Oth, Adrien

As part of the community stress-drop validation study initiative, we apply a spectral decomposition approach to isolate the source spectra of 556 events occurred during the 2019 Ridgecrest sequence (Southern California). We perform multiple decompositions by introducing alternative choices for some processing and model assumptions, namely: three different S-wave window durations (i.e., 5 s, 20 s, and variable between 5 and 20 s); two attenuation models that account differently for depth dependencies; and two different site amplification constraints applied to restore uniqueness of the solution. Seismic moment and corner frequency are estimated for the Brune and Boatwright source models, and an extensive archive including source spectra, site amplifications, attenuation models, and tables with source parameters is disseminated as the main product of the present study. We also compare different approaches to measure the precision of the parameters expressed in terms of 95% confidence intervals (CIs). The CIs estimated from the asymptotic standard errors and from Monte Carlo resampling of the residual distribution show an almost one-to-one correspondence; the approach based on model selection by setting a threshold for misfit chosen with an F-ratio test is conservative compared to the approach based on the asymptotic standard errors. The uncertainty analysis is completed in the companion article in which the outcomes from this work are used to compare epistemic uncertainty with precision of the source parameters.

As part of the community stress‐drop validation study, we evaluate the uncertainties of seismic moment M0 and corner frequency fc for earthquakes of the 2019 Ridgecrest sequence. Source spectra were obtained in the companion article by applying the spectral decomposition approach with alternative processing and model assumptions. The objective of the present study is twofold: first, to quantify the impact of different assumptions on the source parameters; and second, to use the distribution of values obtained with different assumptions to estimate an epistemic contribution to the uncertainties. Regarding the first objective, we find that the choice of the attenuation model has a strong impact on fc results: by introducing a depth‐dependent attenuation model, fc estimates of events shallower than 6 km increase of about 10%. Also, the duration of the window used to compute the Fourier spectra show an impact on fc ⁠: the average ratio between the estimates for 20 s duration to those for 5 s decreases from 1.1 for Mw<3 to 0.66 for Mw>4.5. For the second objective, we use a mixed‐effect regression to partition the intraevent variability into duration, propagation, and site contributions. The standard deviation ϕ of the intraevent residuals for log(fc) is 0.0635, corresponding to a corner frequency ratio 102ϕ=1.33. When the intraevent variability is compared to uncertainties on log(fc), we observe that 2ϕ is generally larger than the 95% confidence interval of log(fc), suggesting that the uncertainty of the source parameters provided by the fitting procedure might underestimate the model‐related (epistemic) uncertainty. Finally, although we observe an increase of log(Δσ) with log(M0) regardless of the model assumptions, the increase of Δσ with depth depends on the assumptions, and no significant trends are detected when depth‐dependent attenuation and velocity values are considered.

Classical mechanisms of volcanic eruptions mostly involve pressure buildup and magma ascent towards the surface1. Such processes produce geophysical and geochemical signals that may be detected and interpreted as eruption precursors1-3. On 22 May 2021, Mount Nyiragongo (Democratic Republic of the Congo), an open-vent volcano with a persistent lava lake perched within its summit crater, shook up this interpretation by producing an approximately six-hour-long flank eruption without apparent precursors, followed-rather than preceded-by lateral magma motion into the crust. Here we show that this reversed sequence was most likely initiated by a rupture of the edifice, producing deadly lava flows and triggering a voluminous 25-km-long dyke intrusion. The dyke propagated southwards at very shallow depth (less than 500 m) underneath the cities of Goma (Democratic Republic of the Congo) and Gisenyi (Rwanda), as well as Lake Kivu. This volcanic crisis raises new questions about the mechanisms controlling such eruptions and the possibility of facing substantially more hazardous events, such as effusions within densely urbanized areas, phreato-magmatism or a limnic eruption from the gas-rich Lake Kivu. It also more generally highlights the challenges faced with open-vent volcanoes for monitoring, early detection and risk management when a significant volume of magma is stored close to the surface.

Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. Although the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This quiet period provides an opportunity to detect subtle signals from subsurface seismic sources that would have been concealed in noisier times and to benchmark sources of anthropogenic noise. A strong correlation between seismic noise and independent measurements of human mobility suggests that seismology provides an absolute, real-time estimate of human activities.

