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We use seismic ambient noise correlation and coda wave interferometry to estimate velocity variations at high temporal resolution, during the pre‐eruptive period and the onset of the 2018 eruption of Kīlauea volcano. A progressive velocity increase is observed from March to the end of April. It is followed by rapid decrease starting a few days before the onset of the East Rift Zone (ERZ) eruption and then by sharp velocity drop when the eruption started. The change of trend from velocity increase to decrease is progressively delayed by a few days from the summit caldera toward the ERZ. The location of the velocity perturbations shows a migration of the sources of velocity changes from the summit caldera toward the ERZ before the eruption. Using a model of pressure source, we show that the simultaneous caldera inflation and velocity increase probably result from an anisotropic distribution of fault and crack orientations. The velocity decrease could be due to damaging processes above the shallow reservoir and to plastic deformations around the caldera. We introduce a forward model of rock damage associated with the volcano‐tectonic seismicity to calculate the velocity decrease. The good agreement between the calculated and the observed velocity variations shows that a large part of the velocity decrease results from damage of the medium. The delayed onsets of velocity decrease and the source migration of velocity perturbations are probably related to progressive fault openings in the Southern and Eastern parts of the caldera and to magma transfer toward the ERZ. Plain Language Summary: Magma migration from the summit reservoir to the lower East rift zone induced changes in the medium properties of the Kīlauea volcano. Pre‐eruptive seismic velocity variations, measured using ambient noise correlation, were caused by the caldera inflation and damage related to the volcano‐tectonic seismicity. Our work shows that the calculated decrease of velocity using a rock damage model associated with the volcano‐tectonic seismicity provides a good agreement with the observed velocity variations. The delayed onsets of velocity decrease and the source migration of velocity perturbations are probably related to progressive fault openings in the Southern and Eastern parts of the caldera and to magma transfer from the summit reservoir to the ERZ. Key Points: A progressive velocity increase is followed by a rapid decrease delayed by a few days from the caldera toward the East rift zoneThe velocity decrease could be due to damaging processes above the shallow reservoir and to plastic deformations around the calderaThe delayed onsets of velocity decrease and the source migration of velocity perturbations are related to fault openings and magma transfer [ABSTRACT FROM AUTHOR]

On 29 July 1968, there was a violent reactivation of Arenal volcano. The resulting westward-directed lateral blast eruption left two villages destroyed and 78 people dead. The activity continued as a long-lasting, open-vent eruption that evolved into seven recognisable phases reflecting changes in magma supply, explosive activity and cone evolution, and ended in October 2010. Here, we review this activity, the geophysical approaches applied to understanding it and the open questions resulting from these insights. The eruptive dynamics were characterised by almost constant lava effusion, degassing, strombolian and vulcanian explosions and infrequent pyroclastic density currents. In this study, the total rock dense equivalent volume of lava and tephra erupted is calculated at 757 ± 77 Mm3, while the volume of the lava flow field is 527 ± 58 Mm3. Typical seismic activity included harmonic and spasmodic tremors, long-period events and explosion signals with frequent audible "booms". The decline of the eruptive activity started in 2000, with a decrease in the number and size of explosive events, a shift from long to short lava flows along with the collapse of lava flow fronts and the subsequent formation of downward-rolling lava block aprons, the frequent growth of dome-like structures on the summit and a gradual decrease in seismic energy. Multiple geological and geophysical studies during this 42-year-long period of open-vent activity at Arenal resulted in many advances in understanding the dynamics of andesitic blocky lava flows, the origin and diversity of pyroclastic density currents and seismic sources, as well as the role of site effects and rough topography in modifying the seismic wavefield. The acoustic measurements presented here include two types of events: typical explosions and small pressure transients. Features of the latter type are not usually observed at volcanoes with intermediate to evolved magma composition. Explosions have different waveforms and larger gas volumes than pressure transients, both types being associated with active and passive degassing, respectively. This body of data, results and knowledge can inform on the type of activity, and associated geophysical signals, of open-vent systems that are active for decades. [ABSTRACT FROM AUTHOR]

