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- and long-term emergency plans, for which probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA require...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2022.941789/full |
| _version_ | 1797997768584724480 |
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| author | Beatriz Martínez Montesinos Manuel Titos Luzón Laura Sandri Oleksandr Rudyy Alexey Cheptsov Giovanni Macedonio Arnau Folch Arnau Folch Sara Barsotti Jacopo Selva Antonio Costa |
| author_facet | Beatriz Martínez Montesinos Manuel Titos Luzón Laura Sandri Oleksandr Rudyy Alexey Cheptsov Giovanni Macedonio Arnau Folch Arnau Folch Sara Barsotti Jacopo Selva Antonio Costa |
| author_sort | Beatriz Martínez Montesinos |
| collection | DOAJ |
| description | For active volcanoes, knowledge about probabilities of eruption and impacted areas becomes valuable information for decision-makers to develop short- and long-term emergency plans, for which probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA requires extreme-scale high-performance computing systems. Within the framework of ChEESE (Center of Excellence for Exascale in Solid Earth; www.cheese-coe.eu), an effort was made to generate exascale-suitable codes and workflows to collect and process in some hours the large amount of data that a quality PVHA requires. To this end, we created an optimized HPC-based workflow coined PVHA_HPC-WF to develop PVHA for a volcano. This tool uses the Bayesian event tree methodology to calculate eruption probabilities, vent-opening location(s), and eruptive source parameters (ESPs) based on volcano history, monitoring system data, and meteorological conditions. Then, the tool interacts with the chosen hazard model, performing a simulation for each ESP set or volcanic scenario (VS). Finally, the resulting information is processed by proof-of-concept-subjected high-performance data analytics (HPDA) scripts, producing the hazard maps which describe the probability over time of exceeding critical thresholds at each location in the investigated geographical domain. Although PVHA_HPC-WF can be adapted to other hazards, we focus here on tephra (i.e., lapilli and ash) transport and deposition. As an application, we performed PVHA for Campi Flegrei (CF), Italy, an active volcano located in one of the most densely inhabited areas in Europe and under busy air traffic routes. CF is currently in unrest, classified as being in an attention level by the Italian Civil Protection. We consider an approximate 2,000 × 2,000 × 40 km computational domain with 2 km grid resolution in the horizontal and 40 vertical levels, centered in CF. To explore the natural variability and uncertainty of the eruptive conditions, we consider a large number of VSs allowing us to include those of low probability but high impact, and simulations of tephra dispersal are performed for each of them using the FALL3D model. Results show the potential of HPC to timely execute a vast range of simulations of complex numerical models in large high-resolution computational domains and analyze great volumes of data to obtain quality hazard maps. |
| first_indexed | 2024-04-11T10:37:50Z |
| format | Article |
| id | doaj.art-6ee5e36e7aa14f8690eed1fe6076349f |
| institution | Directory Open Access Journal |
| issn | 2296-6463 |
| language | English |
| last_indexed | 2024-04-11T10:37:50Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj.art-6ee5e36e7aa14f8690eed1fe6076349f2022-12-22T04:29:15ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632022-09-011010.3389/feart.2022.941789941789On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi FlegreiBeatriz Martínez Montesinos0Manuel Titos Luzón1Laura Sandri2Oleksandr Rudyy3Alexey Cheptsov4Giovanni Macedonio5Arnau Folch6Arnau Folch7Sara Barsotti8Jacopo Selva9Antonio Costa10Istituto Nazionale di Geofisica e Vulcanologia, Bologna, ItalyIcelandic Met Office, Reykjavík, IcelandIstituto Nazionale di Geofisica e Vulcanologia, Bologna, ItalyHigh-Performance Computing Center Stuttgart, Stuttgart, GermanyHigh-Performance Computing Center Stuttgart, Stuttgart, GermanyIstituto Nazionale di Geofisica e Vulcanologia, Naples, ItalyBarcelona Supercomputing Center, Barcelona, SpainGeociencias Barcelona (GEO3BCN), CSIC, Barcelona, SpainIcelandic Met Office, Reykjavík, IcelandIstituto Nazionale di Geofisica e Vulcanologia, Bologna, ItalyIstituto Nazionale di Geofisica e Vulcanologia, Bologna, ItalyFor active volcanoes, knowledge about probabilities of eruption and impacted areas becomes valuable information for decision-makers to develop short- and long-term emergency plans, for which probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA requires extreme-scale high-performance computing systems. Within the framework of ChEESE (Center of Excellence for Exascale in Solid Earth; www.cheese-coe.eu), an effort was made to generate exascale-suitable codes and workflows to collect and process in some hours the large amount of data that a quality PVHA requires. To this end, we created an optimized HPC-based workflow coined PVHA_HPC-WF to develop PVHA for a volcano. This tool uses the Bayesian event tree methodology to calculate eruption probabilities, vent-opening location(s), and eruptive source parameters (ESPs) based on volcano history, monitoring system data, and meteorological conditions. Then, the tool interacts with the chosen hazard model, performing a simulation for each ESP set or volcanic scenario (VS). Finally, the resulting information is processed by proof-of-concept-subjected high-performance data analytics (HPDA) scripts, producing the hazard maps which describe the probability over time of exceeding critical thresholds at each location in the investigated geographical domain. Although PVHA_HPC-WF can be adapted to other hazards, we focus here on tephra (i.e., lapilli and ash) transport and deposition. As an application, we performed PVHA for Campi Flegrei (CF), Italy, an active volcano located in one of the most densely inhabited areas in Europe and under busy air traffic routes. CF is currently in unrest, classified as being in an attention level by the Italian Civil Protection. We consider an approximate 2,000 × 2,000 × 40 km computational domain with 2 km grid resolution in the horizontal and 40 vertical levels, centered in CF. To explore the natural variability and uncertainty of the eruptive conditions, we consider a large number of VSs allowing us to include those of low probability but high impact, and simulations of tephra dispersal are performed for each of them using the FALL3D model. Results show the potential of HPC to timely execute a vast range of simulations of complex numerical models in large high-resolution computational domains and analyze great volumes of data to obtain quality hazard maps.https://www.frontiersin.org/articles/10.3389/feart.2022.941789/fullHPCprobabilistic volcanic hazard assessmentash dispersalexascale computingBayesian event treeperformance optimization and productivity |
| spellingShingle | Beatriz Martínez Montesinos Manuel Titos Luzón Laura Sandri Oleksandr Rudyy Alexey Cheptsov Giovanni Macedonio Arnau Folch Arnau Folch Sara Barsotti Jacopo Selva Antonio Costa On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei Frontiers in Earth Science HPC probabilistic volcanic hazard assessment ash dispersal exascale computing Bayesian event tree performance optimization and productivity |
| title | On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei |
| title_full | On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei |
| title_fullStr | On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei |
| title_full_unstemmed | On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei |
| title_short | On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei |
| title_sort | on the feasibility and usefulness of high performance computing in probabilistic volcanic hazard assessment an application to tephra hazard from campi flegrei |
| topic | HPC probabilistic volcanic hazard assessment ash dispersal exascale computing Bayesian event tree performance optimization and productivity |
| url | https://www.frontiersin.org/articles/10.3389/feart.2022.941789/full |
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