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Spatial and temporal coverage of a cargo-ship GNSS network to detect tsunamis

Authors

Thomas,  Bruce
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Foster,  James
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Louartani,  Tasnîme
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Roger,  Jean
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Thomas, B., Foster, J., Louartani, T., Roger, J. (2023): Spatial and temporal coverage of a cargo-ship GNSS network to detect tsunamis, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3624


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020918
Abstract
Recent tsunamis demonstrate the urgent need for more densely spaced observations and direct measurements from the oceans. Most of the existing observing capacity is located on land or close to the shore, and often sparse (seismic network, land-based GNSS, tide-gauges and DART array), limiting our ability to predict, detect and respond to tsunamis. We propose a network of ships with GNSS systems as a way to fill this geodetic observation gap in the ocean by tracking changes in sea-surface height, and detecting even small, ~10 cm amplitude tsunamis of different origins. One year of navigation data from the commercial shipping fleet is used to generate statistical coverage maps of large ships for different epochs in the Pacific region which are overlapped with regions source of tsunamis and impacted by tsunamis. Some first results describe what a cargo-ship network might experience in terms of tsunami travel time and tsunami predicted amplitudes based on several tsunami models calculated over the Pacific. They clearly demonstrate that commercial shipping lines provide an excellent temporal and spatial coverage of the ocean globally. A focus on different regions indicates that the highest density of ships is near coastlines, and testing different tsunami origins helps understand more precisely how this network could improve regional early warning. By exploring the geographic relationship between tsunami sources, travel times and amplitudes with the ships locations, the discussion seeks to determine the ability of a defined ship network to provide effective warnings for the communities at risk and improve hazard mitigations.