Volcano monitoring and eruption forecasting are based on the observation and joined interpretation of several precursory phenomena. It is thus important to detect new types of precursor and to study their relationship with forthcoming eruptions. In the last years, variations of seismic velocity have been observed in some volcanoes, mainly basaltic, before eruptions. In this paper, we look for velocity variations and waveform decorrelations before the 2014 eruptive sequence of the andesitic Ubinas volcano in Peru. We compute velocity changes by using seismic ambient noise cross-correlation (between pairs of stations) and cross-components correlation (between vertical and horizontal components of single stations), as well as coda wave interferometry of seismic multiplets. With these different approaches, we show that the major explosions that occurred from 13 to 19 April were preceded by a clear velocity decrease and waveform decorrelation. The amplitude of velocity change is generally larger on single-station cross-components correlation than on two-station cross-correlation in all the frequency ranges tested (between 0.1 and 8 Hz). We highlight an apparent anisotropy of velocity change in single-station cross-components correlation, with larger amplitudes when correlating vertical and tangential components than using vertical and radial components with respect to the crater. The Mw = 8.1 Iquique earthquake on 1 April 2014 produced also a marked co-seismic velocity drop detected in a high frequency range(3–5 Hz) in both single-station cross-components correlation and cross-correlations. We locate in the horizontal plane and in depth the velocity perturbation and the structural change related with decorrelation. During the main phase of eruptive activity, the velocity decrease at low frequency (0.1–1 Hz) appears to affect the whole edifice mainly at depth of about 1 to 3 km below the surface. The structural perturbation is more concentrated on the south flank of the volcano, a zone that corresponds to an ancient collapse. We suggest that the observed velocity variations are due to the dilatation of the edifice and to microfracturation induced by magma pressurization. The structural change may be locally enhanced by a possible zone of material weakness in the southern sector. The co-seismic velocity perturbation is located mostly in the southeast flank, at depth smaller than 0.5 to 1 km, and may be related to the presence of the hydrothermal system of the volcano. • Noise correlation functions are calculated both on pairs of stations and on single stations. • Velocity decrease and waveform decorrelation are detected 3 weeks before eruption. • Velocity variations are larger when correlating tangential component than radial. • At higher frequency sharp velocity drop is induced by the M W = 8.1 Iquique earthquake. • Velocity and structural perturbations are located in the edifice at 1–3 km depth below crater. [ABSTRACT FROM AUTHOR]

This paper describes the first step in the dynamical characterization and numerical simulation of an additive manufactured mechanical component under low velocity impact. The mechanical component, was manufactured by a 3D printer (Renishaw AM 250, Renishaw ©) using the selective laser melting process. Accelerometer was placed in the middle of the component, and an impact was applied, recording both impact force and accelerations. Replication of the experimental setup was replicated using the same component manufactured by subtractive process. For the same loading conditions, comparison was conducted in terms of frequencies, accelerations, and damping curves, illustrating first significant differences between the same structure manufactured via different process. Image processing was also conducted via the use of X-ray, providing interesting non-neglectable difference between the two parts. Discussion concerning this study, limitation and openings are also provided, pointing out specific mechanical features that should be taken into account to understand correctly the behavior of additive manufactured mechanical components. [ABSTRACT FROM AUTHOR]

The knowledge of the structure of volcanoes and of the physical properties of volcanic rocks is of paramount importance to the understanding of volcanic processes and the interpretation of monitoring observations. However, the determination of these structures by geophysical methods suffers limitations including a lack of resolution and poor precision. Laboratory experiments provide complementary information on the physical properties of volcanic materials and their behavior as a function of several parameters including pressure and temperature. Nevertheless combined studies and comparisons of field-based geophysical and laboratory-based physical approaches remain scant in the literature. Here, we present a meta-analysis which compares 44 seismic velocity models of the shallow structure of eleven volcanoes, laboratory velocity measurements on about one hundred rock samples from five volcanoes, and seismic well-logs from deep boreholes at two volcanoes. The comparison of these measurements confirms the strong variability of P- and S-wave velocities, which reflects the diversity of volcanic materials. The values obtained from laboratory experiments are systematically larger than those provided by seismic models. This discrepancy mainly results from scaling problems due to the difference between the sampled volumes. The averages of the seismic models are characterized by very low velocities at the surface and a strong velocity increase at shallow depth. By adjusting analytical functions to these averages, we define a generic model that can describe the variations in P- and S-wave velocities in the first 500 m of andesitic and basaltic volcanoes. This model can be used for volcanoes where no structural information is available. The model can also account for site time correction in hypocenter determination as well as for site and path effects that are commonly observed in volcanic structures. [ABSTRACT FROM AUTHOR]

