The Evolving Role of Humans in Weather Prediction and Communication

Author:

Stuart Neil A.1,Hartfield Gail2,Schultz David M.3,Wilson Katie4,West Gregory5,Hoffman Robert6,Lackmann Gary7,Brooks Harold8,Roebber Paul9,Bals-Elsholz Teresa10,Obermeier Holly11,Judt Falko12,Market Patrick13,Nietfeld Daniel14,Telfeyan Bruce15,DePodwin Dan16,Fries Jeffrey17,Abrams Elliot16,Shields Jerry18

Affiliation:

1. NOAA/National Weather Service, Albany, New York;

2. NOAA/National Weather Service, Raleigh, North Carolina;

3. Centre for Atmospheric Science, Department of Earth and Environmental Sciences, and Centre for Crisis Studies and Mitigation, University of Manchester, Manchester, United Kingdom;

4. Cooperative Institute for Severe and High-Impact Weather Research and Operations, University of Oklahoma, and NOAA/OAR/NSSL, Norman, Oklahoma;

5. BC Hydro, Burnaby, British Columbia, Canada;

6. Florida Institute for Human and Machine Cognition, Pensacola, Florida;

7. North Carolina State University, Raleigh, North Carolina;

8. National Severe Storms Laboratory, and University of Oklahoma, Norman, Oklahoma;

9. University of Wisconsin–Milwaukee, Milwaukee, Wisconsin;

10. Department of Geography and Meteorology, Valparaiso University, Valparaiso, Indiana;

11. Cooperative Institute for Severe and High-Impact Weather Research and Operations, University of Oklahoma, Norman, Oklahoma;

12. Mesoscale and Microscale Meteorology Laboratory, NCAR, Boulder, Colorado;

13. University of Missouri, Columbia, Missouri;

14. NOAA/OAR/ESRL/GSL, Boulder, Colorado;

15. 557th Weather Wing, Offutt AFB, Nebraska;

16. AccuWeather, State College, Pennsylvania;

17. Operations Standards and Tactics, 1st Weather Group (ACC), Offutt AFB, Nebraska;

18. Ontario Ministry of Natural Resources and Forestry, Peterborough, Ontario, Canada

Abstract

Abstract A series of webinars and panel discussions were conducted on the topic of the evolving role of humans in weather prediction and communication, in recognition of the 100th anniversary of the founding of the AMS. One main theme that arose was the inevitability that new tools using artificial intelligence will improve data analysis, forecasting, and communication. We discussed what tools are being created, how they are being created, and how the tools will potentially affect various duties for operational meteorologists in multiple sectors of the profession. Even as artificial intelligence increases automation, humans will remain a vital part of the forecast process as that process changes over time. Additionally, both university training and professional development must be revised to accommodate the evolving forecasting process, including addressing the need for computing and data skills (including artificial intelligence and visualization), probabilistic and ensemble forecasting, decision support, and communication skills. These changing skill sets necessitate that both the U.S. Government’s Meteorologist General Schedule 1340 requirements and the AMS standards for a bachelor’s degree need to be revised. Seven recommendations are presented for student and forecaster preparation and career planning, highlighting the need for students and operational meteorologists to be flexible lifelong learners, acquire new skills, and be engaged in the changes to forecast technology in order to best serve the user community throughout their careers. The article closes with our vision for the ways that humans can maintain an essential role in weather prediction and communication, highlighting the interdependent relationship between computers and humans.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference118 articles.

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2. Alexander, C. , and Coauthors , 2020: Rapid Refresh (RAP) and High Resolution Rapid Refresh (HRRR) model development. 26th Conf. on Numerical Weather Prediction, Boston, MA, Amer. Meteor. Soc., 8A.1, https://ams.confex.com/ams/2020Annual/webprogram/Paper370205.html.

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