Volcano infrasound is an important component of multi-disciplinary volcano geophysics and has proven utility for tracking eruptive activity and quantifying eruption dynamics. Unfortunately, a major limitation in our interpretation of volcano infrasound is that it is critically affected by the morphology of the volcanic crater, which can transform potentially simple source-time functions occurring within the crater into a signal that is substantially more complex. If infrasound waveforms are to be used to recover important physical parameters about an eruption source, then a robust understanding of the acoustic response of the crater is required. In many cases, and especially for large deep craters, the acoustic response function acts as a severe filter. For example, at Cotopaxi Volcano (Ecuador) infrasound ‘tornillos’ with an impulsive onset and peaked spectra at 0.2 Hz decaying for more than 90 s are part of the source response due to the crater’s steep-walled, deep crater. We analyze broadband infrasound data from open-vent volcanoes with a wide variety of crater geometries and jointly calculate their crater acoustic response using 1-D (axisymmetric) and 3-D morphologies derived from structure-from-motion digital terrain models. We analyze both explosion and lava lake infrasound from Villarrica (Chile), Stromboli (Italy), and Nyiragongo (Democratic Republic of the Congo) to demonstrate a broad spectrum of volcano infrasound, whose attributes are heavily influenced by crater shape. We demonstrate how some differences between simulations and recorded explosion are influenced by sourcetime functions, which may range from brief and impulsive to complicated or extended in time. Numerical modeling shows that each volcanic crater has a unique impulse response and that deconvolving this acoustic response is vital for estimating important eruption parameters including the size of volcanic explosions.

In this study we derive a spectral model describing the source, propagation and site characteris- tics of S waves recorded in central Italy. To this end, we compile and analyse a high-quality data set composed of more than 9000 acceleration and velocity waveforms in the local magnitude (Ml) range 3.0–5.8 recorded at epicentral distances smaller than 120 km. The data set spans the time period from 2008 January 1 to 2013 May 31, and includes also the 2009 L’Aquila (moment magnitude Mw 6.1, Ml = 5.8) sequence. This data set is suitable for the application of data-driven approaches to derive the empirical functions for source, attenuation and site terms. Therefore, we apply a non-parametric inversion scheme to the acceleration Fourier spectra of the S waves of 261 earthquakes recorded at 129 stations. In a second step, with the aim of defining spectral models suitable for the implementation in numerical simulation codes, we represent the obtained non-parametric source and propagation terms by fitting standard parametric models. The frequency-dependent attenuation with distance r shows a complex trend that we parametrize in terms of geometrical spreading, anelastic attenuation and high- frequency decay parameter k. The geometrical spreading term is described by a piecewise linear model with crossover distances at 10 and 70 km: in the first segment, the spectral ordi- nates decay as r −1.01 while in the second as r −1.68 . Beyond 70 km, the attenuation decreases and the spectral amplitude attenuate as r −0.64 . The quality factor Q(f ) and the high-frequency attenuation parameter k, are Q( f ) = 290 f 0.16 and k = 0.012 s, respectively, the latter being applied only for frequencies higher than 10 Hz. The source spectra are well described by ω2 models, from which seismic moment and stress drops of 231 earthquakes are estimated. We calibrate a new regional relationship between seismic moment and local magnitude that im- proves the existing ones and extends the validity range to 3.0–5.8. We find a significant stress drop increase with seismic moment for events with Mw larger than 3.75, with so-called scaling parameter ε close to 1.5. We also observe that the overall offset of the stress-drop scaling is controlled by earthquake depth. We evaluate the performance of the proposed parametric models through the residual analysis of the Fourier spectra in the frequency range 0.5–25 Hz. The results show that the considered stress-drop scaling with magnitude and depth reduces, on average, the standard deviation by 18 per cent with respect to a constant stress-drop model. The overall quality of fit (standard deviation between 0.20 and 0.27, in the frequency range 1–20 Hz) indicates that the spectral model calibrated in this study can be used to predict ground motion in the L’Aquila region.