Sabancaya volcano is the youngest and second most active volcano in Peru. It is part of the Ampato-Sabancaya volcanic complex which sits to the south of the ancient Hualca Hualca volcano and several frequently active faults, thus resulting in complex volcano-tectonic interactions. After 15 years of repose, in 2013, a series of 4 earthquakes with magnitude >4.5 occurred within 24 h, marking the beginning of a new episode of unrest. Several additional swarms of earthquakes occurred in the following years until magmatic eruptive activity started on 6 November 2016. This activity is ongoing as of this writing, with an average of 50 explosions per day. In this study, we present results of multiparametric monitoring of Sabancaya's activity observed during 2013–2020. Seismic data are used to create a one-dimensional seismic velocity model, to catalog, locate, and characterize earthquakes, to detect repeating earthquake families, and to monitor seismic velocity variations by ambient noise cross-correlation. These analyses are complemented by visual and remote sensing observations and ground deformation measurements. All monitored parameters showed significant changes on 6 November 2016, the day of eruption onset, thus dividing the eruptive activity into pre-eruptive and eruptive stages. The unrest is characterized by high levels of seismic activity with hundreds of events detected per day. Volcano-tectonic (VT) earthquakes were dominant during the pre-eruptive period while long-period (LP) events and explosions have been most numerous since the eruption onset. Earthquake locations highlight long-lasting seismogenic zones along multiple previously active regional faults, as well as along newly identified faults. This VT seismicity is mainly distributed in a sector from the northwest to the east of the volcanic complex at distances of up to 30 km from the crater. We focus our analysis on two eruptive episodes: the eruption onset and subsequent crater migration from south to north, and the increase of lava dome extrusion rate in 2019. Both episodes are accompanied by seismic velocity decreases of up to 0.2% and are preceded by a few weeks by bursts of distal VT activity, including numerous repeating earthquakes. These repeated events were located on several remote tectonic faults (5–25 km from the vent). We suggest that these phenomena could be due to the injection of a batch of magma in the deep reservoir and/or conduit, which would generate 1) a pressure wave propagating in the hydrothermal system, triggering the bursts of seismic activity and 2) slow rising of magma by melting old material filling the conduit that eventually produced the eruptive and dome growth acceleration events. • Precise source locations were obtained with new velocity model • Many earthquakes, several with magnitude >4, were located on regional faults • Intense seismic activity results from interactions between magmatic processes, tectonic environment, and hydrothermal system • Bursts and repeaters of VT and dVT events were observed before 2016 eruption onset and 2019 increase of dome extrusion rate • Pore pressure waves triggered remote ruptures [ABSTRACT FROM AUTHOR]

We present a study of the seismic velocity variations that occurred in the structure before the large 2010 eruption of Merapi volcano. For the first time to our knowledge, the technique of coda wave interferometry is applied to both families of similar events (multiplets) and to correlation functions of seismic noise. About half of the seismic events recorded at the summit stations belong to one of the ten multiplets identified, including 120 similar events that occurred in the last 20 hr preceding the eruption onset. Daily noise cross-correlation functions (NCF) were calculated for the six pairs of short-period stations available. Using the stretching method, we estimate time-series of apparent velocity variation (AVV) for each multiplet and each pair of stations. No significant velocity change is detected until September 2010. From 10 October to the beginning of the eruption on 26 October, a complex pattern of AVV is observed with amplitude of up to ±1.5 per cent. Velocity decrease is first observed from families of deep events and then from shallow earthquakes. In the same period, AVV with different signs and chronologies are estimated from NCF calculated for various station pairs. The location in the horizontal plane of the velocity perturbations related with the AVV obtained from NCF is estimated by using an approach based on the radiative transfer approximation. Although their spatial resolution is limited, the resulting maps display velocity decrease in the upper part of the edifice in the period 12-25 October. After the eruption onset, the pattern of velocity perturbations is significantly modified with respect to the previous one. We interpret these velocity variations in the framework of a scenario of magmatic intrusion that integrates most observations. The perturbation of the stress field associated with the magma migration can induce both decrease and increase of the seismic velocity of rocks. Thus the detected AVVs can be considered as precursors of volcanic eruptions in andesitic volcanoes, without taking their sign into account. [ABSTRACT FROM AUTHOR]

