Created a forecasting model that includes a quantitative estimate of uncertainties, linking it to the definition of tsunami alert levels
Il Probabilistic Tsunami Forecasting (PTF) is the innovative procedure that allows, in real time, the determination of the tsunami alert level taking into account the inevitable uncertainty in the tsunami forecast. The new procedure, which could introduce a breakthrough in the management of tsunami warnings, was developed by an international research team coordinated by the National Institute of Geophysics and Volcanology (INGV) and has just been published in the study “Probabilistic tsunami forecasting for early warnings” in the scientific journal 'Nature Communications'.
“The PTF quantifies the probability of a tsunami of a given intensity occurring within a few minutes of the earthquake that may have generated it”, explains Jacopo Selva of the INGV Tsunami Alert Center (CAT-INGV) and first author of the article. The method developed by the researchers rigorously assesses for the first time the unavoidable degree of uncertainty in real-time tsunami forecasting. "This offers the possibility of linking the definition of the early warning level to the forecast of the intensity of the possible tsunami and the relative uncertainty, based on pre-established risk reduction criteria", adds Jacopo Selva.
“The forecasts are made by combining the earthquake parameters estimated in real time with those expected in the area in the long term and, finally, with millions of numerical simulations of the tsunami propagation, pre-calculated thanks to modern supercomputers”, adds Stefano Lorito, co-author of the study.
The research team applied the PTF, retrospectively, to several seismic events including the 8.8 magnitude earthquake that struck Maule, Chile in 2010, the Zemmouri-Boumerdes tsunami in Algeria, generated in 2003 by an magnitude 6.8, and the tsunami generated almost a year ago by the magnitude 7.0 earthquake that occurred near the Greek island of Samos. All the earthquakes located in the Mediterranean area that have activated the INGV CAT in recent years were also analysed. This made it possible to evaluate the accuracy of the forecasting model on a wide range of magnitudes and types of seismic event, from relatively small crustal earthquakes to larger events generated in subduction zones.
In order to be able to offer an adequate response in the event of an event to citizens residing in coastal areas exposed to the risk of flooding from tsunamis, it is essential to combine scientific evidence with local policy choices, so as to associate an alert level with a given probability , considering that each alert level, in turn, can correspond to certain coastal strips to be evacuated. The latter, in Italy, have been defined by ISPRA, INGV and DPC which are the components of the SiAM (National Alert System for Tsunamis Generated by Earthquakes). Indeed, both missed alarms and false alarms can generate significant socio-economic consequences. Since both cases are due to the uncertainty in the prediction of calamitous events, the PTF proposes to include the uncertainty itself in the calculation.
In the future, this approach could also be very useful for defining new risk management strategies allowing, for example, the preparation of different mitigation actions for specific aspects based on scientific information provided in real time by the PTF such as, for example, the activation of procedures that safeguard industrial plants in emergencies.
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INGV presents a new model for tsunami early warning following an earthquake
Realized a forecasting model that includes a quantitative estimate of uncertainties, linking it to the definition of tsunami alert levels
The Probabilistic Tsunami Forecasting (PTF) is the innovative procedure that allows, in real time, the determination of the tsunami alert level taking into account the inevitable uncertainty on the forecast of the tsunami. The procedure, which could introduce a paradigm shift in the management of tsunami alerts, was developed by an international research team coordinated by the National Institute of Geophysics and Volcanology (INGV - National Institute of Geophysics and Volcanology) has just been published in the study “Probabilistic tsunami forecasting for early warnings” in the scientific journal 'Nature Communications'.
“The PTF quantifies the probability of occurrence of a tsunami with a given intensity within a few minutes after the shock capable of generating it", explains Jacopo Selva of the INGV Tsunami Warning Center (Centro Alerta Tsunami, CAT-INGV) and first author of the article. The method developed by the researchers rigorously and for the first time evaluates the unavoidable degree of uncertainty in real-time tsunami forecasts. “This offers the possibility to link the definition of the alert levels for tsunami early warning to the forecast of the intensity of the possible tsunami and to the relative uncertainty, based on pre-established risk reduction criteria”Jacopo Selva adds.
“The forecasts are made by combining the earthquake parameters estimated in real-time with those expected in the area and, finally, with millions of numerical simulations of the tsunami propagation pre-calculated thanks to modern supercomputers”, adds Stefano Lorito, co-author of the study.
