Figure - available from: Journal of Geophysical Research: Solid Earth
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(a–f) Seismograms and (g–l) spectrograms of a Ml 1.9 volcano‐tectonic event close to the main craters at 19:11 on 29 August. Panels (a–c and g–i) show the seismometer data and (d–f and j–l) the rotational sensor data for the E, N, and Z component. Note the different amplitude and color scale to aid visual comparison of the events recorded by different sensor types, especially for the spectral density. In panels (a–f) the horizontal lines mark a 4 s window duration for the noise (red) and signal (cyan) in the signal‐to‐noise ratio (SNR) ratio calculation. The mean SNR (Equation 2) can be found on top of the seismograms while we display the SNR for each component (Equation 1) in the right upper corner of each seismogram. In panels (g–l) the red lines mark the frequency band of the SNR calculation.
Source publication
Volcano‐seismic signals such as long‐period events and tremor are important indicators for volcanic activity and unrest. However, their wavefield is complex and characterization and location using traditional seismological instrumentation is often difficult. In 2019 we recorded the full seismic wavefield using a newly developed 3C rotational sensor...
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Citations
... In recent years, several researchers explored and analyzed sixcomponent seismic data for well-specified purposes: to enhance the directional features of an incoming seismic wavefield by using translational and rotational sensors as a "point array" [2,3], to analyze the seismic near field ground motion [4], and to study the rotational component of volcano seismicity [5]. ...
... The spectral amplitude of the gyroscopic signal (in black) shows a larger contribution in the 3-10 Hz band and is comparable to signals recorded by the accelerometer (in red). These observations are consistent with what is found in the literature on the comparison between the signals recorded with accelerometers and those recorded with rotational sensors [2][3][4][5]. Indeed, the comparison between the two types of signals can be used for the directional analysis of the seismic wavefield generated by earthquakes. ...
The real-time monitoring of densely populated areas with high seismic and volcanic risk is of crucial importance for the safety of people and infrastructures. When an earthquake occurs, the Earth surface experiences both translational and rotational motions. The latter are usually not monitored, but their measurement and characterization are essential for a full description of the ground motion. Here we present preliminary observational data of a high-sensitivity rotational sensor based on a 2-km-long fiber-optic Sagnac gyroscope, presently under construction in the middle of the Campi Flegrei Volcanic Area (Pozzuoli, Italy). We have evaluated its performance by analyzing data continuously recorded during an acquisition campaign of five months. The experimental setup was composed of a digital nine-component seismic station equipped with both a rotational sensor and conventional seismic sensors (seismometers, accelerometers, and tiltmeters). During this experiment we detected seismic noise and ground rotations wavefield induced by small to medium local earthquakes ( ${{\rm M}_D}\; \lt \;{3}$ M D < 3 ). The prototype gyroscope shows a very promising sensitivity in the range of $5 \times {10^{- 7}} - 8 \times {10^{- 9}}\,\,{\rm rad}/{\rm s}/\sqrt {{\rm Hz}}$ 5 × 10 − 7 − 8 × 10 − 9 r a d / s / H z over the frequency bandwidth 5 mHz–50 Hz. Future upgrades and perspectives are discussed.
... Rotation rate data from the BS-3A instrument were output in standard miniSEED format and processed using identical routines as used for the translational seismic data, that is, no additional or new processing codes were needed to analyze the rotational data. We note that fiber-optical gyroscope instruments have also recently been successfully used to measure ground rotations in other seismology investigations, for example, with applications in volcanology (Eibl et al., 2022;Wassermann et al., 2022). Although we were able to detect and characterize six modes of vibration of the tower from TC-20 data, rotational measurements from the BS-3A only revealed three modes (compare Figs. 2a,b), likely due to the excitation levels of modes 4-6 not being above detectable limits of the sensor. ...
Modal analysis of freestanding rock formations is crucial for evaluating their vibrational response to external stimuli, aiding accurate assessment of associated geohazards. Whereas conventional seismometers can be used to measure the translational components of normal modes, recent advances in rotational seismometer technology now allow direct measurement of the rotational components. We deployed a portable, three-component rotational seismometer for a short-duration experiment on a 36 m high sandstone tower located near Moab, Utah, in addition to conducting modal analysis using conventional seismic data and numerical modeling. Spectral analysis of rotation rate data resolved the first three natural frequencies of the tower (2.1, 3.1, and 5.9 Hz), and polarization analysis revealed the orientations of the rotation axes. Modal rotations were the strongest for the first two eigenmodes, which are mutually perpendicular, full-height bending modes with horizontal axes of rotation. The third mode is torsional with rotation about a subvertical axis. Measured natural frequencies and the orientations of displacements and rotation axes match our numerical models closely for these first three modes. In situ measurements of modal rotations are valuable at remote field sites with limited access, and contribute to an improved understanding of modal deformation, material properties, and landform response to vibration stimuli.
With the development of rotational seismometers, especially the high‐sensitivity optical seismometers, rotational motions have shown increasing benefits for calculation of dispersion curves, estimation of back azimuth and many other applications. Here we present the six‐component observations of 2019 Hualien mww6.1 earthquake simultaneously on both sides of Taiwan Strait. Seismograms and time‐frequency spectrums show that the attenuations for rotations are more significant than translations. Calculations of the surface wave phase velocity are performed for both stations through single‐station records, indicating a distinct difference owning to the instrument installation conditions and site effect. Comparison of theoretical dispersion curves is consistently in trends with estimations, and reveals the influence of higher‐mode surface waves. For the first time, we locate the source of a earthquake through intersection of two stations' back azimuths estimated through rotational methods. Results of comparing to translational polarization verify that rotational observation can distinctly reduce the deviation of source location.
Volcanic eruptions generate continuous or episodic tremor, which can provide unique information about activity changes during eruption. However, the wealth of information in episodic tremor patterns is often not harvested and transitions between patterns remain obscure. The 2021 Geldingadalir eruption of the Fagradalsfjall Fires, Iceland, is an exceptional case, where the lava effusion caused continuous tremor, and 8696 tremor episodes spanning two orders of magnitude in duration and repose. Based on seismometer and video camera data, we associate several-minute-long, symmetrical episodes with an open vent system, where lava remains in the crater bowl during repose, connected to a shallow magma compartment. Ramp-shaped episodes, lasting several hours, are associated with a temporary closure of the vent system, where no lava remains in the crater bowl during repose and more time is required to resume effusion. The transition from continuous to episodic effusion is related to the cumulative time spent in effusion and repose, and to external factors like crater wall collapses.
