 coupler (pypcl) application. We report prelim-inary performance results for this new system, which we call pyccsm. We find pyccsm is significantly slower than its Fortran counterpart, and explain how pypcl's performance may be improved to 91̽»¨ production runs. We believe our results augur well for the use of Python in the top-level coupling and organisation of large parallel multiphysics and multiscale applications.