The 2010 eruption of Merapi is the first large explosive eruption of the volcano that has been instrumentally observed. The main characteristics of the seismic activity during the pre-eruptive period and the crisis are presented and interpreted in this paper. The first seismic precursors were a series of four shallow swarms during the period between 12 and 4months before the eruption. These swarms are interpreted as the result of perturbations of the hydrothermal system by increasing heat flow. Shorter-term and more continuous precursory seismic activity started about 6weeks before the initial explosion on 26 October 2010. During this period, the rate of seismicity increased almost constantly yielding a cumulative seismic energy release for volcano-tectonic (VT) and multiphase events (MP) of 7.5×1010 J. This value is 3 times the maximum energy release preceding previous effusive eruptions of Merapi. The high level reached and the accelerated behavior of both the deformation of the summit and the seismic activity are distinct features of the 2010 eruption. The hypocenters of VT events in 2010 occur in two clusters at of 2.5 to 5km and less than 1.5km depths below the summit. An aseismic zone was detected at 1.5–2.5km depth, consistent with studies of previous eruptions, and indicating that this is a robust feature of Merapi's subsurface structure. Our analysis suggests that the aseismic zone is a poorly consolidated layer of altered material within the volcano. Deep VT events occurred mainly before 17 October 2010; subsequent to that time shallow activity strongly increased. The deep seismic activity is interpreted as associated with the enlargement of a narrow conduit by an unusually large volume of rapidly ascending magma. The shallow seismicity is interpreted as recording the final magma ascent and the rupture of a summit-dome plug, which triggered the eruption on 26 October 2010. Hindsight forecasting of the occurrence time of the eruption is performed by applying the Material Failure Forecast Method (FFM) using cumulative Real-time Seismic Amplitude (RSAM) calculated both from raw records and on signals classified according to their dominant frequency. Stable estimates of eruption time with errors as small as ±4h are obtained within a 6day lapse time before the eruption. This approach could therefore be useful to support decision making in the case of future large explosive episodes at Merapi. [ABSTRACT FROM AUTHOR]

Passive seismic interferometry has become a popular technique towards monitoring. The method depends on the relative stability of background seismic sources in order to make repeatable measurements of subsurface properties. Such stability is typically assessed by examining the similarity of cross-correlation functions through time. Thus, techniques that can better assess the temporal similarity of cross-correlation functions may aid in discriminating between real subsurface processes and artificial changes related variable seismic sources. In this study, we apply agglomerative hierarchical clustering to cross-correlation functions computed using seismic networks at two volcanoes. This allows us to form groups of data that share similar characteristics and also, unlike common similarity measures, does not require a defined reference period. At Piton de la Fournaise (La Réunion island), we resolve distinct clusters that relate both to changes in the seismic source (volcanic tremor onset) and changes in the medium following volcanic eruptions. At Mt Ruapehu (New Zealand), we observe a consistency to cross-correlation functions computed in the frequency band of volcanic tremor, suggesting tremor could be useful as a repeatable seismic source. Our results demonstrate the potential of hierarchical clustering as a similarity measure for cross-correlation functions, suggesting it could be a useful step towards recognizing structure in seismic interferometry data sets. This can benefit both decisions in processing and interpretations of observed subsurface changes. [ABSTRACT FROM AUTHOR]

Abstract: The computer program presented in this note applies methods commonly used in volcano seismology to the analysis of seismic data. It is complementary to the classic seismological software packages used to process tectonic earthquake seismograms. The program''s six user-friendly interfaces provide a large set of tools for reading data in many different formats, for carrying out spectral analysis, autoregressive modelling and deconvolution, for calculating time–frequency representations and Real-time Seismic Amplitude Measurement (RSAM)-type time series, and for detecting volcanic tremors and discrete events in long-duration records. A separate version of the program facilitates signal classification when preparing training databases for automatic recognition systems. [Copyright &y& Elsevier]

