Qβ, Qc, Qi and Qs of the Gargano Promontory (Southern Italy)

doi:10.21203/rs.3.rs-2463942/v1

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Research Article

Q_β, Q_c, Q_i and Q_s of the Gargano Promontory (Southern Italy)

https://doi.org/10.21203/rs.3.rs-2463942/v1

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published 16 Aug, 2023

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We have provided the first estimate of scattering and intrinsic attenuation for the Gargano Promontory (Southern Italy) analyzing 190 local earthquakes with M_L ranging from 1.0 to 2.8. To separate the intrinsic ${Q}_{i}$ and scattering ${Q}_{s}$ quality factors with the Wennerberg approach (1993), we have measured the direct S waves and coda quality factors (${Q}_{\beta }$, ${Q}_{c}$) in the same volume of crust. ${Q}_{\beta }$ parameter is derived with the coda normalization method (Aki, 1980) and ${Q}_{c}$ factor is derived with the coda envelope decay method (Sato, 1977). We selected the coda envelope by performing an automatic picking procedure from ${T}_{start}=1.5{T}_{S}$ up to 30 s after origin time (lapse time ${T}_{L}$). All the obtained quality factors clearly increase with frequency.

The ${Q}_{c}$ values correspond to those recently obtained for the area. The estimated ${Q}_{i}$ are comparable to the ${Q}_{c}$ at all frequencies and range between 100 and 1000. The ${Q}_{s}$ parameter shows higher values than ${Q}_{i}$, except for 8 Hz, where the two estimates are closer. This implies a predominance of intrinsic attenuation over the scattering attenuation. Furthermore, the similarity between ${Q}_{i}$ and ${Q}_{c}$ allows us to interpret the high ${Q}_{c}$ anomaly previously found in the northern Gargano Promontory up to a depth of 24 km, as a volume of crust characterized by very low seismic dumping produced by conversion of seismic energy into heat. Moreover, most of the earthquake foci fall in high ${Q}_{i}$ areas, indicating lower level of anelastic dumping and a brittle behavior of rocks.

seismic attenuation

coda normalization method

intrinsic quality factor

scattering quality factor

Southern Italy

Gargano Promontory

OTRIONS seismic network

It is generally accepted that the seismic-wave attenuation (except geometrical spreading) consists of two mechanisms: intrinsic attenuation and scattering. The intrinsic attenuation of the direct wave is the anelastic damping due to the conversion of kinetic energy into heat. The scattering is the mechanism of elastic reflection, refraction and diffraction of a seismic wave due to propagation through inhomogeneities or to the presence of cracks and defects in the medium. The essential difference between these two mechanisms of energy loss is that scattering attenuation is characterized by the scale length of heterogeneities (the mean free path) whereas the intrinsic attenuation is characterized by time-scale (decay time) (Yoshimoto 2000). Thanks to a great intuition, Aki (1969) proposed for the first time that the seismic coda waves of local earthquakes are backscattered waves from numerous randomly distributed heterogeneities in the Earth and may be treated by statistical methods. Some years later, Aki & Chouet (1975), by using data from spectral seismograms, presented evidence for supporting Aki’s idea and introduced the parameter coda ${Q}_{c}$ as a measure of the amplitude decay rate of coda waves within a given frequency band. They also showed that this decay rate was independent of recording site and event location, if observations were made within approximately 100 km from the epicenter. Starting from these pioneer’s papers, many studies have been carried out at inferring the attenuation of elastic waves in the lithosphere and Earth’s interior by using coda waves (reference in Fehler & Sato, 2003). The scattering attenuation is generally treated by three different assumptions: the single scattering model, usually applied in the analysis of the early part of the coda (Sato, 1977), the multiple scattering model, suitable for simulating the entire coda and treated by the radiative transfer theory (Zeng, 1991) and the diffusion model, which is an extreme limit of the multiple scattering process (Dainty & Toksöz, 1981). In the single scattering model, the travelling distance of the direct wave should be less than the mean free path, the scattered field is assumed weak respect to the unscattered field (Born approximation) and the source-receiver separation is neglected (Sato, 1977). This approximation is then well applicable to short period seismograms and small coda, so in this paper we will refer to the single-scattering approximation to retrieve ${Q}_{c}$. The evaluation of the separated effects of scattering and intrinsic attenuation on coda waves is generally obtained by two approaches, both based on the multiple-scattering assumption: the multiple scattering lapse time window analysis (Fehler et al., 1992) which analyzes the coda waves over time and the Wennerberg method (Wennerberg, 1993) which needs the independent measurements of the quality factors of the direct wave ${Q}_{\beta }$ and of the coda waves ${Q}_{c}$, sampled for the same Earth volume. In the last three decades these two approaches were applied and developed to evaluate intrinsic attenuation and scattering in several areas worldwide both in tectonic contests (Akinci et al., 2020; Bianco et al., 2002; Londono et al., 2022; Sharma et al., 2015; Shengelia et al., 2020; Talebi et al., 2021 among the others) and in volcanic ones (Castro-Melgar et al., 2021; Del Pezzo et al., 2019; Ibáñez et al., 2020; Prudencio et al., 2015; Ugalde et al., 2010 among the others) by estimating the quality factors ${Q}_{i}$ and ${Q}_{s}$ respectively.

