526 research outputs found
Seismic site effects estimation from experimental time series: what can innovative dynamical systems and time series analysis techniques offer?
No full textS-wave velocity zones at the Irazú Volcano (Costa Rica)
No full textThe Irazú Volcano (83°51′09″ W, 9°58′45″ N) is located in the middle portion of Costa Rica, close to a highly populated area, and is one of the largest volcanoes in Central America. The knowledge of the nature and characteristics of the crust under a volcano like this is important in order to interpret the roots of the volcano and its reservoirs. Based on the data from two seismic monitoring stations located at the Irazú edifice, the analysis of receiver functions obtained, and the study of the calculated S-wave velocity models by inversion of P-wave receiver functions of teleseismic events, we interpret the existence of low-velocity layers under the Irazú volcano, located at a depth between 10 and 30 km. In the same way, we interpret high velocity zones as caused by intrusive bodies related to the ancient Irazú volcanic cycles. We confirm these interpretations based on the petrogenetic results from previous scientific sources and their integration with the models presented here. In order to get information about the nature and dimensions of the low- and high-velocity layers, we correlate velocity profiles and results show irregular and tilted shapes in agreement with present and ancient magma reservoirs.Fil: Villegas Alvarez, Raquel Judith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Ciencias de la Tierra. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones en Ciencias de la Tierra; ArgentinaFil: Petrinovic, Ivan Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigaciones en Ciencias de la Tierra. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Investigaciones en Ciencias de la Tierra; ArgentinaFil: Carniel, Roberto. Universita Di Udine.; Itali
Towards assessing the Adriatic Sea coastal vulnerability to regional climate change scenarios: preliminary results
No full textPreliminary results from numerical climate simulations of the Adriatic sea at
high resolution (1/25°), performed during two time-slice integrations, are presented
for the period 1960-90 and the 21st century (2070-2100), according to the “A1b”
scenario defined by IPCC.
This aims at addressing the feasibility of downscaling procedure in a regional basin,
resolving features that are generally still not included when using global models and
gaining useful indications on climate-change induced impacts on the wave climate
and ocean circulation.
For this purpose, a fully coupled version of the ROMS-SWAN model has been implemented,
using interpolated meteorological forcings from the SINTA Project (SImulations
of climate chaNge in the mediTerranean Area, a joint scientific cooperation
of CMCC-INGV-Univ. of Belgrade).
Within the Impacts on Soil and Water Division (ISC) of the CMCC, the numerical
downscaling approach is integrated in a GIS-based Decision Support System
(DSS) aimed at the integrated analysis of climate change impacts and risks on coastal
zones at the regional, aimed at guiding decision-makers in the definition of adaptation
strategies.
Despite further experiments are needed to reach definitive results, the outcomes indicate
the feasibility of the numerical downscaling approach; nevertheless, they also
highlight uncertainties intrinsic to this approach that may be leading, at least at the
present state of the art, to results of difficult interpretation.CNR-ISMARPublished3.7. Dinamica del clima e dell'oceanoope
Towards validating a last generation, integrated wave-current-sediment numerical model in coastal regions using video measurements
No full textAbstract
This paper presents the first steps in the implementation of a morphological numerical model to be applied in the Bevano River region, a shallow water area in the Adriatic Sea, with the aim of helping the identification and assessment of erosional patterns and bottom morphological modifications induced by severe marine storms. The numerical modeling, performed using a fully 3D coupled wave-current-sediment version of the ROMS model, has been complemented with in situ data analysis and observations: a first qualitative validation of the results was given by the analysis of images acquired via an ARGUS video station.
Hydrodynamic modeling highlighted how shear bottom stresses and bottom currents fields were heavily influenced by severe storm situations, and had large effects on the morphology of shallow regions. The correlation between the wave-current induced bottom stresses and the resulting topography was investigated. Nearshore hydrodynamics modeling results demonstrated the dominant role played by alongshore sediment transport, with the magnitude of both cross- and along-shore wave-induced currents strongly depending on wave height and direction.
We found a good qualitative conformity between the results of the numerical models applied during a “Bora” storm and the corresponding video observations; both techniques indicated the migration of the existing sandbar within the range of about 40 m seaward.
Results show how integrated numerical open source tools, often used in oceanography, are becoming suitable for both preliminary investigations and for planning the effective littoral management, and how their calibration can be supported by the use of new low cost techniques, such as video measurements.</jats:p
Towards assessing the Adriatic Sea coastal vulnerability to regional climate change scenarios: preliminary results
No full textPreliminary results from numerical climate simulations of the Adriatic sea at
high resolution (1/25°), performed during two time-slice integrations, are presented
for the period 1960-90 and the 21st century (2070-2100), according to the “A1b”
scenario defined by IPCC.
This aims at addressing the feasibility of downscaling procedure in a regional basin,
resolving features that are generally still not included when using global models and
gaining useful indications on climate-change induced impacts on the wave climate
and ocean circulation.