Abstract: The implementation of fuel cells (FC) in transportation systems, as airplanes, requires some better understanding and mastering of their mechanical behaviours in vibrating environments. To this end, a FC stack is tested on a vibrating platform and characterised on the three geometric axes of the equipment. The impacts over the stack assembly of sine excitations with different frequencies and magnitudes are estimated using various accelerometers placed on different locations of the FC surface. Leak checks are also performed in order to verify that no malfunctions occur in the stack. In this first part, some descriptions concerning the test facilities and the experimental setup are given, as well as some information about the mechanical test procedure applied. Some frequency – acceleration diagrams resulting from the experiments are shown and analysed. Finally, some assessments concerning the stack behaviour in vibrating conditions are made. [Copyright &y& Elsevier]

Abstract: Typical records of volcanic tremor and explosion quakes at Arenal volcano are analyzed with a high-resolution time-frequency method. The main characteristics of these seismic signals are: (1) numerous regularly spaced spectral peaks including both odd and even overtones; (2) frequency gliding in the range [0.9–2] Hz of the fundamental peak; (3) frequency jumps with either positive or negative increments; (4) tremor episodes with two simultaneous systems of spectral peaks affected by independent frequency gliding; (5) progressive transitions between spasmodic tremor and harmonic tremor; (6) lack of clear and systematic relationship between the occurrence of explosions and tremor. Some examples of alternation between two states of oscillation characterized by different fundamental frequencies are also observed. Some tremor and explosion codas are characterized by acoustic and seismic waves with identical spectral content and frequency gliding, which suggests a common excitation process. We propose a source model for the tremor at Arenal in which intermittent gas flow through fractures produces repetitive pressure pulses. The repeating period of the pulses is stabilized by a feedback mechanism associated with standing or traveling waves in the magmatic conduit. The pressure pulses generate acoustic waves in the atmosphere and act as excitation of the interface waves in the conduit. When the repeating period of the pulses is stable enough, they produce regularly spaced spectral peaks by the Dirac comb effect and hence harmonic tremor. When the period stability is lost, because of failures in the feedback mechanism, the tremor becomes spasmodic. The proposed source model of tremor is similar to the sound emission process of a clarinet. Fractures in the solid or viscous layer capping the lava pool in the crater act as the clarinet reed, and the conduit filled with low velocity bubbly magma is equivalent to the pipe of the musical instrument. The frequency gliding is related to variations of the pressure in the conduit, which modify the gas fraction, the wave velocity and, possibly, the length of the resonator. Moreover, several observations suggest that two seismic sources, associated with two magmatic conduits, are active in Arenal volcano. They could explain in particular the apparent independence of tremor and explosions and the episodes of tremor displaying two simultaneous systems of spectral peaks. [Copyright &y& Elsevier]

Abstract: We use the spatial autocorrelation (SPAC) method with improved inversion algorithms to estimate the Love and Rayleigh dispersion curves at two sites at the West and Northeast flanks of Arenal volcano, Costa Rica. At the West flank site, the Rayleigh waves phase velocities vary from 765 m s−1 at 1 Hz to 300 m s−1 at 12 Hz and those of Love waves between 780 and 295 m s−1 in the same frequency band. At the Northeast flank site, the Rayleigh wave velocities range from 1386 to 300 m s−1 and those of Love from 1983 to 315 m s−1. From dispersion curves we derive shallow (<400 m) P and S waves velocity models. 2D velocity models down to a depth of 150 m are also obtained by seismic refraction surveys along two radial profiles on the tephra apron at West and East flanks. They present strong vertical and lateral variations in the velocity and thickness of the layers. Strong variations in amplitude of the spectral peaks are observed for the seismic events along two radial arrays. These site effects are analysed using the H/V spectral ratio method and S-wave theoretical transfer functions. Results show that the wave amplifications are related to resonance effects of shallow structure (<150 m) and occur only where impedance contrast with the deeper layers is strong enough. In contrast, almost no site effect are detected at the Masaya shield volcano, Nicaragua, where the structure is more homogeneous and mainly composed of lava flows. When a resonance of the shallow layers occurs, the correlation coefficients between close stations increase at the corresponding frequency. The site effects may thus produce spurious results with the SPAC method. The H/V spectral ratio, used in complement of the SPAC method, can help detecting the site effects and testing the plane layer hypothesis. Furthermore, the theoretical transfer functions calculated for the estimated velocity models is also useful to validate the models. [Copyright &y& Elsevier]

