Tsunami detection using commercial cargo ships

Researchers at the University of Hawaiʻi at Mānoa School of Ocean and Earth Science and Technology (SOEST) have begun equipping commercial cargo ships with low-cost tsunami sensors to provide real-time early detection data as they move through the North Pacific. The researchers, funded by the National Oceanic and Atmospheric Administration, are partnering with Matson, Maersk Line and the World Ocean Council to equip 10 ships with real-time geodetic GPS systems and satellite communications to enable each vessel to act as a tide gauge and send data to SOEST to analyze for indications of a tsunami wave.

The network has the potential to  be a low-cost and widely spread complement to existing detection systems.

Sources: Huffington Post and University of Hawaii, December 2015.

Photo credit: Aushiker on Flickr.

Article in Huffington Post — ‘Scientists Cleverly Use Cargo Ships For New Tsunami Warning System’, Overview from University of Hawaii
http://www.huffingtonpost.com/entry/cargo-ships-tsunami-warning_5678b016e4b014efe0d69ad3, http://www.hawaii.edu/news/2015/12/16/novel-tsunami-detection-network-uses-navigation-systems-on-commercial-ships/?c

Are you sure you want to delete this "resource"?
This item will be deleted immediately. You cannot undo this action.

Related Resources

Video
28 Nov 2014
One of the research projects at the Zugspitze comes as a surprise to most visitors. Scientists from the German Aerospace Center (DLR) are working on GRIPS ,a device designed to improve tsunami early warning systems.The early warning system that Germa...
Tags: Video, Early Warning Systems, Tsunami
Report
22 Oct 2013
أفادت التقارير بأن عدد من لقوا حتفهم أو تضرروا من جراء الكوارث في عام 2012 بلغ أدنى مستوياته بالمقارنة مع أي من السنوات الأخرى خلال العقد ال...
Tags: Report, Early Warning Systems, Mobile Technology
Report
03 Sep 2020
This is the presentation by Andreas Schaffhauser on 30 September, 2020, at the CAP Implementation Workshop hosted by ITU as a video conference.
Tags: Report, Early Warning Systems