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The Millennium Eruption of Paektu volcano, on the border of China and North Korea, generated tephra deposits that extend >1000 km from the vent, making it one of the largest eruptions in historical times. Based on observed thicknesses and compositions of the deposits, the widespread tephra dispersal is attributed to two eruption phases fuelled by chemically distinct magmas that produced both pyroclastic flows and fallout deposits. We used an ensemble-based method with a dual step inversion, in combination with the FALL3D atmospheric tephra transport model, to constrain these two different phases. The volume of the two distinct phases has been calculated. The results indicate that about 3-16 km3 (with a best estimate of 7.2 km3) and 4-20 km3 (with a best estimate of 9.3 km3) of magma were erupted during the comendite and trachyte phases of the eruption, respectively. Eruption rates of up to 4 × 108 kg/s generated plumes that extended 30-40 km up into the stratosphere during each phase.

Volcano Observatories (VOs) around the world are required to maintain the surveillance of their volcanoes and inform timely civil protection and aviation authorities about impending eruptions. Often, they work through procedures which allow them to respond timely to volcanic crises and provide a service aimed at reducing the potential impact of an eruption. Within the International Airways Volcano Watch (IAVW) framework, VOs are asked to operate a system designed to inform the aviation community about the status of a volcano and the expected threat associated. Despite the IAVW documentation reports the definition of the different color coded levels, operating the Aviation Color Code (ACC) can be a difficult task and VOs might adopt different strategies on how, when and why to change it. Following the two European Volcano Observatories and VAACs meetings, in 2019 and 2021, the European VOs agreed to present an overview on how they work about ACC. This analysis reveals that not all VOs in Europe have the usage of ACC as part of their operations, mainly because of lack of eruptions in recent times. Moreover, those VOs which regularly adopt ACC, operate it differently depending on the frequency of the eruptions, the type of volcano, the historical eruptive activity, the monitoring level, but also the agreement with the local Air Transport Navigation providers. At the same time all VOs change ACC in a very dynamic way to reflect the variability in the volcanic activity, except during decreasing activity and waning phase. This study shows that despite the ACC system is designed to provide a standard, its usage strongly depends on the evaluation of those responding to volcano emergencies. Still the usage of ACC is of relevance for the aviation stakeholders, that encourage its practice in addition to a wider dialogue with the Volcano Observatories in Europe.

Interdisciplinary digital twins are becoming able to mimic the different Earth system domains with unrivalled precision, providing analyses, forecasts, uncertainty quantification, and ¿what if¿ scenarios for natural and anthropogenic hazards from their genesis to propagation and impacts. The EU DT-GEO project (2022-2025) is deploying a prototype digital twin on geophysical extremes consisting of interrelated Digital Twin Components (DTCs), intended as self-contained containerised entities embedding simulation codes, Artificial Intelligence (AI) layers, large volumes of nearly-real-time data streams, data assimilation methodologies, and overarching workflows for deployment and execution of single or coupled DTCs in centralised High Performance Computing (HPC) and virtual cloud computing Research Infrastructures (RIs). These DTCs, actually a first step towards a digital twin on Geophysical Extremes integrated in the Destination Earth (DestinE) initiative, will deal with geohazards from earthquakes, volcanoes, and tsunamis by harnessing world-class computational (EuroHPC) and data (EPOS) Research Infrastructures, operational monitoring networks, and leading-edge research and academia partnerships. In particular, 4 DTCs of the 12 in DT-GEO will address different volcanic hazards. DTC-V1 will merge multi-parametric data from ground- based and remote observation systems (on-site monitoring networks and satellites) with global modelling of magma and rock dynamics and with AI approach. DTC-V2 will merge real-time geostationary satellite observations with the FALL3D model using the on-line data assimilation PDAF system to generate deterministic and ensemble-based probabilistic forecast products. DTC-V3 will merge real-time multi- parametric data from ground-based and remote observation systems with deterministic modelling of lava flow propagation and inundation areas including Bayesian modelling of vent opening. Finally, DTC-V4 will consider air-quality data and AI in a gas

