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High risk volcanic events are commonly preceded by long periods of unrest during which scientists are asked to provide near real-time forecasts. The rarity of such events, inaccessibility of the underground volcanic system, non-linear behaviors, and limited datasets constitute major sources of uncertainty. In order to provide reasoned guidance in the face of uncertainties, monitoring observations and conceptual/theoretical models must be incorporated into a formal and structured probabilistic scheme using evidence science principles. As uncertainty and subjectivity are inescapable components of volcanic hazard forecasts, they must be dealt with and clearly communicated to decision-makers and society. Here, we present the set-up of an automated near-real-time tool for short-term eruption forecasting for Campi Flegrei caldera (CFc), Italy. The tool, based on a Bayesian Event Tree scheme, takes account of all the available information, and subjectivity of choices is dealt through a 5-year-long elicitation experiment with a team of about 30 of the major experts of the geological history, dynamics and monitoring of CFc. The tool provides prompt probabilistic assessment in near real-time, making it particularly suitable for tracking a rapidly evolving crisis, and it is easily reviewable once new observations and/or models become available. The quantitative rules behind the tool, which represent the group view of the elicited community of experts, are defined during a period of quiescence, thus allowing prior scrutiny of any scientific input into the model, and minimizing the external stress on scientists during an actual emergency phase. Notably, the results also show that CFc may pose a higher threat to the city of Naples than the better-known Mount Vesuvius.

Operational eruption forecasting at high-risk volcanoes: the case of Campi Flegrei, Naples