the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Sep 2025
Constraining the wavefield of volcano-seismic events on Mt. Etna, Italy through rotational sensor and array observations
Abstract. Long-period (LP) events and tremor are characteristic seismic signals of active volcanoes, offering insight into underlying fluid-driven processes. Their emergent wavefield is complex and challenging to characterise. Seismic arrays as well as a rotational sensor with a co-located seismometer (6C station) can decipher LP event and tremor wave field composition. This study aims to analyse and compare directional and phase velocity estimates by processing a 25-day long dataset from a rotational sensor and an array of seven broadband stations deployed at Mt. Etna, Italy, in August–September 2019. We derive the back azimuths (BAz) of LP events and tremor from both the seismometer array and the 6C station, and we compare these estimates with a reference BAz obtained from the network locations from the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) on Mt. Etna.
Volcanic tremor occurs in distinct phases with varying seismic and surface activity. Depending on the phase, either the array or 6C method provides reliable BAz estimates, agreeing well with the INGV-OE reference. We find that BAz estimates of both methods are shifted southward relative to the reference location for the LP events. We attribute the larger southward deviation observed in the 6C results to local heterogeneities which exert a stronger influence on the 6C station than on the array.
Based on the array derived slownesses we infer that the tremor and LP events mainly consist of surface waves. Further, the rotational sensor recordings suggest a wavefield dominated by SH-type waves. In combination with the observed temporal evolution of the 6C phase velocity in narrow frequency bands, we infer Love-wave dominance. This study highlights the value of a rotational sensor to constrain the wavefield in a deterministic way in a complex volcanic environment.
Competing interests: One of the co-authors, Gilda Currenti, is an associate editor for the journal.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-4412', Anonymous Referee #1, 26 Oct 2025
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RC2: 'Comment on egusphere-2025-4412', Anonymous Referee #2, 06 Nov 2025
Summary
The authors compare the estimations of backazimuths and phase velocities from array data as well as a rotational sensor (6C) with reference results from the permanent INGV network deriving implications for the dominant wavetype of the recorded LP- and tremor events. Due to the significant complexity of the involved wavefields the authors point out that conventional array recordings often do not allow for a detailed wavefield composition regarding tremor and LP events and this lack of information forms the motivation for this study introducing rotational sensor data.
Reference localisation of tremor and LP-events (INGV) are explained in great detail as well as the derived backazimuth values that are ultimately used for comparison. High-quality figures contain a very high amount of information in very good detail. The authors reveal an interesting discrepancy between backazimuths derived from rotational sensor data compared to traditional array or network methods. The systematic offset observed for the rotational sensor is likely attributed to site effects which are substantial in the heavily scattering medium on Mt Etna’s edifice to which the single rotational sensor would be particularly susceptible. The possibility of wave type mixing is pointed out due to deeper tremor sources and simultaneous surface strombolian activity. Love-wave dominated wave fields are expected for the LP events according to the rotational sensor data. The authors conclude that while the single rotational sensor can not provide reliable information in terms of direction of arrival of tremor or LP signals it is a useful addition to traditional array or network-based analysis as it offers wave field separation. Multiple arrays would improve results significantly as source locations rather than direction of arrival may be obtained while also multiple rotational sensors would reduce effect of heterogeneities.
Some comments/suggestions below
general comments on sections or figures
section 2.2 --- how do different window lengths for calculation of RMS of tremor affect results? The tremor sliding window is relatively long, potentially obscuring shorter time variations. A shorter time window might be an interesting test or alternatively a larger overlap of adjacent windows for better time resolution. As for LP events, would a different 5 second noise window (say 15 seconds before event window instead of 25) affect SNR in a meaningful way or would the distribution of SNR across all events remain roughly the same?
section 2.5 --- the detailed explanation of the array processing may be condensed a little more. Array processing is quite routine and since a reference to more detail is given anyway (line 207) this section could be kept shorter.
Section 3 --- the estimated uncertainty of derived backazimuths is on the same order as reported variations between the 3 methods or some of their changes over time, therefore observed temporal variations or between methods need to be checked in terms of statistical relevance as they may not be significant
Figure 1 --- include reference to fault locations in figure caption
Figure 2 --- colours for tremor locations of P2 and P4 are too similar | in the caption the array center is referred to as “yellow dot” when it is a green square according to legend. “Array centre” could be removed entirely as it covers the symbol for the rotational sensor in plot
Figure 3 --- move legend in panels b, d to respective top left corners to avoid overlap with data | in panels b-d uncertainty bars could be added to legend as well for quicker overview
Figure 4 --- slowness in panel c could be colour-coded according to event altitude as well to better track corresponding data points in panels b and c | in caption remove “The” in last sentence
Figure 6 --- if the subplots could be re-arranged in such a way that the entire figure does not have to be tilted but fits onto the page normally this would improve readability
section 3 --- the listing of all results could be condensed a little to increase overall flow or reading as some parts are a little drawn-out
for all figures (including supplementary material) fontsizes of axes or colorbar labels, ticks and legends could be increased a bit for better readability
suggestions regarding text flow
lines 74-77 --- The aim of this study is to test, for the first time in a volcanic environment, whether the 6C approach provides reliable estimates of back azimuths and velocities compared with those obtained from a conventional seismic array, and whether these results are consistent with reference locations from the Istituto Nazionale di Geofisica e Vulcanologia–Osservatorio Etneo (INGV-OE) network.
