RT Journal Article
T1 Probabilistic tsunami forecasting for early warning
A1 Selva, Jacopo
A1 Lorito, Stefano
A1 Volpe, Manuela
A1 Romano, Fabrizio
A1 Tonini, Roberto
A1 Perfetti, Paolo
A1 Bernardi, Fabrizio
A1 Taroni, Matteo
A1 Scala, Antonio
A1 Babeyko, Andrey
A1 Lovholt, Finn
A1 Gibbons, Steven
A1 Macías, Jorge
A1 Castro, Manuel Jesús
A1 González-Vida, José Manuel
A1 Sánchez-Linares, Carlos
A1 Bayraktar, Hafize Basak
A1 Basili, Roberto
A1 Maesano, Francisco Emanuele
A1 Tiberti, Mara
A1 Mele, Francesco
A1 Piatanesi, Alessandro
A1 Amato, Alessandro
K1 Maremotos
AB Tsunami warning centres face the challenging task of rapidly forecasting tsunami threat immediately after an earthquake, when there is high uncertainty due to data deficiency. Here we introduce Probabilistic Tsunami Forecasting (PTF) for tsunami early warning. PTF expli- citly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs- false-alarms. Impact forecasts and resulting recommendations become progressively less uncertain as new data become available. Here we report an implementation for near-source early warning and test it systematically by hindcasting the great 2010 M8.8 Maule (Chile) and the well-studied 2003 M6.8 Zemmouri-Boumerdes (Algeria) tsunamis, as well as all the Mediterranean earthquakes that triggered alert messages at the Italian Tsunami Warning Centre since its inception in 2015, demonstrating forecasting accuracy over a wide range of magnitudes and earthquake types.
PB Springer Nature
YR 2021
FD 2021-09-28
LK https://hdl.handle.net/10630/32889
UL https://hdl.handle.net/10630/32889
LA eng
NO Selva, J., Lorito, S., Volpe, M. et al. Probabilistic tsunami forecasting for early warning. Nat Commun 12, 5677 (2021). https://doi.org/10.1038/s41467-021-25815-w
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 4 mar 2026