Volcanic tremor and long-period (LP) events are characterized by sharp spectral peaks that generally result from resonance effects at the source and which concentrate most of the radiated energy. The understanding of these seismovolcanic phenomena requires good descriptions of the distribution in time and frequency of the different spectral components included in the signals, as well as a separation of the resonance effects from less energetic effects such as excitation and propagation. We address the issue of extracting from individual records information as detailed as possible on the physical processes involved at the source. We introduce and compare several time–frequency analysis methods, and we describe the application of autoregressive modeling and deconvolution methods to the characterization and separation of the main spectral components. We propose a signal analysis approach based on the joint use of a set of complementary methods, and we present applications to several examples of volcanic tremor and LP events. The time–frequency analysis of some of the LP events taken as examples reveals short-duration components at the seismogram onsets with energy concentrated at frequencies either higher or lower than the main resonance frequencies. These seismic phases are probably related to the excitation processes of the volcanic resonators. In several cases, the arrival of the main spectral peak has a delay of a few tenths of a second with respect to the first arrival. The residual signals obtained by deconvolving and eliminating the main spectral components contain information about the excitation, such as duration, delay, or frequency band. The residual signals are short for LP events, and continuous for volcanic tremor. The autoregressive modeling of the sample records gives precise estimations of the frequency and quality factor of the main spectral peaks. The measured parameters cover a wide range of values, which is consistent with the great variety of fluids filling resonating cavities in volcanoes. [Copyright &y& Elsevier]

Volcano acoustic signals contain valuable information on shallow magmatic and hydrothermal processes. In some cases, the detection of acoustic waves is the only clear evidence of the occurrence of volcanic explosions. Their study is thus complementary to that of seismic signals. For this reason, acoustic sensors are more and more frequently integrated in volcano monitoring systems as well as in temporary instrumental deployments. We have developed a broadband, robust and low-cost infrasound sensor designed for the detection and analysis of acoustic waves on volcanoes. It is based on a microelectromechanical differential pressure transducer (MEMS). The reference pressure is balanced with the atmospheric pressure through a pneumatic high-pass filter. Its low corner frequency, usually set to 60 mHz, can be adjusted from a few to tens of mHz. Its amplitude range is ±240 Pa and its sensitivity is 20 mV Pa−1, with a noise level <0.05 Pa RMS. The power consumption is 42 mW (3.5 mA with 12 V voltage). A direct output of the MEMS also provides a signal with sensitivity of about 500 μV Pa−1 and range ± 1245 Pa. This sensor is not sensitive to mechanical vibrations. The instrumental response of each infrasound sensor is carefully measured from 1 mHz to >100 Hz using two specially designed calibration systems which deliver sinusoidal pressure variations. The mechanical elements of the sensor are produced by 3D printer and filled with epoxy resin which guarantees high robustness in the aggressive environment of most volcanoes. The sensor dimensions (26x45x80 mm) and weight (100 g) makes it very easy to handle and install. • An infrasound sensor was especially designed for volcano monitoring and studies. • Amplitude range ± 240 Pa, sensitivity 20 mV Pa−1, noise level < 0.05 Pa RMS. • Instrumental response and sensitivity to vibrations are precisely determined. • Simple calibration devices and vibrating platform are presented. [ABSTRACT FROM AUTHOR]

Modern seismic networks provide a huge amount of data received in real-time, being impossible the manual identification of relevant events useful to monitor the activity of the volcano. Thus, many volcano observatories areinterested in tools to perform an online, automatic analysis of the seismic activity. Machine Learning area provides various of Volcano-Seismic Recognition (VSR)systems designed to classify seismic events in real-time. However, only a few approaches can also detect them in a continuous data streams. Most of those VSR systems are based on the 2-step supervised paradigm: 1. A training database (X-DB) of a given volcano 'X' is prepared with hundreds of events manually detected and classified according to their physical origin.2. Statistical models are built analysing this DB, and are later used to automatically identify events in new data recorded at the volcano X.This supervised procedure is the major drawback to achieve a fast deploymentof a VSR system for another volcano Y, as the preparation of its own Y-DB takes considerable time, and requires qualified operators and previous recordings, which is difficult for volcanoes without recent activity or which haven't been monitored.In order to overcome these limitations, the EU-funded project 'VULCAN.ears'focused on real-time, Volcano-Independent VSR (VI.VSR) approaches. It proposes alternative solutions based on state-of-the-art technologies as universal DBs and models, waveform standardisation and parallel architectures. Recent results obtained by mixing DBs from Popocatépetl, Colima, Deception and Arenal active volcanoes will be presented. We apply VULCAN.ears technologies to evaluate VSR systems on joint DBs built with data of several volcanoes. We also use volcano-independent models to automatically classify events of another volcano, analysing how the recognition accuracy varies as the training DB becomes more complex. All tests are carried out by an easy to use, user-friendly graphical application (geoStudio).All these achievements produce new insights useful to redesign the next-generation, portable and robust VSR systems. [ABSTRACT FROM AUTHOR]

