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Doing something about the weather


  • Regnier, Eva


Recent developments in weather forecasting have created the potential for the operations research and management science (OR/MS) community to have a tremendous impact in distilling weather information into valuable decision tools. Weather-sensitive applications include transport, electric utilities, agriculture, and public emergency management. This article surveys existing research and practice using OR/MS tools to integrate weather forecasts in decision-making. Because the conditions that created the potential for OR/MS contributions--in particular an explosion in the amount of relevant forecast data--are quite recent, the amount of existing OR/MS work is modest. This article also describes promising but unexplored research opportunities for the OR/MS community.

Suggested Citation

  • Regnier, Eva, 2008. "Doing something about the weather," Omega, Elsevier, vol. 36(1), pages 22-32, February.
  • Handle: RePEc:eee:jomega:v:36:y:2008:i:1:p:22-32

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    References listed on IDEAS

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    Cited by:

    1. repec:spr:annopr:v:264:y:2018:i:1:d:10.1007_s10479-017-2637-6 is not listed on IDEAS
    2. Chen, Shin-Guang, 2013. "Bayesian approach for optimal PV system sizing under climate change," Omega, Elsevier, vol. 41(2), pages 176-185.
    3. McLay, Laura A. & Boone, Edward L. & Brooks, J. Paul, 2012. "Analyzing the volume and nature of emergency medical calls during severe weather events using regression methodologies," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 55-66.
    4. Roopesh Ranjan & Tilmann Gneiting, 2010. "Combining probability forecasts," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 71-91, January.
    5. Souffriau, Wouter & Vansteenwegen, Pieter & Vanden Berghe, Greet & Van Oudheusden, Dirk, 2011. "The planning of cycle trips in the province of East Flanders," Omega, Elsevier, vol. 39(2), pages 209-213, April.
    6. Taylor, James W. & Snyder, Ralph D., 2012. "Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing," Omega, Elsevier, vol. 40(6), pages 748-757.
    7. Cao, Qing & Ewing, Bradley T. & Thompson, Mark A., 2012. "Forecasting wind speed with recurrent neural networks," European Journal of Operational Research, Elsevier, vol. 221(1), pages 148-154.
    8. Tilmann Gneiting & Larissa Stanberry & Eric Grimit & Leonhard Held & Nicholas Johnson, 2008. "Rejoinder on: Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 256-264, August.
    9. Frank Youhua Chen & Candace Arai Yano, 2010. "Improving Supply Chain Performance and Managing Risk Under Weather-Related Demand Uncertainty," Management Science, INFORMS, vol. 56(8), pages 1380-1397, August.
    10. Arora, Siddharth & Taylor, James W., 2016. "Forecasting electricity smart meter data using conditional kernel density estimation," Omega, Elsevier, vol. 59(PA), pages 47-59.
    11. Eva Regnier, 2008. "Public Evacuation Decisions and Hurricane Track Uncertainty," Management Science, INFORMS, vol. 54(1), pages 16-28, January.
    12. Kerkhove, L.-P. & Vanhoucke, M., 2017. "Optimised scheduling for weather sensitive offshore construction projects," Omega, Elsevier, vol. 66(PA), pages 58-78.


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