The project Digital Twin for GEOphysical extremes-(DT-GEO) aims to use Digital Twin Components to create replicas of physical systems, serving as a virtual laboratory to study natural extreme events. The ratio- nale is the intrinsic risks of potentially catastrophic events to anthropic activities, infrastructures, and cultural heritage. In the framework of the project, this paper describes, how the DTC workflow architecture is designed, focusing on flexibility, scalability, and maintainability, and how it is further developed. To demonstrate how ICT efforts can expand horizons in Geosciences, an application to volcanic hazard is presented taking as a case study the 2019 volcanic eruption of Raikoke (Kuril Islands).

Within the framework of ChEESE (Center of Excellence for Exascale in Solid Earth) we created an optimized HPC-based workflow coined PVHA_HPC-WF to develop Probabilistic Volcanic Hazard Assessment (PVHA) for a specific volcano. Increasing the computational capabilities of current PVHA products, PVHA_HPC-WF provides probability and hazard maps, with uncertainty, for tephra fallout at ground and airborne ash concentration and time-persistence at strategic flight levels, exploring the natural variability in Eruptive Source Parameters (ESPs) and wind conditions through a large number of ash dispersal simulations with the model Fall3D. Among other tests, we showcased the workflow through a live exercise for Campi Flegrei, proving the feasibility and usefulness for end-users, such as the Centre of Competence of the Italian Civil Protection PLINIVS and ARISTOTLE, of such hazard evaluations to produce useful short-term impact assessment of tephra ground load at the scale of a country, in particular over mobility networks (road, railways, seaports and airports) and electrical networks, in an operational environment, dealing with real- time performance-distributed workflow. We ran 300 large-scale and high-resolution tephra dispersal simulations with the Flagship code Fall3D on MareNostrum at BSC fetching weather forecast from GFS, and we processed them on the computer cluster ADA at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) of Bologna fetching real-time monitoring data from Osservatorio Vesuviano surveillance system. Results show the ability of the PVHA_HPC-WF to perform PVHA in a reasonable time, with a sufficient level of detail, and therefore its usefulness for civil protection officials and society in reliably assessing volcanic hazard.

Which is the EuroHPC deployment roadmap, policy and HPC infrastructure access modes? Which are the research funding opportunities for geosciences from Horizon Europe (REA) or other EC Directorates-General (DGs)? How can European geoscientists better partner to benefit from the Exascale transition opportunities?

In recent years, there has been a growing interest in ensemble-based based approaches for modeling volcanic plumes. The development of advanced ensemble modeling techniques enables the exploration of novel methods for the incorporation of real observations into tephra dispersal models using ensemble- based data assimilation techniques. However, traditional data assimilation algorithms, including ensemble Kalman filter methods, can yield suboptimal state estimates for positive-definite variables such as volcanic aerosols and tephra deposits. We present two new ensemble-based data assimilation techniques for semi- positive-definite variables with highly skewed uncertainty distributions, such as deposit mass loading. The proposed methods are applied to reconstruct the tephra fallout deposit resulting from the 2015 Calbuco eruption and the 946 CE eruption of Baekdu volcano, the so-called Millennium eruption, one of the largest eruptions in historic times based on widespread tephra dispersal. The FALL3D dispersal model was used to perform an ensemble of runs in order to simulate the transport and deposition of tephra for different model configurations. Subsequently, deposit thickness measurements are assimilated to reconstruct the tephra deposit and improve the first-guess results, obtained from a simple ensemble forecast. An assessment of the assimilation methods is carried out using an independent dataset of observations in terms of different evaluation metrics. The methodologies presented here represent promising alternatives for the assimilation of real observations in operational models.

In recent years, there has been a growing interest in ensemble approaches for modelling the atmospheric transport of volcanic aerosol, ash, and lapilli (tephra). The development of such techniques enables the exploration of novel methods for incorporating real observations into tephra dispersal models. However, traditional data assimilation algorithms, including ensemble Kalman filter (EnKF) methods, can yield suboptimal state estimates for positive-definite variables such as those related to volcanic aerosols and tephra deposits. This study proposes two new ensemble-based data assimilation techniques for semi-positive-definite variables with highly skewed uncertainty distributions, including aerosol concentrations and tephra deposit mass loading: the Gaussian with non-negative constraints (GNC) and gamma inverse-gamma (GIG) methods. The proposed methods are applied to reconstruct the tephra fallout deposit resulting from the 2015 Calbuco eruption using an ensemble of 256 runs performed with the FALL3D dispersal model. An assessment of the methodologies is conducted considering two independent datasets of deposit thickness measurements: an assimilation dataset and a validation dataset. Different evaluation metrics (e.g. RMSE, MBE, and SMAPE) are computed for the validation dataset, and the results are compared to two references: the ensemble prior mean and the EnKF analysis. Results show that the assimilation leads to a significant improvement over the first-guess results obtained from the simple ensemble forecast. The evidence from this study suggests that the GNC method was the most skilful approach and represents a promising alternative for assimilation of volcanic fallout data. The spatial distributions of the tephra fallout deposit thickness and volume according to the GNC analysis are in good agreement with estimations based on field measurements and isopach maps reported in previous studies. On the other hand, although it is an interesting approach, the GIG m

The atmospheric dispersion of gases (of natural or industrial origins) can be very hazardous to life and the environment if the concentration of some gas species overcome specie-specific thresholds. In this context, the natural variability associated to the natural phenomena has to be explored to provide robust probabilistic gas dispersion hazard assessments. VIGIL-1.3 (automatic probabilistic VolcanIc Gas dIspersion modeLling) is a Python simulation tool born to automatize the complex and time-consuming simulation workflow required to process a large number of gas dispersion numerical simulations. It is interfaced with two models: a dilute (DISGAS) and a dense gas (TWODEE-2) dispersion model. The former is used when the density of the gas plume at the source is lower than the atmospheric density (e.g. fumaroles), the latter when the gas density is higher than the atmosphere and the gas accumulates on the ground and may flow due to the density contrast with the atmosphere to form a gravity current (e.g. cold CO2 flows). In the enhancement of the code towards a higher-scale computing, here we present the ongoing improvements aimed to extend some code functionalities such as memory management, modularity revision, and full-ensemble uncertainty on gas dispersal scenarios (e.g. sampling techniques for gas fluxes and source locations). Optimizations are also provided in terms of tracking errors, redesignation of the input file, validation of data provided by the users, and addition of the Latin hypercube sampling (LHS) for the post-processing of model outputs. All these new features will be issued in the future release of the code (VIGIL-2.0) in order to facilitate the users which could run VIGIL on laptops or large supercomputer, and to widen the spectrum of model applications from routinely operational forecast of volcanic gas to long-term hazard and/or risk assessments purposes.

A Digital Twin Component (DTC) provides users with digital replicas of different components of the Earth system through unified frameworks integrating real-time observations and state-of-the-art numerical models. Scenarios of extreme events for natural hazards can be studied from the genesis to propagation and impacts using a single DTC or multiple coupled DTCs. The EU DT-GEO project (2022-2025) is implementing a prototype digital twin on geophysical extremes consisting of 12 interrelated Digital Twin Components, intended as self-contained and containerised software entities embedding numerical model codes, management of real-time data streams and data assimilation methodologies. DTCs can be deployed and executed in centralized High Performance Computing (HPC) and cloud computing Research Infrastructures (RIs). In particular, the DTC-V2 is implementing an ensemble-based automated operational system for deterministic and probabilistic forecast of long-range ash dispersal and local-scale tephra fallout. The system continuously screens different ground-based and satellite-based data sources and a workflow is automatically triggered by a volcanic eruption to stream and pre-process data, its ingestion into the FALL3D dispersal model, a centralized or distributed HPC model execution, and the post-processing step. The DTCs will provide capability for analyses, forecasts, uncertainty quantification, and "what if" scenarios for natural and anthropogenic hazards, with a long-term ambition towards the Destination Earth mission-like initiative.