In this paper, the separation of ${Q}_{s}$ and ${Q}_{i}$ is attempted for the Gargano Promontory (Southern Italy, hereafter GP). The Wennerberg approach has been used, and this implies the independent estimations of ${Q}_{\beta }$ and of ${Q}_{c}$ for the same area. ${Q}_{\beta }$has been estimated using the coda normalization method (Aki, 1980) and ${Q}_{c}$ has been estimated using the method of the coda envelope decay (Sato, 1977), over the same dataset as ${Q}_{\beta }$. The GP is classified as high seismic hazard (horizontal peak ground acceleration $PGA=[0.200-0.225]$g for the 10% probability of exceedance in 50 years, from MPS04 of Stucchi et al., 2004). This classification follows the 2002 October 31th earthquake (${M}_{W}=5.7$) that hit Molise (Southern Italy), a region bordering the GP and until then classified as non-seismic. In 2013 the GP was covered by the OTRIONS local seismic network, installed and managed in cooperation between the University of Bari Aldo Moro (hereafter UniBa) and the National Institute of Volcanology and Geophysics (hereafter INGV), and since then an intense microseismicity has been recorded. The present work benefited of the recently released database of waveforms of the GP microearthquakes (Filippucci et al., 2021c).

From a geodynamic point of view, the GP is considered a continental lithospheric block belonging to Adria plate, subducting the Apennines chain in the western side (De Lorenzo et al., 2017; Petrullo et al., 2017; Bentivenga et al., 2017; Bucci et al., 2019) and Dinarids and Albanids in the eastern sector (Di Bucci & Angeloni, 2013).

The structural setting of GP (Fig. 1) is complex and subject to different interpretations. Ortolani & Pagliuca (1987) consider central portion of GP as a pushup structure influenced by Dinarids. Patacca et al. (2008) invoke halokinetic factors along with tectonics. Bertotti et al. (1999) propose a structural model up to a depth of 4 km, based on surface geological evidences, seismic and well data. These authors hypothesize a basal detachment of the entire carbonate multilayer, located at a depth of 4 km in the Carpino location and becoming more superficial moving towards SW. Near Monte Granata the detachment intersects the topographic surface.

The GP area is adjacent to the Apennine chain which is the most seismically active part of the Italian territory, both for frequency recurrence and magnitude of earthquakes. Even if the seismic history of GP is characterized by destructive events, as the 1627 earthquake (estimated ${M}_{W}=6.7$) and the 1646 earthquake (estimated ${M}_{W}=6.2$) (Del Gaudio et al., 2007), in the last 5 decades, few events with magnitude ${M}_{W}>4$ have been recorded in the GP. The number of high magnitude earthquakes increases if we move some tenths of km westward towards the Molise, where the 2002 October 31th earthquake occurred (Rovida et al., 2022).

