Articles | Volume 8, issue 7
https://doi.org/10.5194/gmd-8-2067-2015
https://doi.org/10.5194/gmd-8-2067-2015
Development and technical paper
 | 
13 Jul 2015
Development and technical paper |  | 13 Jul 2015

Experiences with distributed computing for meteorological applications: grid computing and cloud computing

F. Oesterle, S. Ostermann, R. Prodan, and G. J. Mayr

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Cited articles

Allcock, B., Bester, J., Bresnahan, J., Chervenak, A. L., Foster, I. T., Kesselman, C., Meder, S., Nefedova, V., Quesnel, D., and Tuecke, S.: Data management and transfer in high-performance computational Grid environments, Parallel Comput., 28, 749–771, 2002.
Barstad, I. and Schüller, F.: An extension of Smith's linear theory of orographic precipitation: introduction of vertical layers, J. Atmos. Sci., 68, 2695–2709, 2011.
Berger, M., Zangerl, T., and Fahringer, T.: Analysis of overhead and waiting time in the EGEE production Grid, in: Proceedings of the Cracow Grid Workshop, 2008, 287–294, 2009.
Berriman, G. B., Deelman, E., Juve, G., Rynge, M., and Vöckler, J.-S.: The application of cloud computing to scientific workflows: a study of cost and performance, Philos. T. R. Soc. A., 371, 20120066, https://doi.org/10.1098/rsta.2012.0066, 2013.
Blanco, C., Cofino, A. S., and Fernandez-Quiruelas, V.: WRF4SG: a scientific gateway for climate experiment workflows, Geophys. Res. Abstr., EGU2013-11535, EGU General Assembly 2013, Vienna, Austria, 2013.
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Short summary
Three practical meteorological applications with different characteristics highlight the core computer science aspects and applicability of distributed computing to meteorology. Presenting cloud and grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts.