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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nefedova, V. Jacob, R. Foster, I. Zhengyu Liu Yun Liu Deelman, E. Mehta, G. Mei-Hui Su Vahi, K. |
| Copyright Year | 2006 |
| Description | Author affiliation: Argonne National Laboratory (Nefedova, V.; Jacob, R.) || Argonne National Laboratory; University of Chicago, USA (Foster, I.) || University of Wisconsin-Madison, USA (Zhengyu Liu; Yun Liu) || University of Southern California, USA (Deelman, E.; Mehta, G.; Mei-Hui Su; Vahi, K.) |
| 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. |
| Starting Page | 32 |
| Ending Page | 32 |
| File Size | 345356 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769527345 |
| DOI | 10.1109/E-SCIENCE.2006.261116 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-04 |
| Publisher Place | The Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Sea surface Automation Atmospheric modeling Computational modeling Computer simulation Laboratories Atmosphere Signal processing Data systems Ocean temperature |
| Content Type | Text |
| Resource Type | Article |
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