Since the installation of the first seismic station on the GP (by INGV and UniBa in 1986), the instrumental coverage of the GP has been improved up to 4 stations in 2008. In 2013, UniBa and INGV cooperated for the installation of 12 new seismic stations (OT network) which greatly improved the seismic monitoring of the southern Italy and of GP. In the following years the network has undergone some changes (refer to Filippucci et al., 2021c for more details) up to the current layout, which can be viewed on https://eida.ingv.it/it/. The seismic monitoring of OT and IV networks on GP revealed an intense activity of micro-earthquakes with magnitude up to 2.8 and the results are disclosed in literature by some recent papers. The 1D velocity model (de Lorenzo et al., 2017) revealed that the GP seismic activity is concentrated at two different depths: deeper in the NE with foci below 20 km and shallower in the SW with foci above 15 km. This difference is probably due to a slope of the brittle/ductile transition at depth, as initially hypothesized by Filippucci et al., (2019b) and subsequently numerically modeled by Lavecchia et al. (2022). The hypocenter distribution, moving from southwest to northeast, aligns itself by drawing a seismogenic surface that deepens towards the northeast but on which earthquakes rupture in an orthogonal direction, towards the northwest, with thrust faulting mechanism (Miccolis et al., 2021). The depth of this lineament agrees with the Moho depth in the GP which is higher (25–30 km as estimated by de Lorenzo et al., 2014; 2017) compared to the Apennine (18–20 km) (Cassinis et al., 2007). The active faults responsible of the seismicity of GP are not yet recognized and no relationship has been found with the San Marco in Lamis-Mattinata composite fault reported by the DISS 3.3.0 database (DISS Working Group, 2021). The southernmost part of GP is characterized by fluid circulation along fractures at shallow depth (Tripaldi, 2020) and this may be the origin of the shallower seismicity of this area. In this frame, Filippucci et al. (2019a), by carrying out a 2D attenuation study at a local scale, revealed that along the direction in which the seismicity becomes deeper, that is moving from southwest to northeast, ${Q}_{c}$ decreases. These authors found also a high ${Q}_{c}$ anomaly which can be correlated with the anomalies of other geophysical observations as gravity (Loddo et al., 1996), surface heat flow (Della Vedova et al., 2001), ${V}_{P}/{V}_{s}$ (Improta et al., 2014) and magnetic field (Speranza & Chiappini, 2002) but they were not able to interpret it in terms of anelasticity or scattering. In order to answer to the question whether these anomalies are related to anelasticity or to heterogeneities of the GP crust, in this paper we separate the contribution of quality factors ${Q}_{i}$ and ${Q}_{s}$ to coda attenuation and finally discuss the trend of ${Q}_{c}$ with depth recently obtained by Filippucci et al., (2021a,b).

The dataset consists of the seismograms of 190 small earthquakes recorded between July 2015 and August 2018 by the UniBa OTRIONS (FDSN code OT) and the INGV RSN (FDSN code IV) seismic networks (refer to Filippucci et al., 2021c for a complete description of the OT seismic network) (Fig. 2) for a total of 24 stations. The OT network started to operate in 2013 and from 2019 recordings are transmitted continuously and in real time on the EIDA platform (European Integrated Data Archive). The OT stations are equipped with 3-component short-period Lennartz velocimeters (Filippucci et al., 2021c); the IV stations are equipped with 3-component velocimeters ranging from very broadband to short period (Michelini et al., 2016). All the considered earthquakes are localized in the GP, with epicentral distance less than 70 km, foci depth reaching the lower crust down to 35 km and M_L ranging from 1.0 to 2.8 (Fig. 2). Locations have an average horizontal error of 0.85 km and an average vertical error of 0.94 km. Events with hypocentral distances larger than 70 km were removed from the analysis being out of the area of interest. This dataset has been already released and is available for downloading (Filippucci et al., 2021d).

First, we carried out a careful visual analysis of all the waveforms (1477 3-component recordings), to remove traces having irregular coda decay (energy bumps) or high noise content. Then, we developed an automatic procedure for waveform selection in order to accept all the recordings for which ${T}_{L}>1.5 {T}_{S}$, being ${T}_{L}$ measured from the earthquake origin time and ${T}_{S}$ the S wave travel time.

In Fig. 2, the record section on the right shows that the choice of ${T}_{L}=30 s$ allows to include in the dataset the seismograms recorded at hypocentral distance less than 70 km. For ${T}_{L}=30 s$, the radius of the spherical volume of Earth crust involved in the ${Q}_{c}$ computation is 58 km for GP (as already derived by Filippucci et al. 2019a). With ${T}_{L}=30 s$, a total number of 1317 3-component recordings were suitable for further analysis, that is the 89% of the initial dataset.

