Geometrical and physical properties of the 1982-84 deformation source at Campi Flegrei - Italy

Deformation of the ground surface in volcanic areas is generally recognized as a reliable indicator of unrest, possibly resulting from the intrusion of fresh magma within the shallow rock layers. The intrusion process is usually represented by a deformation source such as an ellipsoidal pressurized cavity, embedded within a homogeneous and elastic half-space. Similar source models allow inferring the depth, the location and the (incremental) volume of the intrusion, which are very important parameters for volcanic risk implications. However, assuming a homogeneous and elastic rheology and, assigning a priori the shape and the mechanism of the source (within a very restricted “library” of available solutions) may bias considerably the inference of source parameters. In complete generality, any point source deformation, including overpressure sources, may be described in terms of a suitable moment tensor, while the assumption of an overpressure source strongly restricts the variety of allowable moment tensors. In particular, by assuming a pressurized cavity, we rule out the possibility that either shear failure may precede magma emplacement (seismically induced intrusion) or may accompany it (mixed tensile and shear mode fracture). Another possibility is that a pre-existent weakness plane may be chosen by the ascending magma (fracture toughness heterogeneity). We perform joint inversion of levelling and EDM data (part of latter are unpublished), collected during the 1982-84 unrest at Campi Flegrei caldera: a 43% misfit reduction is obtained for a general moment source if the elastic heterogeneities computed from seismic tomography are accouted for. The inferred source is at 5.2 km depth but cannot be interpreted as a simple pressurized cavity. Moreover, if mass conservation is accounted for, magma emplaced within a shallow source must come from a (generally deeper) reservoir, which is usually assumed to be deep enough to be simply neglected. At Campi Flegrei, seismic tomography indicates that the “deep” magma source is rather shallow (at 7-8 km depth), so that its presence should be included in any thorough attempt to source modeling. Taking into account a deflating source at 7.5 km depth (represented either as a horizontal sill or as an isotropic cavity) and an inflating moment source, the fit of both levelling and EDM data improves further (misfit reduction 80%), but still the best fitting moment source (at 5.5 km depth) falls outside the range of pressurized ellipsoidal cavities. The shallow moment source may be decomposed in a tensile and a shear dislocation. No clue is obtained that the shear and the tensile mechanisms should be located in different positions. Our favourite interpretation is in terms of a crack opening in mixed tensile and shear mode, as would be provided by fluid magma unwelding pre-stressed solid rock. Although this decomposition of the source is not unique, the proposed solution is physically motivated by the minimum overpressure requirement. An important implication of this new interpretation is that the magma emplaced in the shallow moment source during the 1982-84 unrest was not added to already resident magma at the same position

Editorial: The Impact of Open Science for Evaluation of Volcanic Hazards

n/

The Mw 7.9Wenchuan (China) Earthquake: exploring the role of crustal heterogeneities from finite element analysis of DInSAR coseismic deformation

A destructive (Mw 7.9) earthquake struck the Sichuan province (China) on May 12, 2008. The seismic event, the largest in China in more than three decades and referred as the Wenchuan earthquake, ruptured approximately 280 km of the Yingxiu-Beichuan fault and about 70 km of the Guanxian-Anxian fault. Surface effects were suffered over a wide epicentral area (about 300 km E-W and 250 km N-S). The huge earthquake took place within the context of long term uplift of the Longmen Shan range in eastern Tibet. The Longmen Shan fault zone is the main tectonic boundary between the Sichuan basin and eastern Tibet and is characterized by a large topographic relief (from 500m a.s.l. to more than 4000m) and large variations in rheological properties. The coseismic deformation is imaged by a set of ALOS-PALSAR L-band SAR interferograms. We use an unprecedented high number of data (25 frames from 6 adjacent tracks) to encompass the entire coseismic area. The resulting mosaic of differential interferograms covers an overall area of about 340 km E-W and 240 km N-S. The complex geophysical context of Longmen Shan and the variations of the fault geometry along its length can be better handled by means of numerical methods. The fault geometry is constrained by inversions of geodetic data and by taking into account the geological features of eastern Tibet and Sichuan basin. As a result, we build a Finite Element (FE) model consisting of two non planar faults embedded in a non-homogeneous medium with real topography of the area. We develop a procedure to perform inversions of DInSAR data based on FE computed Green functions of the surface displacement field. We retrieve a complex slip distribution on the fault segments in a heterogeneous medium with realistic surface topography

Contribution of the EVER-EST project to the community of the Geohazard Supersites initiative

The EVER-EST project (European Virtual Environment for Research - Earth Science Themes: a solution) is a H2020 project (2015-2018) aimed at the creation of a Virtual Research Environment (VRE) focused on the requirements of the Earth Science community. The VRE is intended to enhance the ability to collaborate, interoperate and share knowledge and experience between all relevant stakeholders, including researchers, monitoring teams and civil protection agencies. Among the innovations of the project is the exploitation of the “Research Object” concept.PublishedVIenna,Austria1VV. Altr

