Advertisement

Storm Prediction Research and its Application to the Oil/Gas Industry

  • Lizzie S. R. Froude
  • Robert J. Gurney
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Abstract

The accurate prediction of storms is vital to the oil and gas sector for the management of their operations. An overview of research exploring the prediction of storms by ensemble prediction systems is presented and its application to the oil and gas sector is discussed. The analysis method used requires larger amounts of data storage and computer processing time than other more conventional analysis methods. To overcome these difficulties eScience techniques have been utilised. These techniques potentially have applications to the oil and gas sector to help incorporate environmental data into their information systems.

Keywords

Storm tracks ensemble prediction system eScience oil and gas industry 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bengtsson, L., Hodges, K. I. and Roeckner, E. (2006) Storm tracks and climate change. Climate Dynamics. 19, 3518–3543.Google Scholar
  2. Bengtsson, L., Hodges, K. I. and Esch, M. (2007a) Tropical cyclones in a T159 resolution global climate model: Comparison with observations and re-analyses. Tellus. 59A, 396–416.Google Scholar
  3. Bengtsson, L., Hodges, K. I., Esch, M., Keenlyside, N., Kornblueh, L., Luo, J.-J. and Yamagata, T. (2007b) How may tropical cyclones change in a warmer climate? Tellus. 59A, 539–561.Google Scholar
  4. Bengtsson, L., Hodges, K. I. and Keenlyside, N. (2008) Will extratropical storms intensity in a warmer climate? J. Climate. (accepted).Google Scholar
  5. Buizza, R. and Palmer, T. N. (1995) The singular-vector structure of the atmospheric global circulation. J. Atmos. Sci. 52, 1434–1456.CrossRefGoogle Scholar
  6. Buizza, R., Bidlot, J.-R., Wedi, N., Fuentes, M., Hamrud, M., Holt, G. and Vitart, F. (2007) The new ECMWF VAREPS (Variable Resolution Ensemble Prediction System). Quart. J. Roy. Meteorol. Soc. 133, 681–695.CrossRefGoogle Scholar
  7. Froude, L. S. R. (2008) Storm tracking with remote data and distributed computing. Comput. Geosciences. 34, 1621–1630.CrossRefGoogle Scholar
  8. Froude, L. S. R. (2009) Regional differences in the prediction of extratropical cyclones by the ECMWF ensemble prediction system. Mon. Weather Rev. (accepted).Google Scholar
  9. Froude, L. S. R., Bengtsson, L. and Hodges, K. I. (2007a) The predictability of extratropical storm tracks and the sensitivity of their prediction to the observing system. Mon. Weather Rev. 135, 315–333.CrossRefGoogle Scholar
  10. Froude, L. S. R., Bengtsson, L. and Hodges, K. I. (2007b) The prediction of extratropical storm tracks by the ECMWF and NCEP ensemble prediction systems. Mon. Weather Rev. 135, 2545–2567.CrossRefGoogle Scholar
  11. Hall, M. (1999) Servlets and Java Server Pages (JSP) 1.0: A tutorial. See http://www.apl. jhu.edu/~hall/java/Servlet-Tutorial/
  12. Hodges, K. I. (1995) Feature tracking on the unit sphere. Mon. Weather Rev. 123, 3458–3465.CrossRefGoogle Scholar
  13. Hodges, K. I. (1999) Adaptive constraints for feature tracking. Mon. Weather Rev. 127, 1362–1373.CrossRefGoogle Scholar
  14. Hoskins, B. J. and Hodges, K. I. (2002) New perspectives on northern hemisphere winter storm tracks. J. Atmos. Sci. 59, 1041–1061.CrossRefGoogle Scholar
  15. Hoskins, B. J. and Hodges, K. I. (2005) A new perspective on southern hemisphere storm tracks. J. Climate. 18, 4108–4129.CrossRefGoogle Scholar
  16. Kalnay, E., Kanamitsu, R. and Kistler, R. (1996) The NCEP/NCAR 40-year re-analysis project. Bull. Am. Meteorol. Soc. 74, 2317–2330.Google Scholar
  17. Leith, C. E. (1974) Theoretical skill of Monte Carlo forecasts. Mon. Weather Rev. 102, 409–418.CrossRefGoogle Scholar
  18. Lorenz, E. N. (1963) Deterministic nonperiodic flow. J. Atmos. Sci. 20, 130–141.CrossRefGoogle Scholar
  19. Molteni, F., Buizza, R., Palmer, T. N. and Petroliagis, T. (1996) The ECMWF ensemble prediction system: Methodology and validation. Quart. J. Roy. Meteor. Soc. 122, 73–119.CrossRefGoogle Scholar
  20. Thain, D., Tannenbaum, T. and Livny, M. (2005) Distributed computing in practice: The Condor experience. Concurr. Comput. Pract. Exp. 17, 323–356.CrossRefGoogle Scholar
  21. Toth, Z. and Kalnay, E. (1993) Ensemble forecasting at the NMC: the generation of perturbations. Bull. Am. Meteorol. Soc. 74, 2317–2330.CrossRefGoogle Scholar
  22. Toth, Z. and Kalnay, E. (1997) Ensemble forecasting at NCEP and the breeding method. Mon. Weather Rev. 125, 3297–3319.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Lizzie S. R. Froude
    • 1
  • Robert J. Gurney
    • 1
  1. 1.Environmental Systems Science Centre (ESSC)University of ReadingReadingUK

Personalised recommendations