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An exploration of National Weather Service daily forecasts using R Shiny

Author

Listed:
  • Dooti Roy

    (Boehringer Ingelheim Pharmaceuticals Inc.)

  • Gregory Vaughan

    (Bentley University)

  • Jianan Hui

    (Boehringer Ingelheim Pharmaceuticals Inc.)

  • Junxian Geng

    (Boehringer Ingelheim Pharmaceuticals Inc.)

Abstract

Weather forecasts often affect daily lives of billions of people globally. Accurate forecasts can help combat and effectively mitigate damage caused by extreme weather. Alternatively, faulty forecasts can consequently lead to unnecessary financial investments and a waste of resources. Our work explores what is the extent of variability in errors of the National Weather Service predictions as observed in 113 cities in the United States between July 1, 2014 and September 1, 2017 and attempts to model the distribution of errors. Simultaneously, we deliver an interactive tool for future researchers to explore the actual and forecast weather data as well as expose hidden patterns in the data.

Suggested Citation

  • Dooti Roy & Gregory Vaughan & Jianan Hui & Junxian Geng, 2023. "An exploration of National Weather Service daily forecasts using R Shiny," Computational Statistics, Springer, vol. 38(3), pages 1173-1191, September.
    • Handle: RePEc:spr:compst:v:38:y:2023:i:3:d:10.1007_s00180-023-01341-9
    DOI: 10.1007/s00180-023-01341-9
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    References listed on IDEAS

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    1. Rob J. Hyndman, 2006. "Another Look at Forecast Accuracy Metrics for Intermittent Demand," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 4, pages 43-46, June.
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    Cited by:

    1. Mine Cetinkaya-Rundel & Wendy Martinez, 2023. "The 2018 data challenge expo of the American statistical association," Computational Statistics, Springer, vol. 38(3), pages 1117-1122, September.

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