On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei

For active volcanoes, knowledge about probabilities of eruption and impacted areas becomes valuable information for decision-makers to develop short- long-term emergency plans, which probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA requires extreme-scale high-performance computing systems. Within the framework ChEESE (Center Excellence Exascale in Solid Earth; www.cheese-coe.eu ), an effort was made generate exascale-suitable codes workflows collect process some hours large amount data that a quality requires. To this end, we created optimized HPC-based workflow coined PVHA_HPC-WF volcano. This tool uses Bayesian event tree methodology calculate probabilities, vent-opening location(s), eruptive source parameters (ESPs) based on volcano history, monitoring system data, meteorological conditions. Then, interacts with chosen model, performing simulation each ESP set scenario (VS). Finally, resulting processed by proof-of-concept-subjected analytics (HPDA) scripts, producing maps describe probability over time exceeding critical thresholds at location investigated geographical domain. Although can be adapted other hazards, focus here tephra (i.e., lapilli ash) transport deposition. As application, performed Campi Flegrei (CF), Italy, located one most densely inhabited Europe under busy air traffic routes. CF currently unrest, classified as being attention level Italian Civil Protection. We consider approximate 2,000 × 40 km computational domain 2 grid resolution horizontal vertical levels, centered CF. explore natural variability uncertainty conditions, number VSs allowing us include those low but high impact, simulations dispersal are them using FALL3D model. Results show potential HPC timely execute vast range complex numerical models high-resolution domains analyze great volumes obtain maps.