Applying Scientific Workflow to ESM

  • Ufuk Utku TuruncogluEmail author
Part of the SpringerBriefs in Earth System Sciences book series (BRIEFSEARTHSYST)


As described in the previous section, a typical ESM application manages a series of different tasks, such as configuration, the building and running of the model on various computing resources, and the pre- and post-processing of the input data and model results, and, finally, the visualization of the results. Now-a-days, there are additional tasks concerned with the gathering of metadata about the run environment used, about the model itself and about the input and output data used in a particular run. Due to the complexity of the processes and the multi-component nature of the earth system models used, each of these tasks requires different levels of expertise and attention. If not supported well, the intricacies of these processes may prevent researchers from focusing on scientific issues, and may make it difficult, or even impossible, to undertake some earth system science problems.


Configuration File Earth System Model Provenance Information Earth System Science CCSM Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Altintas I, Barney O, Jaeger-Frank E (2006) Provenance collection support in the kepler scientific workflow system, Provenance and Annotation of Data, pp 118–132. doi:10.1007/11890850_14.
  2. Bavoil L, Callahan SP, Scheidegger CE, Vo HT, Crossno P, Silva CT, Freire J (2005) Vistrails: enabling interactive multiple-view visualizations. In: IEEE Visualization, IEEE Computer Society 18Google Scholar
  3. Bowers S, Ascher B (2005) Actor-oriented design of scientific workflows. In: In 24st International conference on conceptual modeling, Springer, pp 369–384Google Scholar
  4. Cao B, Plale B, Subramanian G, Robertson Ed, Simmhan Y (2009) Provenance Information Model of Karma Version 3. In: Proceedings of the 2009 Congress on Services-I. IEEE Computer Society, Washington, pp 348–351. doi: 10.1109/SERVICES-I.2009.54.
  5. Collins N, Theurich G, Deluca C, Suarez M, Trayanov A, Balaji V, Li P, Yang W, Hill C, Da Silva A (2005) Design and implementation of components in the earth system modeling framework. Int J High Perform Comput Appl 19(3):341–350. doi:  10.1177/1094342005056120 Google Scholar
  6. Eker J, Janneck J, Lee EA, Liu J, Liu X, Ludvig J, Sachs S, Xiong Y (2003) Taming heterogeneity—the ptolemy approach. Proceedings of the IEEE 91(1):127–144CrossRefGoogle Scholar
  7. Frew J, Metzger D, Slaughter P (2008) Automatic capture and reconstruction of computational provenance. Concurr Comput: Pract Exper 20:485–496. doi:10.1002/cpe.1247.
  8. Hill C, DeLuca C, Balaji V, Suarez M, da Silva A (2004) The architecture of the earth system modeling framework. Comput Sci Eng 6(1):18–28. doi: Google Scholar
  9. Larson J, Jacob R, Ong E (2005) The model coupling toolkit: a new fortran90 toolkit for building multiphysics parallel coupled models. Int J High Perform Comput Appl 19(3):277–292. doi: http://10.1177/1094342005056115 Google Scholar
  10. Lee EA, Neuendorffer S (2000) Moml-a modeling markup language in xml-version 0.4. Tech. Rep. UCB/ERL M00/12, EECS Department, University of California, Berkeley.
  11. Ludäscher B, Altintas I, Berkley C, Higgins D, Jaeger E, Jones M, Lee EA, Tao J, Zhao Y (2005) Scientific workflow management and the kepler system. Concurr Comput Pract Exper 18(10):1039–1065Google Scholar
  12. Majithia S, Shields MS, Taylor IJ, Wang I (2004) Triana: a graphical web service composition and execution toolkit. In: ICWS, IEEE Computer Society, pp 514Google Scholar
  13. Muniswamy-Reddy K, Holland DA, Braun U, Seltzer M (2006) Provenance-aware storage systems. In: Proceedings of the annual conference on USENIX ’06 Annual Technical Conference. USENIX Association, Berkelay, p 4.
  14. Oinn T, Addis M, Ferris J, Marvin D, Senger M, Greenwood M, Carver T, Glover K, Pocock MR, Wipat A, Li P (2004) Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics 20(17):3045–3054 URL Scholar
  15. Plale B, Gannon D, Brotzge J, Droegemeier K, Kurose JF, McLaughlin D, Wilhelmson R, Graves SJ, Ramamurthy M, Clark RD, Yalda S, Reed DA, Joseph E, Chandrasekar V (2006) Casa and lead: adaptive cyberinfrastructure for real-time multiscale weather forecasting. IEEE Computer 39(11):56–64CrossRefGoogle Scholar
  16. Podhorszki N, Klasky S (2008) Workflows in a secure environment. Distributed and Parallel Systems pp 143–153. doi: 10.1007/978-0-387-79448-8_13
  17. Turuncoglu UU, Murphy S, DeLuca C, Dalfes N (2011) A scientific workflow environment for earth system related studies. Computers & Geosciences 37(7):943–952. doi: 10.1016/j.cageo.2010.11.013.

Copyright information

© The Author(s) 2012

Authors and Affiliations

  1. 1.Istanbul Technical UniversityIstanbulTurkey

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