• Turrialba volcano slowly transitioned from a closed- (2010) to an open-vent system (2017). • Seismic tremor decreases precede eruptive phases at Turrialba volcano. • Pre-eruptive tremor abatement is accompanied with SO 2 flux decrease. • Chromatic signals are common seismic precursors (e.g. tornillos, harmonic tremor). • Magnitude 5.5 earthquake correlates with the transition to an open-vent system. Turrialba is a stratovolcano located at the easternmost part of the Costa Rican volcanic front. After remaining quiescent for more than a century, in 1996 it started to show signs of unrest, until a first phreatomagmatic explosion occurred on January, 2010. Since then, the activity evolved from phreatic to magmatic, in a series of distinct eruptive phases. In this paper, we investigate the seismic records that span the whole eruptive process (2010-present), in order to identify precursory signals and characterize the volcanic evolution. A long-term analysis was carried out based on the continuous records, as well as seismic catalogs (volcano-tectonic seismicity, harmonic tremor, etc.). In addition, the gradual character of the evolution of this eruption allowed for the analysis of independent precursory stages. Thus, we inspected in detail the most important of those periods, particularly, prior to the first 2010 phreatomagmatic eruption, and prior to the 2016 transition to an open vent system. Temporary tremor amplitude decreases were found to precede most of the eruptive phases. In total, 9 pre-eruptive tremor abatement periods were identified spanning several days (5–44), which often concurred with a decrease in the SO 2 flux. The analysis of the volcano-tectonic seismicity highlights the migration of magma from a deep (6–10 km) reservoir beneath the neighboring Irazú volcano towards Turrialba volcano, especially between the years 2015 and 2016. This activity peaked on December 2016 when a Mw 5.5 earthquake took place between both volcanoes. Harmonic tremor episodes thrived in the later phase when the system finally opened (2017–2018). In the short-term, compounded tonal seismic signals were identified as precursor events, such as long-period events followed by harmonic tremor or by a multichromatic coda similar to tornillo-type events. The co-occurrence of tremor amplitude decreases and tonal seismic signals is interpreted to be caused by a sealing of the hydrothermal system, which blocked the circulation of fluids and permitted the resonances in the inner cavities. This process leaded to pressure accumulation and the consequent eruptions. Thus, trough a series of cycles of sealing and rupture the system of conduits gradually opened. The seismic characterization of this eruption constitutes insightful knowledge useful for monitoring and risk assessment purposes. [ABSTRACT FROM AUTHOR]

Abstract: An array of ten broadband stations was installed on the Popocatépetl volcano (Mexico) for four months between October 2002 and February 2003. 26 regional and teleseismic earthquakes were selected and filtered in the frequency time domain to extract the fundamental mode of the Rayleigh wave. The average dispersion curve was obtained in two steps. Firstly, phase velocities were measured in the period range [2–50] s from the phase difference between pairs of stations, using Wiener filtering. Secondly, the average dispersion curve was calculated by combining observations from all events in order to reduce diffraction effects. The inversion of the mean phase velocity yielded a crustal model for the volcano which is consistent with previous models of the Mexican Volcanic Belt. The overall crustal structure beneath Popocatépetl is therefore not different from the surrounding area, and the velocities in the lower crust are confirmed to be relatively low. Lateral variations of the structure were also investigated by dividing the network into four parts and by applying the same procedure to each sub-array. No well-defined anomalies appeared for the two sub-arrays for which it was possible to measure a dispersion curve. However, dispersion curves associated with individual events reveal important diffraction for 6 s to 12 s periods which could correspond to strong lateral variations at 5 to 10 km depth. [Copyright &y& Elsevier]