A unified probabilistic framework for volcanic hazard and eruption forecasting

Abstract. The main purpose of this article is to emphasize the importance clarifying probabilistic framework adopted for volcanic hazard and eruption forecasting. Eruption forecasting analysis seek quantify deep uncertainties that pervade modeling pre-, sin-, post-eruptive processes. These can be differentiated into three fundamental types: (1) natural variability systems, usually represented as stochastic processes with parameterized distributions (aleatory variability); (2) uncertainty in our knowledge how systems operate evolve, often subjective probabilities based on expert opinion (epistemic uncertainty); (3) possibility forecasts are wrong owing behaviors about which we completely ignorant and, hence, cannot terms (ontological error). Here put forward a recently proposed by Marzocchi Jordan (2014), unifies treatment all types uncertainty. Within framework, an or model said complete only if it (a) fully characterizes epistemic model's representation aleatory (b) unconditionally tested (in principle) against observations identify ontological errors. Unconditional testability, key validation, hinges experimental concept events exchangeable data sequences well-defined frequencies. We illustrate application unified describing concepts tephra fall from Campi Flegrei. Eventually, example may serve guide same other hazards.