4.1. Q_β estimation

We estimated ${Q}_{\beta }$ applying the coda normalization method (Aki, 1980). This method adopts the ratio between direct S wave and coda wave amplitude spectra, at a fixed lapse time ${T}_{L}$. The obtained spectral ratio is considered independent of site and S-wave source effects (Sato et al., 2012).

${Q}_{\beta }$ was estimated for several frequencies $f$ ={3, 4, 5, 6, 8, 10, 12} Hz with frequency bands ranging from $f/\sqrt{2}$ to $\sqrt{2}f$ by performing a linear regression of data vs distance, based on the following relation (Aki, 1980):

$${\left.⟨ln\left[\frac{{{r}^{\gamma }A}_{\beta }\left(r,f\right)}{{A}_{c}\left(r,f,{t}_{L}\right)}\right]⟩\right|}_{ r\pm \varDelta r} = a\left(f\right)-\frac{\pi fr}{{Q}_{\beta }\left(f\right){V}_{\beta }}$$

where $r$ is the hypocentral distance, A_β and A_c are respectively the spectral amplitudes of S wave and coda waves, $\varDelta r=1.25$ km, ${V}_{\beta }=3.86$km/s is the S wave average velocity in the GP (de Lorenzo et al., 2017) and $a\left(f\right)$ is the intercept of the linear fitting. Geometrical spreading is usually represented in the left side of Eq. (1) as ${r}^{\gamma }$, being $\gamma$ the geometrical spreading factor which varies depending on the considered seismic wave and source-receiver distance (Frankel, 2015 and bibliography therein). For body waves and up to 100 km, $\gamma =1$ (Yoshimoto et al., 1993; Frankel, 2015).

We set ${T}_{L}=30$ s and fixed the time window length ${\varDelta t}_{w}=2.56$ s. ${\varDelta t}_{w}$ starts $0.1$s before ${T}_{S}$ for measuring ${A}_{\beta }$; ${\varDelta t}_{w}$ is centered on the lapse time ${T}_{L}$, over coda waves for measuring ${A}_{c}$.

This choice of the time window length causes the number of sampling points to be a power of 2, being the sampling rate of the OT network seismometers at 100 Hz. The discrete Fourier Transform in the spectral analysis module of internal functions of SAC (Goldstein & Snoke, 2005; Goldstein et al., 2003), was computed without zero-padding to obtain the S-wave and coda wave spectra. A 5% cosine-taper was applied to signals inside ${\varDelta t}_{w}$ in order to reduce distortion caused by finite length signals and avoid the Gibb’s phenomenon (Scherbaum, 2001). ${Q}_{\beta }$ estimates were performed without using different time window amplitudes since Yoshimoto et al. (1993) showed that $Q$ values vary slightly with the length of the time windows, always within the standard deviation.

We considered the three components of the seismograms filtered with 4-pole Butterworth filter in the frequency band defined by $\left[\frac{f}{\sqrt{2}},\sqrt{2}f\right]$. So, the considered frequency bands (in Hz) are: $f=3$Hz: [2.1–4.2], $f=4$ Hz: [2.8–5.7], $f=5$ Hz [3.5–7.1], $f=6$ Hz [4.2–8.5], $f=8$ Hz [5.7–11.3], $f=10$ Hz [7.1–14.1], $f=12$ Hz [8.5–17]. In Fig. 3, the values of $ln\left[\frac{{rA}_{\beta }\left(r,f\right)}{{A}_{c}\left(r,f,{t}_{L}\right)}\right]$, grouped in space windows of 2$\varDelta r=2.5$ km, are plotted as function of $r$ for each frequency band. ${Q}_{\beta }\left(f\right)$ is the result of the linear regression through Eq. (1) and it is plotted as a function of frequency in Fig. 4 and listed in Table 1 with the relative errors $\varDelta {Q}_{\beta }$. The parameters deriving from linear fitting are listed in Table 2.

