HR: 0800h
AN: SF31A-0714    [Abstracts]
TI: Flexible Environments for Grand-Challenge Simulation in Climate Science
AU: Pierrehumbert, R
EM: rtp1@geosci.uchicago.edu
AF: Department of the Geophysical Sciences, Universtiy of Chicago, 5734 S. Ellis Ave., Chicago, IL 60615 United States
AU: Tobis, M
EM: tobis@geosci.uchicago.edu
AF: Department of the Geophysical Sciences, Universtiy of Chicago, 5734 S. Ellis Ave., Chicago, IL 60615 United States
AU: Lin, J
EM: jlin@geosci.uchicago.edu
AF: Department of the Geophysical Sciences, Universtiy of Chicago, 5734 S. Ellis Ave., Chicago, IL 60615 United States
AU: Dieterich, C
EM: cdieterich@geosci.uchicago.edu
AF: Department of the Geophysical Sciences, Universtiy of Chicago, 5734 S. Ellis Ave., Chicago, IL 60615 United States
AU: * Caballero, R
EM: rca@geosci.uchicago.edu
AF: Department of the Geophysical Sciences, Universtiy of Chicago, 5734 S. Ellis Ave., Chicago, IL 60615 United States
AB: Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability.
DE: 3394 Instruments and techniques
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting