Future Perspectives

  • Luca Bonaventura
Part of the SpringerBriefs in Earth System Sciences book series (BRIEFSEARTHSYST, volume 1)


We have reviewed in this Brief the state of the art and the current development directions of the numerical methods at the core of Earth System Models. It is easy to see that, over the last 20 years, a much wider range of techniques has been proven to be applicable to oceanic and atmospheric flows than in the earlier stages of climate model development. The impressive increase in computational power is certainly one of the driving forces behind this change. It is very likely to yield in the near future models based on numerical methods that would not have been considered practically useful just a few years ago. Furthermore, massively parallel architectures have become the effective standard in supercomputing, thus imposing good scalability and strong data locality as essential requirements for any model to be applied extensively in this context.


  1. Dongarra J, Beckman P, Moore T, Aerts P, Aloisio G, Andre JC, Barkai D, Berthou JY, Boku T, Braunschweig B, Cappello F, Chapman B, Chi X, Choudhary A, Dosanjh S, Dunning T, Fiore S, Geist A, Gropp B, Harrison R, Hereld M, Heroux M, Hoisie A, Hotta K, Ishikawa Y, Jin Z, Johnson F, Kale S, Kenway R, Keyes D, Kramer B, Labarta J, Lichnewsky A, Lippert T, Lucas B, Maccabe B, Matsuoka S, Messina P, Michielse P, Mohr B, Mueller M, Nagel W, Nakashima H, Papka ME, Reed D, Sato M, Seidel E, Shalf J, Skinner D, Snir M, Sterling T, Stevens R, Streitz F, Sugar B, Sumimoto S, Tang W, Taylor J, Thakur R, Trefethen A, Valero M, van der Steen A, Vetter J, Williams P, Wisniewski R, Yelick K (2011) The international exascale software roadmap. Int J High Perform Comput Appl ISSN 1094-3420 25(1):3–60Google Scholar
  2. Govett M, Tierney G, Middlecoff J, Henderson T (2009) Using graphical processing units (gpus) for next generation weather and climate models. Climate and Atmospheric Sciences (CAS) workshop, Sept 2009, Annecy, FranceGoogle Scholar
  3. Kothe DB (2007) Science prospects and benefits with exascale computing. Oak Ridge National Laboratory, Tennessee, National Center for Computational SciencesGoogle Scholar
  4. Michalakes J, Vachharajani M (2008) GPU acceleration of numerical weather prediction. Parallel Processing Letters 18(2):531–548Google Scholar
  5. Takahashi K, Peng X, Onishi R, Ohdaira M, Goto K, Fuchigami H, Sugimura T (2007) Multi-scale coupled atmosphere-ocean gcn and simulations. In: Mozdzynski G (ed) Proceedings of the twelth ECMWF workshop use of high performance computing in meteorology, Reading, UK, pp 36–54Google Scholar

Copyright information

© The Author(s) 2012

Authors and Affiliations

  1. 1.MOX-Dipartimento di MatematicaPolitecnico di MilanoMilanoItaly

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