line 102 --- Using a rotational sensor Eibl et al. (2022a) have shown, that
lines 114-115 --- For each LP event, we calculated the RMS within a 5-second time window containing the signal as well as the RMS within a 5-second noise window that
line 249 --- just use NEC instead of North East crater as acronym was introduced earlier
line 290 --- 1.6 km altitude, a trend which is statistically significant despite the uncertainties.
line 308 --- remove “the”
line 321 --- the BAz is consistent with
line 348-349 --- to a direction in between the northern and southern craters about 10°-15° further south compared to the INGV reference
line 351 --- but also deviate
line 363 --- remove “furthermore”
line 433 --- However, in this case the distance changes by 0.8 km
line 449 --- In previous studies, LP events at Mt. Etna have been mentioned
line 476 --- which is possibly related to local scattering
line 484 --- The 6C Baz, however, point back in a direction 20° further south, which
Citation: https://doi.org/10.5194/egusphere-2025-4412-RC2 -
EC1: 'Comment on egusphere-2025-4412', Antonella Longo, 08 Nov 2025
The two reviewers already addressed the main issues of the paper, so that no further reviews are needed.
The authors can proceed with the correction phase.
Citation: https://doi.org/10.5194/egusphere-2025-4412-EC1
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- 1
This manuscript presents a detailed analysis of the wavefield excited by tremor and long-period (LP) events associated with the eruptions of Mount Etna, Italy, during August–September 2019. In particular, the authors use an array composed of a rotational sensor and six seismic stations to estimate the back azimuth and phase velocity of seismic waves generated by these events. By comparing the array-derived back azimuths with the source locations of tremor and LP events estimated from INGV-OE routine processing, they demonstrate a high level of agreement during periods of intense tremor activity, whereas discrepancies are observed in the rotational sensor data. The authors attribute these inconsistencies to local structural heterogeneities. Furthermore, combined analysis of the rotational sensor and seismometers reveals that SH waves are dominant in the wavefield of both tremor and LP events. The integration of rotational sensor data with seismic array observations is highly innovative and provides valuable insights for future observations using rotational sensors. Below are several comments that may help improve the manuscript.
Length of the Time Window for Tremor Analysis
In this study, a relatively long time window of 30 minutes was used for tremor analysis. However, the waveform characteristics may vary during such a long period. In cases of non-stationary seismic activity or changes in propagation paths, averaging over this interval may obscure temporal variations. Including supplementary analyses to evaluate the stability of the waveforms within each window would enhance the reliability of the results.
Significance of Back-Azimuth Variations
During phases 0–1, the back azimuth is reported to change from 210° to 190°, but the estimation uncertainty is ±10–20 degrees. Considering this margin of error, a change of about 20 degrees may not be statistically significant, and the interpretation based on this variation should be made with caution.
In addition, the authors note that the back-azimuth estimates derived from different methods (array, 6C method, and INGV network) show different directions across phases 0–2. However, if all values fall within their uncertainty ranges, emphasizing inter-method differences may not be meaningful. Please clarify whether these differences are statistically significant, or at least interpret the results with due consideration of the uncertainties.
Figure 2
In Figure 2, the plotted colors for phases P2 and P4 are quite similar, making them difficult to distinguish, especially in grayscale printing or for readers with color vision deficiencies. Consider using more distinct hues (e.g., blue and red) to improve visual clarity.
Figure 4
In Figures 4c (array-derived slowness) and 4d (6C-derived phase velocity), uncertainties or confidence intervals of the estimated values are not indicated, making it difficult to assess the reliability of the results. When comparing outcomes obtained from different methods, it is essential to evaluate and display these uncertainties. If possible, please include error bars.
Figure 5
In Figure 5d, high correlation coefficients are observed not only during LP-event periods but also at other times. It is unclear whether these correlations correspond to real events or to noise signals. Please provide a clear explanation in the text regarding the possible causes of these high correlations.
Figure 6
Figure 6 contains a large amount of diverse information (temporal changes, spatial distribution, directional deviations, histograms, etc.) within a single figure, making it difficult for readers to follow. The following reorganization is suggested:
Arrange panels (a), (c), and (d) vertically to align their time axes and clarify temporal consistency.
Combine panels (f), (g), and (h), which contain statistical information on back-azimuth deviations, into a separate figure.
Enlarge and reposition the maps (b) and (e) for improved readability.
Figure 7
In Figures 7b and 7c, it is not specified which instruments (array or rotational sensor) and which components (e.g., HHZ, HJZ) the running spectrograms are based on. Please indicate this information clearly in the figure captions or in the main text.