Table 1

Parameters derived from the linear regression through Eq. (1), as shown in the Fig. 3. m is the slope, n is the intercept and ${R}^{2}$ is the determination coefficient.
$f$(Hz)	$m$	$n$	${R}^{2}$
3	-0.02599	6.525	0.58
4	-0.02913	6.949	0.67
5	-0.02294	7.002	0.72
6	-0.0297	7.086	0.76
8	-0.0303	7.081	0.61
10	-0.0254	6.874	0.56
12	-0.02407	6.744	0.53

Table 2

Average quality factors and their errors, seismic albedo, extinction length, percentage distance between ${Q}_{s}$ and ${Q}_{i}$ reative to ${Q}_{s}$for different values of the frequency$f .$
$f$ (Hz)	${Q}_{\beta }$	$\varDelta {Q}_{\beta }$	${Q}_{c}$	$\varDelta {Q}_{c}$	${Q}_{S}$	$\varDelta {Q}_{s}$	${Q}_{i}$	$\varDelta {Q}_{i}$	${B}_{0}$	${L}_{e}^{}$ (km)	$\frac{{(Q}_{s}-{Q}_{i})}{{Q}_{s}}\left(\%\right)$
3	91	12	158	14	269	57	138	16	0,34	19	49
4	118	16	205	17	343	16	180	20	0,34	18	48
5	167	19	267	23	404	55	240	26	0,41	21	41
6	233	29	340	30	537	69	312	35	0,43	24	42
8	275	48	505	60	568	369	438	67	0,48	21	23
10	421	92	679	67	1407	93	602	92	0,3	26	57
12	598	144	855	88	2561	828	781	128	0,23	31	70

4.2. Processing for Q_c estimation

We performed a new estimation of ${Q}_{c}$ by considering the same source to receiver couples previously used for inferring ${Q}_{\beta }$. We applied the method of coda envelope decay (Aki, 1969) based on the linear fitting of coda energy envelope. An automatic procedure was implemented to pick the starting time of envelope decay of coda waves. The procedure consists of selecting coda waves in a time window between ${1.5 T}_{S}$ and ${T}_{L}$, being ${T}_{L}=30$ s. In our case, the choice of ${1.5 T}_{S}$, allows to include recordings at distances less than 70 km (Fig. 2). We used the same dataset selected for the ${Q}_{\beta }$estimate and observed that all the 1317 three component seismograms were suitable for the ${Q}_{c}$ analysis.

The recordings were bandpass filtered with fourth-order Butterworth around the central frequency $f$ ={3, 4, 5, 6, 8, 10, 12} Hz, with frequency bands defined in the previous subsection. Assuming the single isotropic scattering theory (Sato, 1977), ${Q}_{c}\left(f\right)$ can be retrieved by using the following relationship (Sato, 1977):

$$ln\left[\frac{{A}_{c}\left(r,f,t\right)r}{\sqrt{K\left(a\right)}}\right] = ln\left[{A}_{0}\left(f\right)\right]-\frac{\pi ft}{{Q}_{c}\left(f\right)}$$

where r is the hypocentral distance, ${A}_{c}\left(r,f,t\right)=\sqrt{{H}^{2}\left(S\right)+{S}^{2}\left(t\right)}$ with $H\left(S\right)$ is the Hilbert transform of the seismogram $S\left(t\right)$; $K\left(a\right)=\frac{1}{a}\text{ln}\frac{a+1}{a-1}$ with $a=\frac{{T}_{L}}{{T}_{s}} (a>1$ always). The Eq. (2) allows to estimate ${Q}_{c}\left(f\right)$from a linear regression analysis of the decay rate of the logarithmic coda envelope ${A}_{c}\left(r,f,t\right)$ vs. time $t$. The averaged estimates of ${Q}_{c}\left(f\right)$ are plotted in Fig. 4 and listed in Table 2 with the standard deviation $\varDelta {Q}_{c}$.

4.3. Separation of ${Q}_{i}$ and ${Q}_{s}$ effects

We applied the method proposed by Wennerberg (1993) to infer the scattering and the intrinsic quality factors, ${Q}_{s}$ and ${Q}_{i}$ separately. The method is based on the intuition that the ratio between the coda amplitude decay predicted by the multiple scattering model (Zeng, 1991) and that predicted by the single scattering model (Aki & Chouet, 1975) follows a linear trend as a function of the dimensionless mean free time $\tau =\omega {T}_{L}/{Q}_{s}$, where $\omega =2\pi f$.

