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Journal of Science Policy & Governance | Volume 17, Issue 02 | October 12, 2020

Policy Memo: The Impact of Emerging 5G Technology on U.S. Weather Prediction​

Sarah E. Benish (1,2)*, Graham H. Reid (1,3), Abhinav Deshpande (1,3), Shantam Ravan (1,3), Rachel Lamb (1,4)*
  1. Graduate Science Policy at the University of Maryland (GSP at UMD)
  2. University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD
  3. University of Maryland, Department of Physics, College Park, MD
  4. University of Maryland, Department of Geographical Sciences, College Park, MD
*Indicates equal contributions
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https://doi.org/10.38126/JSPG170203
Keywords: weather; 5G; forecasting; prediction; satellites; remote sensing; radio bands
Executive Summary: Fifth generation (5G) wireless networks promise to provide faster and more expansive data connectivity, exceeding thresholds from previous fourth generation (4G) technology. The deployment of 5G infrastructure requires allocating additional frequencies in radio bands at 24 gigahertz (GHz), potentially contaminating neighboring remote sensing bands used for weather forecasting and prediction. The current U.S. out-of-band emissions limit at 24 GHz of -20 dBW per 200 MHz is projected to degrade meteorological forecast accuracy by up to 30%, reducing the hurricane forecast lead time by 2 to 3 days, and endangering thousands of additional lives. Under the Weather Research and Forecasting Innovation Act of 2017 (Pub.L 115-25), the National Oceanic and Atmospheric Administration (NOAA) must develop more accurate and timely severe weather forecasts in order to protect life and property and reduce economic risk; however, the potential out-of-band interference from the roll out of 5G threatens this aim. Given U.S. economic reliance on accurate weather prediction (estimated to be in the trillions of dollars), we propose that Congress mandate stricter noise restrictions to adequately meet requirements of the Pub.L 115-25, while minimizing disruption to 5G deployment. 

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Sarah Benish is a Ph.D. candidate at the University of Maryland in the Department of Atmospheric and Oceanic Science studying air pollutants and greenhouse gases from an airborne field campaign in the North China Plain. She is a founding member and Vice-President of Graduate Science Policy at the University of Maryland. Sarah earned a BS in Biology and Environmental Studies with a certificate in Global Health from the University of Wisconsin-Madison.
 
Rachel Lamb is a Ph.D. candidate in the Department of Geographical Sciences at the University of Maryland, College Park (UMD). In partnership with NASA’s Carbon Monitoring System, Rachel is working with state governments to better include land-based carbon in their climate change mitigation planning and activities. She has served in multiple leadership capacities on campus including as the Vice President of Government Affairs for Graduate Student Government, and founding member and treasurer of Graduate Science Policy at UMD. Rachel also earned Masters degrees in Public Policy, and in Sustainable Development and Conservation Biology from UMD, as well as a BS in Environmental Studies and BA in International Relations from Wheaton College (IL).
 
Abhinav Deshpande is a Ph.D. candidate at the University of Maryland in the Department of Physics. His research interests are at the intersection of quantum computer science and many-body physics. He was previously at the Indian Institute of Technology, Kanpur, where he obtained an integrated bachelor’s and master’s degree in physics.
 
Graham Reid is a Ph.D. candidate in the Physics Department at the University of Maryland where he works in atomic physics experiment. His research uses ultracold atoms as a model to study transport in disordered quantum systems.
 
Shantam Ravan is a Ph.D candidate in the Physics Department at the University of Maryland. He currently works on studying nitrogen vacancies in diamond for use in high-resolution nanoscale sensing, and as a model system for driven many-body interacting quantum systems. He earned a BS in Electrical Engineering and Engineering Physics from the University of Michigan.
 
Acknowledgements
The authors would like to thank Dr. Adria Schwarber and Dr. Yuhan (Douglas) Rao for their review of and comments on our manuscript. We would also like to thank Aditi Dubey and Liz Friedman, executive members of Graduate Science Policy at University of Maryland, for their feedback on earlier drafts.
DISCLAIMER: The findings and conclusions published herein are solely attributed to the author and not necessarily endorsed or adopted by the Journal of Science Policy and Governance. Articles are distributed in compliance with copyright and trademark agreements.

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