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Eric Floehr

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Eric Floehr is the founder and owner of ForecastWatch, a company that evaluates the accuracy of weather forecasts.[1][2]

Overview[edit]

Floehr created a program by utilizing Python that gathered online weather forecasts released by the AccuWeather, National Weather Service and The Weather Channel.[3][2] He founded Intellovations, and later ForecastWatch the system that monitors the quality and accuracy of weather forecasts for over 1,200 locations worldwide.[1][4]

In 2002, Floehr discovered Wet bias by collecting historical data of weather forecasts made by the National Weather Service, The Weather Channel, and AccuWeather for the United States, and collected the data on the website of ForecastWatch. Floehr found that the commercial forecasts were biased: they consistently predicted a higher probability of precipitation than actually occurred as compared to The National Weather Service forecasts who were unbiased.[5][6]

In 2018 author Michael Lewis cited Floehr's work in his book, The Fifth Risk, as “the closest thing to an authority on the relative accuracy of various weather forecasts.”[7]

Forbes, dubbed Floehr as the “J.D. Power of weather prediction.” in a publication in June 2019.[8]

Awards[edit]

Floehr received the Community Service Award (3rd Quarter 2017) for contributions to the Python Community including chairing the PyOhio conference, founding the Central Ohio Python User Group and serving as a resource for Python programmers in Columbus, OH.[9]

Education[edit]

Floehr received a B.Sc in Computer and Information Science from Ohio State University in 1993.[4]

Papers and research[edit]

  • Bickel, J & Floehr, Eric & Kim, Seong Dae. (2011). Comparing NWS PoP Forecasts to Third-Party Providers. Monthly Weather Review. 139. 3304-3321. 10.1175/2011MWR3525.1.[10]
  • Anbarci, Nejat & H. Boyd III, John & Lee, Jungmin & Floehr, Eric & Song, Joon Jin. (2011). Population and Income Sensitivity of Private and Public Weather Forecasting. Regional Science and Urban Economics. 41. 124-133. 10.1016/j.regsciurbeco.2010.11.001.[11]
  • Anbarci, Nejat & Floehr, Eric & Lee, Jungmin & Song, Joon Jin. (2019). Economic Bias of Weather Forecasting: A Spatial Modeling Approach.[12]

References[edit]

  1. 1.0 1.1 "Evaluating Weather Forecast Accuracy: An Interview with Eric Floehr - DZone Big Data". dzone.com. Retrieved 2019-04-10.
  2. 2.0 2.1 "Q&A: How data science improves weather forecasting (Includes interview)". www.digitaljournal.com. 2019-03-05. Retrieved 2020-11-07.
  3. "When you really need the best forecast, which app should you trust?". Washington Post. Retrieved 2019-12-04.
  4. 4.0 4.1 "Forecast Watch: The man who checks meteorologists' accuracy". www.bizjournals.com. Retrieved 2019-11-08.
  5. Silver, Nate (2012). The signal and the noise : why so many predictions fail--but some don't. New York: Penguin Press. ISBN 9781594204111. OCLC 780480483. Search this book on Amazon.com Logo.png
  6. Fahey, Mark (2016-08-25). "This weather app will give you the most accurate forecasts". www.cnbc.com. Retrieved 2020-12-15.
  7. Lewis, Michael (Michael M.). The fifth risk : undoing democracy. [London]. ISBN 9780241373545. OCLC 1056252597. Search this book on Amazon.com Logo.png
  8. Adams, Susan (June 2019). "The Real Cloud Wars: The $6 Billion Battle Over The Future Of Weather Forecasting". Forbes.
  9. Heaton, Christy (2017-11-25). "Python Software Foundation News: Eric Floehr, Community Service Award 3rd Quarter 2017 Recipient". Python Software Foundation News. Retrieved 2019-04-10.
  10. "Comparing NWS PoP Forecasts to Third-Party Providers".
  11. "Population and Income Sensitivity of Private and Public Weather Forecasting".
  12. "Economic Bias of Weather Forecasting: A Spacial Modeling Approach".


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