Meteotsunami Forecasting and Warning System for the Laurentian Great Lakes:

New Paradigm for Big Data Challenges and Analytics

Dates: June 19-21, 2017
Leads: Chin Wu, University of Wisconsin-MadisonDave Kristovich, University of Illinois at Urbana ChampaignPhilip Chu, NOAA GLERLEric Anderson, NOAA GLERLSteven Ruberg, NOAA GLERLGreg Mann, NOAA NWSYu-Hen Hu, University of Wisconsin-MadisonVictoria Campbell-Arvai, University of Michigan
GLERL Research Program: Integrated Physical and Ecological Modeling and Forecasting

Lake Michigan waves at South Haven lighthouse. Credit: Tom Gill

Description: Meteotsunamis are similar to earthquake-generated tsunamis, but are caused by meteorological events such as rapid changes in barometric pressure often associated with fast moving weather systems. Although many meteotsunamis are too small to notice, large meteotsunamis can have devastating coastal impacts (damaging waves, flooding, strong currents) that cause significant damage, injury and death. Meteotsunamis are frequently observed in the Great Lakes, averaging 106 events per year (Bechle et. al., 2016). Examples of destructive Great Lakes meteotsunamis include:

  • In 1929, a retreating 6 meter wave pulled ten people to their deaths at in Lake Michigan at Grand Haven, MI [Grand Haven Daily Tribune 1929].
  • In 1954, a 3 meter wave hit Chicago and swept many fishermen off a pier, killing seven.
  • In 1998, a strong meteotsunami in Lake Michigan capsized a tug boat at the White Lake, MI harbor [NOAA 1998].
  • On July 4, 2003 at Sawyer, MI, seven people drowned in an incident initially attributed to rip currents, though the water level records indicated a moderate meteotsunami occurred around the time of the drownings.
  • Anderson et al. (2015) documented recent meteotsunamis in Lake Erie swept 3 swimmers one kilometer offshore.
  • A so-called tidal wave (meteotsunami) in Lake Superior (2014) caused flooding, interrupting shipping operations and prompting residents to be evacuated.

Furthermore, sudden and unexpected water level drawdown due to meteotsunamis could cause dry intakes, leading to insufficient water supply and endangering the safety of nuclear power plants in the Great Lakes. While the hazards that meteotsunamis pose the Great Lakes and U.S. oceanic coastlines has been recognized, a reliable warning system for forecasting meteotsunamis has yet to be developed.

Meteotsunami forecasting has been hindered by challenges related to big data features associated with rapidly varied atmospheric and hydrodynamic conditions. The four V’s, defined by the NSF/JST Big Data in Disasters Workshop [Pu and Kitsuregawa 2013], are (i) velocity – the speed at which data is generated and processed to meet demands; (ii) veracity – the quality of the data in terms of accuracy, uncertainty, and reliability; (iii) volume – the scale of data and the implications of scale on how it can be processed; and (iv) variety – the heterogeneity of data from various sources with diverse formats, resolutions, and semantics.

Goals: The overall goal of the summit is to construct a framework for developing a real-time meteotsunami warning system in the Laurentian Great Lakes that can meet weather forecast requirements, thus reducing risks due to coastal flooding, preventing swimmer drowning, and increasing the safety of nuclear power plant operations.

2018 Ocean Science Meeting:

Media Resources

  • FAQs and Additional Resources on Meteotsunamis (PDF)
  • Ocean Sciences Press Conference Slide Deck (PDF)
  • Ocean Sciences Press Conference Recording (Video)
  • Southern Lake Michigan Wave Animation (GIF)
  • Lake Michigan Storm Radar (GIF)
  • The Weather Channel News; There’s a Type of Tsunami on the Great Lakes You May Not Have Heard of Before, 2/13/2018 (Article)


2017 Meteotsunami Summit:

2017 Participants

Atmospheric Science and Meteorology  

  • David King for David Kristovich, University of Illinois at Urbana-Champaign & Illinois State Water Survey
  • Greg Mann, NOAA, National Weather Service (NWS), Weather Forecast Office, Detroit/Pontiac, MI
  • Jay Hobgood, Ohio State University, Geography Department Atmospheric Sciences Program
  • Robert LaPlante, NOAA, NWS, Weather Forecast Office, Cleveland, OH
  • William W. Schultz, University of Michigan

Big-Data Computer Science & Advanced Technology and Observing Systems

  • Kelli Paige, Great Lakes Observing System (GLOS)
  • Qunying Huang, University of Wisconsin-Madison
  • Philip Chu, NOAA, Great Lakes Environmental Research Laboratory (GLERL)
  • Steven Ruberg, NOAA, GLERL
  • Yu-Hen Hu, University of Wisconsin-Madison

Communication, Warning, and Social Science

  • Bob Dukesherer, NOAA, NWS, Grand Rapids, MI
  • Kirk Lombardy, NOAA, NWS, Weather Forecast Office, Cleveland, OH
  • Victoria Campbell-Arvai, University of Michigan

Dynamics of Coastal and Physical Oceanography

  • David Schwab, University of Michigan, Graham Sustainability Institute
  • Dmitry Beletsky, University of Michigan, CIGLR
  • Eric Anderson, NOAA, GLERL
  • Lewis Kozlosky, NOAA, NWS, Tsunami Physical Science, Marine, Tropical and Tsunami Services Branch
  • Marie Eble, NOAA, Pacific Marine Environmental Lab (PMEL), Center of Tsunamis Research
  • Qianqian Liu, Grand Valley State University

Experts in Meteotsunamis

  • Alexander Rabinovich, Institute of Ocean Sciences, Canada and Russian Academy of Sciences, Moscow
  • Jadranka Šepić, Institute of Oceanography and Fisheries, Split, Croatia
  • Adam Bechle, Wisconsin Sea Grant Institute
  • Alvaro Linares, UW-Madison
  • Chin Wu, University of Wisconsin-Madison

News Coverage