The research team applied the PTF, a posteriori, to several seismic events, including the 8.8 magnitude earthquake that hit Maule, Chile, in 2010, the Zemmouri-Boumerdes tsunami, Algeria, generated in 2003 by an earthquake of magnitude 6.8, and the recent tsunami generated almost a year ago by the earthquake of magnitude 7.0, which occurred near the Greek island of Samos. All the earthquakes located in the Mediterranean area that have activated the INGV CAT in recent years were also analysed. This made it possible to evaluate the accuracy of the forecasting model over a wide range of magnitudes and types of the seismic event, from relatively small crustal earthquakes to larger events generated in subduction areas.
In order to be able to offer, in case of an event, an adequate response to citizens residing in coastal areas exposed to the risk of flooding from a tsunami, it is essential to combine the scientific evidence with political choices that are needed to link an alert level to a given probability, considering that each alert level, in turn, can correspond to certain coastal areas to be evacuated. The latter, in Italy, have been defined by ISPRA, INGV, and DPC, which are the components of the SiAM ("National Alert System for Tsunamis Generated by Earthquakes", the National Alert System for Tsunamis generated by earthquakes). Indeed, both missed and false alarms can generate significant socio-economic consequences. Given that both cases are due to the uncertainty in the prediction of hazardous events, the PTF aims at integrating the uncertainty itself into calculations.
This approach in the future may be useful also for the definition of new strategies of risk management, allowing, for example, the definition of different mitigation actions for specific issues based on the scientific information provided in real-time by the PTF such as, for example, the activation of procedures to safeguard industrial plants in cases of emergency.
Il Probabilistic Tsunami Forecasting (PTF) is the innovative procedure that allows, in real time, the determination of the tsunami alert level taking into account the inevitable uncertainty in the tsunami forecast. The new procedure, which could introduce a breakthrough in the management of tsunami warnings, was developed by an international research team coordinated by the National Institute of Geophysics and Volcanology (INGV) and has just been published in the study “Probabilistic tsunami forecasting for early warnings” in the scientific journal 'Nature Communications'.
“The PTF quantifies the probability of a tsunami of a given intensity occurring within a few minutes of the earthquake that may have generated it”, explains Jacopo Selva of the INGV Tsunami Alert Center (CAT-INGV) and first author of the article. The method developed by the researchers rigorously assesses for the first time the unavoidable degree of uncertainty in real-time tsunami forecasting. "This offers the possibility of linking the definition of the early warning level to the forecast of the intensity of the possible tsunami and the relative uncertainty, based on pre-established risk reduction criteria", adds Jacopo Selva.
“The forecasts are made by combining the earthquake parameters estimated in real time with those expected in the area in the long term and, finally, with millions of numerical simulations of the tsunami propagation, pre-calculated thanks to modern supercomputers”, adds Stefano Lorito, co-author of the study.
The research team applied the PTF, retrospectively, to several seismic events including the 8.8 magnitude earthquake that struck Maule, Chile in 2010, the Zemmouri-Boumerdes tsunami in Algeria, generated in 2003 by an magnitude 6.8, and the tsunami generated almost a year ago by the magnitude 7.0 earthquake that occurred near the Greek island of Samos. All the earthquakes located in the Mediterranean area that have activated the INGV CAT in recent years were also analysed. This made it possible to evaluate the accuracy of the forecasting model on a wide range of magnitudes and types of seismic event, from relatively small crustal earthquakes to larger events generated in subduction zones.
In order to be able to offer an adequate response in the event of an event to citizens residing in coastal areas exposed to the risk of flooding from tsunamis, it is essential to combine scientific evidence with local policy choices, so as to associate an alert level with a given probability , considering that each alert level, in turn, can correspond to certain coastal strips to be evacuated. The latter, in Italy, have been defined by ISPRA, INGV and DPC which are the components of the SiAM (National Alert System for Tsunamis Generated by Earthquakes). Indeed, both missed alarms and false alarms can generate significant socio-economic consequences. Since both cases are due to the uncertainty in the prediction of calamitous events, the PTF proposes to include the uncertainty itself in the calculation.
In the future, this approach could also be very useful for defining new risk management strategies allowing, for example, the preparation of different mitigation actions for specific aspects based on scientific information provided in real time by the PTF such as, for example, the activation of procedures that safeguard industrial plants in emergencies.
