Stratigraphic rhythms synthesized from orbital variations

Previous work on a pelagic stratigraphic sequence in the Middle Cretaceous (Albian) of Italy, about 100 Ma, defined a hierarchy of oscillations. These were identified as variations in carbonate productivity and bottom fauna linked to seafloor aeration. The sequence geometry suggests response to orbitally driven climatic variations, reflecting Berger's precession index, which depicts the precession cycle as a carrier wave modulated by orbital eccentricity. Here we use Berger's astronomic precession index curve for the past 1,500 k.y. in combination with the stratigraphic data to construct a forward model of sedimentation and stratigraphy. The precession index curve serves as a point of departure, and modeling proceeds in three steps: (1) conversion of the precession index into a curve of sedimentation rates through time, using the flux rates calculated from the stratigraphy and applied in a nonlinear way; (2) conversion of that curve into an ideal stratigraphy in which the time dimension is changed into the spatial dimension of stratigraphy; and (3) modification of this stratigraphy by bioturbation as a nonlinear function of seafloor aeration. This computer simulation produces a reasonably good match to the observed stratigraphy. Perhaps more important is the insight gained into changes in the distribution of spectral power; whereas the power of the precession index lies wholly in the precessional terms, that of the stratigraphic sequence lies largely in the eccentricity frequencies. Our model shows how power is transferred from one to the other in each of the three steps. The spectrum of the ultimate stratigraphy synthesized is essentially identical with that of the natural sequence

Stratigraphic rhythms synthesized from orbital variations

Previous work on a pelagic stratigraphic sequence in the Middle Cretaceous (Albian) of Italy, about 100 Ma, defined a hierarchy of oscillations. These were identified as variations in carbonate productivity and bottom fauna linked to seafloor aeration. The sequence geometry suggests response to orbitally driven climatic variations, reflecting Berger's precession index, which depicts the precession cycle as a carrier wave modulated by orbital eccentricity. Here we use Berger's astronomic precession index curve for the past 1,500 k.y. in combination with the stratigraphic data to construct a forward model of sedimentation and stratigraphy. The precession index curve serves as a point of departure, and modeling proceeds in three steps: (1) conversion of the precession index into a curve of sedimentation rates through time, using the flux rates calculated from the stratigraphy and applied in a nonlinear way; (2) conversion of that curve into an ideal stratigraphy in which the time dimension is changed into the spatial dimension of stratigraphy; and (3) modification of this stratigraphy by bioturbation as a nonlinear function of seafloor aeration. This computer simulation produces a reasonably good match to the observed stratigraphy. Perhaps more important is the insight gained into changes in the distribution of spectral power; whereas the power of the precession index lies wholly in the precessional terms, that of the stratigraphic sequence lies largely in the eccentricity frequencies. Our model shows how power is transferred from one to the other in each of the three steps. The spectrum of the ultimate stratigraphy synthesized is essentially identical with that of the natural sequence

Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS−MIROVA Thermal Data Series

In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes

Infrasound array criteria for automatic detection and front velocity estimation of snow avalanches: Towards a real-time early-warning system

Avalanche risk management is strongly related to the ability to identify and timely report the occurrence of snow avalanches. Infrasound has been applied to avalanche research and monitoring for the last 20 years but it never turned into an operational tool to identify clear signals related to avalanches. We present here a method based on the analysis of infrasound signals recorded by a small aperture array in Ischgl (Austria), which provides a significant improvement to overcome this limit. The method is based on array-derived wave parameters, such as back azimuth and apparent velocity. The method defines threshold criteria for automatic avalanche identification by considering avalanches as a moving source of infrasound. We validate the efficiency of the automatic infrasound detection with continuous observations with Doppler radar and we show how the velocity of a snow avalanche in any given path around the array can be efficiently derived. Our results indicate that a proper infrasound array analysis allows a robust, real-time, remote detection of snow avalanches that is able to provide the number and the time of occurrence of snow avalanches occurring all around the array, which represent key information for a proper validation of avalanche forecast models and risk management in a given area