For this purpose, a fully coupled version of the ROMS-SWAN model has been implemented,
using interpolated meteorological forcings from the SINTA Project (SImulations
of climate chaNge in the mediTerranean Area, a joint scientific cooperation
of CMCC-INGV-Univ. of Belgrade).
Within the Impacts on Soil and Water Division (ISC) of the CMCC, the numerical
downscaling approach is integrated in a GIS-based Decision Support System
(DSS) aimed at the integrated analysis of climate change impacts and risks on coastal
zones at the regional, aimed at guiding decision-makers in the definition of adaptation
strategies.
Despite further experiments are needed to reach definitive results, the outcomes indicate
the feasibility of the numerical downscaling approach; nevertheless, they also
highlight uncertainties intrinsic to this approach that may be leading, at least at the
present state of the art, to results of difficult interpretation.CNR-ISMARPublished3.7. Dinamica del clima e dell'oceanoope
Seismic characteristics of lava lake convection at Erta Ale, Ethiopia
No full textAnalysis of thermal, seismic, and video data, collected between 17 and 19 February, 2002, reveals that Erta Ale lava lake cycles between low (~0.03 m s -1 ) and high (~0.1 m s -1 ) convective regimes, with 60 to 220 minute periods. We attempt to characterize the seismic signature of each convective regime using spectral content, polarization analysis, and amplitude-based location of the continuous tremor.
We identify the distinguishing spectral characteristics of each convective regime from continuous spectrograms. This information, combined with the covariance analysis method of Jurkevics (1988), is used to analyze the wavefield composition.
For both convective regimes, we find tha t the wavefield from 0.85-3 Hz is dominated by rectilinear polarization, with azimuths and angles of incidence most consistent with P waves. At higher frequencies, for both convective regimes, the wavefield becomes more complex, and planar polarization dominates, suggesting that the higher frequency energy is mostly comprised of scattered S and Rayleigh waves. Because the majority of energy is concentrated at the lower frequencies, where body waves dominate, we assume an isotropic source, and locate windows of tremor from each convective regime with a method based on Gottsch�mer and Surono (2000).
Our modified method uses least-squares inversion, based on tremor amplitudes recorded at three separate 3-component stations, to determine tremor epicenters and source power. By dividing each time window into shorter segments, and locating each segment of data, we find that the tremor source regions obtained for the low and high convective phases differ significantly. We also find a weak relationship between average frequency and tremor location. The similar wavefield composition of both convective phases suggests that they may share a common source process. However, their locations argue strongly that the source process is not only non-stationary, but is distributed over a small, unique volume for each of the two convective phases
Machine Learning in Volcanology: A Review
No full textA volcano is a complex system, and the characterization of its state at any given
time is not an easy task. Monitoring data can be used to estimate the probability
of an unrest and/or an eruption episode. These can include seismic, magnetic,
electromagnetic, deformation, infrasonic, thermal, geochemical data or, in an ideal
situation, a combination of them. Merging data of different origins is a non-trivial
task, and often even extracting few relevant and information-rich parameters from
a homogeneous time series is already challenging. The key to the characterization
of volcanic regimes is in fact a process of data reduction that should produce
a relatively small vector of features. The next step is the interpretation of the
resulting features, through the recognition of similar vectors and for example,
their association to a given state of the volcano. This can lead in turn to highlight
possible precursors of unrests and eruptions. This final step can benefit from the
application of machine learning techniques, that are able to process big data in an
efficient way. Other applications of machine learning in volcanology include the
analysis and classification of geological, geochemical and petrological “static” data
to infer for example, the possible source and mechanism of observed deposits, the
analysis of satellite imagery to quickly classify vast regions difficult to investigate
on the ground or, again, to detect changes that could indicate an unrest. Moreover,
the use of machine learning is gaining importance in other areas of volcanology,
not only for monitoring purposes but for differentiating particular geochemical
patterns, stratigraphic issues, differentiating morphological patterns of volcanic
edifices, or to assess spatial distribution of volcanoes. Machine learning is helpful
in the discrimination of magmatic complexes, in distinguishing tectonic settings of
volcanic rocks, in the evaluation of correlations of volcanic units, being particularly
helpful in tephrochronology, etc. In this chapter we will review the relevant methods
and results published in the last decades using machine learning in volcanology,
both with respect to the choice of the optimal feature vectors and to their subsequent
classification, taking into account both the unsupervised and the supervised
approaches
SHORT ANALYSIS OF RAINFALL TRENDS IN FRIULI-VENEZIA-GIULIA FROM 1951 TO 1986
No full textAnnual and seasonal rainfall data taken in the period 1951-1986 have been spatially averaged over the region Friuli-Venezia Giulia and analysed with the aim of searching for the presence of trends. The results of the two rank tests recommended by the World Meteorological Organization (WMO) support the hypothesis of a decreasing trend in the autumn rainfall and, with less probability, an increasing trend in sprin
Precipitation distribution in Friuli - Venezia Giulia: average amounts and cluster analysis
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