EGU24-14892, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Enduser Driven and Impact-based Time Dependent Tsunami Early Warning (TiDeTEW) in Aotearoa New Zealand

Bill Fry1, Christopher Mueller1, Chris Moore2, Emily Lane3, Jen Andrews1, Chris Zweck1, Aditya Gusman1, Sophia Tsang1, Emeline Wavelet4, Anna Kaiser1, Ciaran King1, Xiaoming Wang1, and Biljana Lukovic
Bill Fry et al.
  • 1( Te Pū Ao, GNS Science, Wellington, New Zealand
  • 2Pacific Marine Environmental Laboratory, Seattle, Washington, USA
  • 3National Institute of Water and Atmospheric Research, Wellington, New Zealand
  • 4University of Otago, Dunedin, New Zealand

Since the 1960s, tsunami early warning has, for the most part, been predicated on using earthquake characterisation as proxy information for tsunami generation. Shortcomings with this approach include large epistemic uncertainties in wave forecasts that typically preclude actionable impact-based forecasts. Fortunately, the tsunami early warning paradigm is shifting. Here we present a prototype next-generation tsunami early warning system implemented by the New Zealand RCET (Rapid Characterisation of Earthquakes and Tsunamis) programme that is currently operational on a best-endeavours basis in New Zealand. This system is based on 1) observational advances including the densification of deep-ocean tsunami meters, 2) scientific advances provided by direct tsunami inversion 3) ensemble and time-dependent forecasting and 4) co-creation with end users of impact-based forecasts products. We call this system TiDeTEW (Time Dependent Tsunami Early Warning)

Following the recent deployment of the 12-station NZ DART tsunamimeter array (Fry et al., 2020), New Zealand’s Tsunami Expert Panel (TEP) can now use direct observations of tsunamis to underpin time-dependent tsunami early warning forecasts. By using DART inversions and ensemble modelling, we reduce uncertainties in forecasts enough to generate actionable early warning products that provide information about the evolution of the threat prior to land arrival, analogous to weather forecasting of storm evolution. Our forecasting products are being improved through co-development with at risk coastal communities that are dominantly indigenous Māori. In past natural disasters, the social structure of Māori communities has proven to be a major advantage in response and incorporation of Māori values into decisions around risk tolerance of the early warning products guides our levels of forecast conservatism. Understanding the response structure in these communities and its strong reliance on marae (Māori communal meeting houses) is also guiding our product development.

In an aligned effort within the UNESCO Intergovernmental Oceanographic Commission (UNESCO-IOC), we have developed a risk-based approach to assess the efficacy of this tsunami early warning method. We quantify the relative number of tsunami sources for which data support at least 20 minutes of pre-impact warning time to vulnerable coastal populations. We further map the warning gaps to population density of exposed coastlines. We apply this scheme using the NZ DART network to better quantify domestic and Southwest Pacific risk and resilience gains delivered by NZ DART and further highlight existing gaps and opportunities, largely around local source tsunamis.

How to cite: Fry, B., Mueller, C., Moore, C., Lane, E., Andrews, J., Zweck, C., Gusman, A., Tsang, S., Wavelet, E., Kaiser, A., King, C., Wang, X., and Lukovic, B.: Enduser Driven and Impact-based Time Dependent Tsunami Early Warning (TiDeTEW) in Aotearoa New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14892,, 2024.