---
INGV presents a new model for tsunami early warning following an earthquake
Realized a forecasting model that includes a quantitative estimate of uncertainties, linking it to the definition of tsunami alert levels
The Probabilistic Tsunami Forecasting (PTF) is the innovative procedure that allows, in real time, the determination of the tsunami alert level taking into account the inevitable uncertainty on the forecast of the tsunami. The procedure, which could introduce a paradigm shift in the management of tsunami alerts, was developed by an international research team coordinated by the National Institute of Geophysics and Volcanology (INGV - National Institute of Geophysics and Volcanology) has just been published in the study “Probabilistic tsunami forecasting for early warnings” in the scientific journal 'Nature Communications'.
“The PTF quantifies the probability of occurrence of a tsunami with a given intensity within a few minutes after the shock capable of generating it", explains Jacopo Selva of the INGV Tsunami Warning Center (Centro Alerta Tsunami, CAT-INGV) and first author of the article. The method developed by the researchers rigorously and for the first time evaluates the unavoidable degree of uncertainty in real-time tsunami forecasts. “This offers the possibility to link the definition of the alert levels for tsunami early warning to the forecast of the intensity of the possible tsunami and to the relative uncertainty, based on pre-established risk reduction criteria”Jacopo Selva adds.
“The forecasts are made by combining the earthquake parameters estimated in real-time with those expected in the area and, finally, with millions of numerical simulations of the tsunami propagation pre-calculated thanks to modern supercomputers”, adds Stefano Lorito, co-author of the study.
The research team applied the PTF, a posteriori, to several seismic events, including the 8.8 magnitude earthquake that hit Maule, Chile, in 2010, the Zemmouri-Boumerdes tsunami, Algeria, generated in 2003 by an earthquake of magnitude 6.8, and the recent tsunami generated almost a year ago by the earthquake of magnitude 7.0, which occurred near the Greek island of Samos. All the earthquakes located in the Mediterranean area that have activated the INGV CAT in recent years were also analysed. This made it possible to evaluate the accuracy of the forecasting model over a wide range of magnitudes and types of the seismic event, from relatively small crustal earthquakes to larger events generated in subduction areas.
In order to be able to offer, in case of an event, an adequate response to citizens residing in coastal areas exposed to the risk of flooding from a tsunami, it is essential to combine the scientific evidence with political choices that are needed to link an alert level to a given probability, considering that each alert level, in turn, can correspond to certain coastal areas to be evacuated. The latter, in Italy, have been defined by ISPRA, INGV, and DPC, which are the components of the SiAM ("National Alert System for Tsunamis Generated by Earthquakes", the National Alert System for Tsunamis generated by earthquakes). Indeed, both missed and false alarms can generate significant socio-economic consequences. Given that both cases are due to the uncertainty in the prediction of hazardous events, the PTF aims at integrating the uncertainty itself into calculations.
This approach in the future may be useful also for the definition of new strategies of risk management, allowing, for example, the definition of different mitigation actions for specific issues based on the scientific information provided in real-time by the PTF such as, for example, the activation of procedures to safeguard industrial plants in cases of emergency.
Figure 1: The PTF integrates the information derived from real-time monitoring with information on earthquakes expected in the area and, finally, with millions of numerical simulations of tsunami propagation pre-calculated thanks to modern supercomputers, providing estimates that can be updated over time, allowing a reduction in uncertainty - Figure 1: The PTF integrates information derived from real-time monitoring with information on expected earthquakes in the area and, finally, with millions of numerical simulations of tsunami propagation pre-calculated thanks to modern supercomputers, providing estimates that may be updated over time, allowing a reduction of the uncertainty
Figure 2: The accuracy of the PTF probabilistic estimates have been verified a posteriori with numerous seismic events that occurred in the Mediterranean, including all the events that have activated the INGV Tsunami Warning Center (CAT) since 2015 -
Figure 2: The accuracy of the probabilistic estimates of the PTF were tested in hindcasting mode with numerous seismic events that occurred in the Mediterranean, including all the events that activated the INGV Tsunami Warning Center (CAT – “Centro di Alerta Tsunami”) since its inception in 2015
Figure 3: The quantifications produced by the PTF can be linked to the different alert levels of the early warning system by considering the actual uncertainties at the time of the estimate. This allows to define the alert level taking into account the potential number of false or missed alarms deriving from the inevitable uncertainty that exists in the first minutes after the earthquake - Figure 3: The quantifications produced by the PTF can be linked to the different alert levels of the early warning system, accounting for the actual uncertainties at the time of the estimate. This allows to define the alert level taking into account the potential number of false or missed alarms resulting from the unavoidable uncertainty that exists in the first minutes after the earthquake