Automating Climate Science: Large Ensemble Simulations on the TeraGrid with the GriPhyN Virtual Data System

Authors:
Veronika Nefedova;Robert Jacob;Ian Foster;Zhengyu Liu;Yun Liu;Ewa Deelman;Gaurang Mehta;Mei-Hui Su;Karan Vahi
Affiliations:
Argonne National Laboratory;Argonne National Laboratory;Argonne National Laboratory/ University of Chicago, USA;University of Wisconsin-Madison, USA;University of Wisconsin-Madison, USA;University of Southern California, USA;University of Southern California, USA;University of Southern California, USA;University of Southern California, USA
Venue:
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
Year:
2006

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Abstract

Ensemble simulations are a promising technique for identifying the signal of atmospheric response to extra-tropical sea surface temperature variability with high statistical significance. The basic idea is to perform multiple simulations from slightly different initial conditions and then to study the average signal of the ensemble. A significant obstacle to performing such ensemble simulations is the bookkeeping required to prepare, execute, and track the progress of hundreds of different computations. We describe an ensemble simulation experiment in which the Fast Ocean Atmosphere Model was run on the U.S. TeraGrid. In this experiment, we used the GriPhyN Virtual Data System to manage our ensemble simulations and their execution on distributed resources, achieving dramatic (order-of-magnitude) reductions in turnaround time relative to previous manual experiments.