Enabling FAIR research in Earth Science through research objects

Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific information and resources in a way compliant with the FAIR principles and sustain the development of key infrastructure and tools. This paper provides an account of the challenges, experiences and solutions involved in the adoption of FAIR around research objects over several Earth Science disciplines. During this journey, our work has been comprehensive, with outcomes including: an extended research object model adapted to the needs of earth scientists; the provisioning of digital object identifiers (DOI) to enable persistent identification and to give due credit to authors; the generation of content-based, semantically rich, research object metadata through natural language processing, enhancing visibility and reuse through recommendation systems and third-party search engines; and various types of checklists that provide a compact representation of research object quality as a key enabler of scientific reuse. All these results have been integrated in ROHub, a platform that provides research object management functionality to a wealth of applications and interfaces across different scientific communities. To monitor and quantify the community uptake of research objects, we have defined indicators and obtained measures via ROHub that are also discussed herein.Published550-5645IT. Osservazioni satellitariJCR Journa

EVER-EST: the platform allowing scientists to cross-fertilize and cross-validate data

Over recent decades large amounts of data about our Planet have become available. If this information could be easily discoverable, accessible and properly exploited, preserved and shared, it would potentially represent a wealth of information for a whole spectrum of stakeholders: from scientists and researchers to the highest level of decision and policy makers. By creating a Virtual Research Environment (VRE) tailored to the needs of Earth Science (ES) communities, the EVER-EST (http://ever-est.eu) project provides a range of both generic and domain specific data analysis and management services to support a dynamic approach to collaborative research. EVER-EST provides the means to overcome existing barriers to sharing of Earth Science data and information allowing research teams to discover, access, share and process heterogeneous data, algorithms, results and experiences within and across their communities, including those domains beyond Earth Science. EVER-EST is funded by the European Commission H2020 programme for three years starting in October 2015. The project is led by the European Space Agency (ESA) and involves some of the major European Earth Science data providers/users including NERC, DLR, INGV, CNR and SatCEN . The paper presents specific aspects of this collaboration platform in terms of infrastructure and implemented paradigms. Some case studies on cross-fertilization analysis are documented in order to show the process for creating knowledge and new data starting from collected data from different sources (e.g. from remote and social sensing). The paper concludes with few future outcomes

Relations between pressurized triaxial cavities and moment tensor distributions

Pressurized cavities are commonly used to compute ground deformation in volcanic areas: the set of available solutions is limited and in some cases the moment tensors inferred from inversion of geodetic data cannot be associated with any of the available models. Two different source models (pure tensile source, TS and mixed tensile/shear source, MS) are studied using a boundary element approach for rectangular dislocations buried in a homogeneous elastic medium employing a new C/C++ code which provides a new implementation of the dc3d Okada fortran code. Pressurized triaxial cavities are obtained assigning the overpressure in the middle of each boundary element distributed over the cavity surface. The MS model shows a moment domain very similar to triaxial ellipsoidal cavities. The TS and MS models are also compared in terms of the total volume increment limiting the analysis to cubic sources: the observed discrepancy (~10%) is interpreted in terms of the different deformation of the source interior which provides significantly different internal contributions (~30%). Comparing the MS model with a Mogi source with the some volume, the overpressure of the latter must be ~37% greater than the former, in order to obtain the same surface deformation; however the outward expansion and the inner contraction separately differ by ~\ub110% and the total volume increments differ only by ~2%. Thus, the density estimations for the intrusion extracted from the MS model and the Mogi model are nearly identical

