Articles | Volume 9, issue 7
https://doi.org/10.5194/gmd-9-2293-2016
https://doi.org/10.5194/gmd-9-2293-2016
Development and technical paper
 | 
05 Jul 2016
Development and technical paper |  | 05 Jul 2016

Performance evaluation of a throughput-aware framework for ensemble data assimilation: the case of NICAM-LETKF

Hisashi Yashiro, Koji Terasaki, Takemasa Miyoshi, and Hirofumi Tomita

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Cited articles

Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., Strow, L. L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems, IEEE T. Geosci. Remote Sens., 41, 253–264, https://doi.org/10.1109/TGRS.2002.808356, 2003.
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical aspects, https://doi.org/10.1175/1520-0493(2001)129<0420:ASWTET>2.0.CO;2, 2001.
Clayton, A. M., Lorenc, A. C., and Barker, D. M.: Operational implementation of a hybrid ensemble/4D-Var global data assimilation system at the Met Office, Q. J. Roy. Meteor. Soc., 139, 1445–1461, https://doi.org/10.1002/qj.2054, 2013.
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Dennis, J. M., Vertenstein, M., Worley, P. H., Mirin, A. A., Craig, A. P., Jacob, R., and Mickelson, S.: Computational performance of ultra-high-resolution capability in the Community Earth System Model, Int. J. High Perform. C., 26, 5–16, https://doi.org/10.1177/1094342012436965, 2012.
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We propose the design and implementation of an ensemble data assimilation framework for weather prediction at a high resolution and with a large ensemble size. We consider the deployment of this framework on the data throughput of file I/O and multi-node communication. With regard to high-performance computing systems, where data throughput performance increases at a slower rate than computational performance, our new framework promises drastic reduction of total execution time.
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