We thank Igor B. Morozov for his interest in our article and for his comment (Morozov 2011) regarding the non-parametric attenuation curves for the Irpinia–Basilicata region obtained by generalized spectral inversion (Cantore et al. 2011). Morozov's comment has its root in a new model proposed by Morozov (2008, 2010) for the interpretation of seismic attenuation data, where the author comes to the conclusion that the typically used geometrical spreading terms are oversimplified and argues in favor of a new geometrical spreading ...

We exploit S-wave spectral amplitudes from 112 aftershocks (3.0 ≤ ML ≤ 5.3) of the L’Aquila 2009 seismic sequence recorded at 23 temporary stations in the epicentral area to estimate the source parameters of these events, the seismic attenuation characteristics and the site amplification effects at the recording sites. The spectral attenuation curves exhibit a very fast decay in the first few kilometers that could be attributed to the large attenuation of waves traveling trough the highly heterogeneous and fractured crust in the fault zone of the L’Aquila mainshock. The S-waves total attenuation in the first 30 km can be parameterized by a quality factor QS(f) = 23f^0.58 obtained by fixing the geometrical spreading to 1/R. The source spectra can be satisfactorily modeled using the omega-square model that provides stress drops between 0.3 and 60 MPa with a mean value of 3.3±2.8 MPa. The site responses show a large variability over the study area and significant amplification peaks are visible in the frequency range from 1 to more than 10 Hz. Finally, the vertical component of the motion is amplified at a number of sites where, as a consequence, the horizontal-to-vertical spectral ratios (HVSR) method fails in detecting the amplitude levels and in few cases the resonance frequencies.

Computing the magnitude of an earthquake requires correcting for the propagation effects from the source to the receivers. This is often accomplished by performing numerical simulations using a suitable Earth model. In this work, the energy magnitude Me is considered and its determination is performed using theoretical spectral amplitude decay functions over teleseismic distances based on the global Earth model AK135Q. Since the high frequency part (above the corner frequency) of the source spectrum has to be considered in computing Me, the influence of propagation and site effects may not be negligible and they could bias the single station Me estimations. Therefore, in this study we assess the inter- and intrastation distributions of errors by considering the Me residuals computed for a large data set of earthquakes recorded at teleseismic distances by seismic stations deployed worldwide. To separate the inter- and intrastation contribution of errors, we apply a maximum likelihood approach to the Me residuals. We show that the interstation errors (describing a sort of site effect for a station) are within ±0.2 magnitude units for most stations and their spatial distribution reflects the expected lateral variation affecting the velocity and attenuation of the Earth's structure in the uppermost layers, not accounted for by the 1-D AK135Q model. The variance of the intrastation error distribution (describing the record-to-record component of variability) is larger than the interstation one (0.240 against 0.159), and the spatial distribution of the errors is not random but shows specific patterns depending on the source-to-station paths. The set of coefficients empirically determined may be used in the future to account for the heterogeneities of the real Earth not considered in the theoretical calculations of the spectral amplitude decay functions used to correct the recorded data for propagation effects.

In this study, new intensity prediction equations are derived for Central Asia, considering about 6000 intensity data points from 66 earthquakes encompassing the surface-wave magnitude range of 4.6–8.3. The suitability of the functional form used for constructing the model is assessed by comparing its predictions with those achieved through a non-parametric model. The parametric regressions are performed considering different measures of the source-to-site distance, namely the hypocentral, epicentral and the extended distance metrics. The latter is defined as the minimum distance from the site to a line crossing the epicentres, oriented along the strike of the earthquake and having a length estimated from the event’s magnitude. Although the extended distance is introduced as a preliminary attempt to improve the prediction capability of the model by considering the finiteness of the fault extension, the standard deviation of the residual distribution obtained considering the extended distance (σ = 0.734) does not show an improvement with respect to the results for the epicentral distance (σ = 0.737). The similarity of the two models in term of average residuals is also confirmed by comparing the interevent errors obtained for the two regressions, obtaining very similar values for all earthquakes but the 1911, M 8.2 Kemin event. In particular, different evidences suggest that the magnitude of this event could be overestimated by about half a magnitude unit. Regarding the variability of the residual distribution, all the three considered components (i.e. interevent, interlocation and record-to-record variances) are not negligible, although the largest contribution is related to the record-to-record variability, suggesting that both source and propagation as well as site effects not captured by the considered model influence the spatial variability of the intensity values.