FAIR Research Objects for realizing Open Science with RELIANCE EOSC project

The H2020 Reliance project delivers a suite of innovative and interconnected services that extend European Open Science Cloud (EOSC)’s capabilities to support the management of the research lifecycle within Earth Science Communities and Copernicus Users. The project has delivered 3 complementary  technologies: Research Objects (ROs), Data Cubes and AI-based Text Mining.RoHub is a Research Object management platform that implements these 3 technologies and enables researchers to collaboratively manage, share and preserve their research work.RoHub implements the full RO model and paradigm: resources associated to a particular research work are aggregated into a single FAIR digital object, and metadata relevant for understanding and interpreting the content is represented as semantic metadata that are user and machine readable. The development of RoHub is co-designed and validated through multidisciplinary and thematic real life use cases led by three different Earth Science communities: Geohazards, Sea Monitoring and Climate Change communities. A RO commonly starts its life as an empty Live RO. ROs aggregate new objects through their whole lifecycle. This means, a RO is filled incrementally by aggregating new relevant resources such as workflows, datasets, documents according to its typology that are being created, reused or repurposed. These resources can be modified at any point in time.We can copy and keep ROs in time through snapshots which reflect their status at a given point in time. Snapshots can have their own identifiers (DOIs) which facilitates tracking the evolution of a research. At some point in time, a RO can be published and archived (so called Archived RO) with a permanent identifier (DOI). New Live ROs can be derived based on an existing Archived RO, for instance by forking it. To guide researchers, different types of Research Objects can be created:Bibliography-centric: includes manuals, anonymous interviews, publications, multimedia (video, songs) and/or other material that support research;Data-centric: refers to datasets which can be indexed, discovered and manipulated;Executable: includes the code, data and computational environment along with a description of the research object and in some cases a workflow. This type of ROs can be executed and is often used for scripts and/or Jupyter Notebooks;Software-centric: also known as “Code as a Research Object”. Software-centric ROs include source codes and associated documentation. They often include sample datasets for running tests.Workflow-centric: contains workflow specifications, provenance logs generated when executing the workflows, information about the evolution of the workflow (version) and its components elements, and additional annotations for the workflow as a whole.Basic: can contain anything and is used when the other types do not cover the need.To ease the understanding and the reuse of the ROs, each type of RO (except Basic RO) has a template folder structure that we recommend researchers to select. For instance an executable RO has 4 folders:'biblio' where  researchers can aggregate documentations, scientific papers that øed to the development of the software/tool that is aggregated in the tool folder;'input' where all the input datasets required for executing the RO are aggregated;'output' where some or all the results generated by executing the RO are aggregated;'tool' where the executable tool is aggregated. Typically, we aggregate Jupyter Notebook and/or executable workflows (Galaxy or snakemake workflows).In addition to the different types of ROs and associated template structures, researchers can select the type of resources that constitutes the main entity of a RO: for instance, a Jupyter Notebook can be selected as the main entity of an executable RO. As shown on Fig. 1, this additional metadata is then visible to everyone (and machine readable) to ease reuse. Examples of Bibliography-centric and Data-centric Research Objects are shown on Fig. 2: the overall overview of any types of Research Object is always the same with mandatory metadata information such as the title, description, authors & collaborators, sketch (featured plots/images), the content of the RO (with different structures depending on the type of ROs). Additional information is displayed on the right panel such as number of downloads, additional discovered metadata (automatically discovered from the Reliance text enrichment service), free keywords (added by end-users) and citation. The 'toolbox' and 'share' sections allows end-users to download, snapshot and archive the RO and/or share it.Any Research Object in RoHub is a FAIR digital object that is for instance findable in OpenAire, including Live ROs.In our presentation, we will showcase different types of ROs for the 3 Earth Science communities represented in Reliance to highlight how the scientists in our respective disciplines changed their working methodology towards Open Science

Geodetic constraints to the source mechanism of the 2011-2013 unrest at Campi Flegrei (Italy) caldera

Campi Flegrei caldera (Italy) was affected by a new unrest phase during 2011\u20132013. We exploit two COSMO-SkyMed data sets to map the deformation field, obtaining displacement rates reaching 9 cm/yr in 2012 in the caldera center. The resulting data set is fitted in a geophysical inversion framework using finite element forward models to account for the 3-D heterogeneous medium. The best fit model is a north dipping mixed-mode dislocation source lying at ~5km depth. The driving mechanism is ascribable to magma input into the source of the large 1982\u20131984 unrest (since similar source characteristics were inferred) that generates initial inflation followed by additional shear slip accompanying the extension of crack tips. The history and the current state of the system indicate that Campi Flegrei is able to erupt again, and the advanced techniques adopted provide useful information for short-term forecasting

Synergic Use of Multi-Sensor Satellite Data for Volcanic Hazards Monitoring: The Fogo (Cape Verde) 2014–2015 Effusive Eruption

Monitoring volcanic eruptions provides key information for hazard assessment and its time evolution. Satellite remote sensing data are nowadays essential to perform such task, thanks to their capability to survey disastrous events also in remote and under-monitored regions, with frequent revisit time and accurate spatial resolution. Even though satellite imageries are presently used to analyze several phenomena related to eruptions, automatic methods and synergic exploitation of different sensors are rarely considered. In this work, we have analyzed satellite images coming from both synthetic apertureradar(SAR)andopticalsensors,tostudytheeffusiveeruptionofFogovolcano, CapeVerde,whichtookplacebetweenNovember2014andJanuary2015.Inparticular, we have exploited multi-sensor images from Sentinel-1, COSMO-SkyMed, Landsat8, and Earth-Observing-1 missions, to retrieve lava flow patterns and volcanic source parameters related to the eruption. The main outcome of our work is the application of a new automatic change detection technique for estimating the lava field and its temporalevolution,combiningtheSARintensityandtheinterferometricSARcoherence. The innovative algorithm is able to take full advantage of the Sentinel-1 mission’s 6day repeat cycle. Such data are here used for the first time for lava mapping, thereby providing an unprecedented example of using the multi-temporal interferometric SAR (InSAR) coherence to automatically monitor lava flow evolution in emergency phase. This new technique, jointly used with optical satellite images, is capable of resolving with spatial and temporal detail the evolution of lava flows. We have also performed differential SAR interferometry (DInSAR) to map the ground deformation and retrieve the feeding dyke by inverting syn-eruptive signals. Results from source modeling show a SW-NE oriented dyke, located inside Chã das Caldeiras, SW of the Pico do Fogo. Our work highlights how multidisciplinary and satellite open data, along with innovative and automatic processing techniques, may be adopted for real-time hazard estimates in an operational environmentPublishedArticle 221V. Storia eruttivaJCR Journa