Dynamics of Mount Nyiragongo lava lake inferred from thermal imaging and infrasound array

Abstract Lava lakes provide a direct observation window into processes which usually remain hidden, such as magma convection and outgassing dynamics. We here report a coupled analysis of thermal infrared footage and infrasound array recordings at Mount Nyiragongo (D. R. Congo), and derive a conceptual model of the lava lake's convective system and outgassing mechanism. We suggest that surface flow results from a horizontal pressure gradient at the surface of the lake, driving the crust from high-pressure regions where hot upwelling magma impinges the surface, to low-pressure regions where cold downwelling magma pulls away from the surface. The ascending current of this convection cell carries gas pockets, which once at the surface, are dragged across the lake into downwelling sinks. Such sinks are characterized by persistent chaotic bubble bursting (spattering), whose intensity and position are tracked from infrasound array analysis. Fluctuations of these are observed, but have not been correlated with oscillations of the lava lake level, nor with the variations of surface velocities, both recorded from infrared footage. We also report the activity of a new eruptive vent, which opened early 2016 near an inner circular fracture of the crater's third terrace. We show that the vent's activity was intermittent, alternating between explosive strombolian activity and effusive activity. The latter produced lava flows which spread on the crater's last terrace before cascading into the active lava lake. Although no significant change in the lake behavior was witnessed while the new eruptive vent was active, increased attention should be addressed as this new activity could reflect over-pressurization of the shallow magmatic system. The variety of phenomena captured by this study complements and expands observations reported at other low-viscosity lava lakes, chiefly Kilauea (Hawai'i) and Erta Ale (Ethiopia). Despite Nyiragongo's more vigorous convective regime (where multiple convective cells can operate simultaneously), we suggest that the mechanisms controlling the surface motion and outgassing are similar at all three systems, pointing to generic processes governing the dynamics of low-viscosity lava lakes

Azimuth Estimations From a Small Aperture Infrasonic Array: Test Observations at Stromboli Volcano, Italy

AbstractWe tested the performance of an infrasonic array consisting of three microphones with a 20‐m aperture at Stromboli volcano, Italy. There were four active vents separated by ∼10∘. We employed multiple signal classification (MUSIC) to estimate direction of arrival (DOA) of the detected signals. Using test signals of which the source vents were identified by visual observation, the resolution of DOA estimation of MUSIC is compared with those of Capon beamforming, grid search, and semblance. We confirmed that MUSIC and grid search gave better resolution of DOA than the other two methods. Also, MUSIC provided the best resolutions in time and frequency. It was shown that the DOA switched between different vents or fluctuated in short time scales and can vary with frequency, which indicate multiple active sources. Possible DOA estimation errors were evaluated. A small aperture infrasonic array combined with MUSIC will become a powerful tool for studying and monitoring active volcanoes

Explosions and periodic tremor at Karymsky volcano, Kamchatka, Russia: Explosions and periodic tremor at Karymsky volcano

The explosions of Karymsky volcano often produce signals containing a sequence of repeating pulses recorded on acoustic and seismic sensors, known as chugging. The amplitudes of these pulses correlate with the time interval between pulses. For a given measured acoustic pressure, seismic amplitudes take on arbitrary values up to a specific, empirically determined threshold. Conversely, events with a small seismic amplitude yielded acoustic waves with large variations and large-amplitude seismic events corresponded to large acoustic waves. These observations are not consistent with a source modelled by a resonating conduit. Rather, a model consisting of a sequence of discrete pulses explains the data and provides a framework for understanding the dynamics of degassing at the vent. The physical model for chugging involves a time-varying narrowing vent where gasses are released in a series of oscillations which appear to be harmonic but instead are modelled as short-term transients, or discrete pulses, suggestive of choked flow