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

中文翻译：

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火山灾害和喷发预测的统一概率框架

摘要。本文的主要目的是强调澄清用于火山灾害和喷发预测的概率框架的重要性。喷发预测和火山灾害分析旨在量化普遍存在于喷发前、火山喷发和喷发后过程建模的深度不确定性。这些不确定性可以分为三种基本类型：（1）火山系统的自然变率，通常表示为具有参数化分布的随机过程（随机变率）；(2) 我们对火山系统如何运作和演化的认识的不确定性，通常表示为基于专家意见的主观概率（认知不确定性); (3) 由于我们完全不了解火山过程的行为，我们的预测错误的可能性，因此无法量化概率（本体错误）。在这里，我们提出了 Marzocchi & Jordan (2014) 最近提出的用于危险分析的概率框架，该框架统一了对所有三种类型的不确定性的处理。在此框架内，喷发预测或火山灾害模型只有在 (a) 完全表征模型对偶然变率的表示中的认知不确定性和 (b) 可以无条件地（原则上）针对观测进行测试时才被称为完整的识别本体错误。无条件可测试性是模型验证的关键，取决于实验概念它根据具有明确定义的频率的可交换数据序列来表征危险事件。我们通过描述用于预测 Campi Flegrei 火山灰坠落的实验概念来说明这种统一概率框架的应用。最终，这个例子可以作为将相同的概率框架应用于其他自然灾害的指南。