Assuming that ${Q}_{c}$ is computed for the single-scattering model, ${Q}_{s}$ and ${Q}_{i}$ can be derived for the multiple-scattering model by this mathematical relationship:

$$\frac{1}{{Q}_{c}\left(\tau \right)} =\frac{1}{{Q}_{i}}+\frac{1-2\delta \left(\tau \right)}{{Q}_{s}}$$

being $\delta \left(\tau \right)$ a correction needed to account for multiple-scattering model of Zeng (1991)$. \delta \left(\tau \right)$ is a theoretical discrete point function of $\tau$ that can be approximated by a linear function (Wennerberg, 1993):

$$1-2\delta \left(\tau \right)=\frac{-1}{4.44+0.738\tau }$$

According with Wennerberg (1993), if we assume that ${Q}_{\beta }$ is the total attenuation ${Q}_{T}$, the combination of intrinsic and scattering attenuation effects is described by:

$$\frac{1}{{Q}_{\beta }} =\frac{1}{{Q}_{i}}+\frac{1}{{Q}_{s}}$$

The necessary condition to separate the contributions of intrinsic and scattering attenuation is to have independent estimates of ${Q}_{c}$ and ${Q}_{\beta }$, both obtained as function of frequency for the same Earth volume. This is the reason why we computed ${Q}_{c}$ instead of using previous results (Filippucci et al., 2021a; a). Then, one approach is to solve the system formed by the equations (3) and (5), which leads to:

$$\frac{1}{{Q}_{S}} = \frac{1}{2\delta \left(\tau \right)}\left(\frac{1}{{Q}_{\beta }}-\frac{1}{{Q}_{c}\left(\tau \right)}\right)$$

$$\frac{1}{{Q}_{i}} = \frac{1}{2\delta \left(\tau \right)}\left(\frac{2\delta \left(\tau \right)-1}{{Q}_{\beta }}+\frac{1}{{Q}_{c}\left(\tau \right)}\right)$$

Equation (6) implies ${Q}_{c}\left(\tau \right)>{Q}_{\beta }$ always since ${Q}_{S}>0$.

Since ${Q}_{T}={Q}_{\beta }$ we can also evaluate the seismic albedo

${B}_{0}=\frac{{Q}_{s}^{-1}}{{Q}_{T}^{-1}}$ defined as the dimensionless ratio of scattering loss to total attenuation, and the extinction length ${L}_{e}^{}=\frac{v}{2\pi f}{Q}_{T}^{}$ that is the distance over which the primary S wave energy is decreased by ${e}^{-1}$.

The obtained results and relative errors for ${T}_{L}=30$ s are reported in Table 2 and plotted in Fig. 4 as functions of $f$.

4.4 Dependence of ${Q}$ on${f}$

The frequency dependence of ${Q}_{c},{Q}_{\beta },{Q}_{i},{Q}_{s}$ at ${T}_{L}=30$ can be retrieved by using the average value of each quality factor plotted in Fig. 4 by means of the power law relationship of rock quality parameter $Q\left(f\right)={Q}_{0}{\left(\frac{f}{{f}_{0}}\right)}^{\alpha }$ (or equivalently of rock attenuation ${Q}^{-1}\left(f\right)={Q}_{0}^{-1}{\left(\frac{f}{{f}_{0}}\right)}^{-\alpha }$), with ${f}_{0}=1$Hz. We obtained the following values of ${Q}_{0}$ and $\alpha$ (and the corresponding ${Q}_{0}^{-1}$):

${Q}_{\beta }\left(f\right)=(20\pm 3){f}^{1.34\pm 0.10}$	${Q}_{\beta }^{-1}=(51 \pm 4){{10}^{-3}f}^{-1.34\pm 0.06}$	(8)
${Q}_{c}\left(f\right)=\left(37\pm 2\right){f}^{1.25\pm 0.05}$	${Q}_{c}^{-1}=(27 \pm 1){10}^{-3}{f}^{-1.25\pm 0.03}$
${Q}_{s}\left(f\right)=\left(40\pm 9\right){f}^{1.52\pm 0.22}$	${Q}_{s}^{-1}=(25 \pm 6){10}^{-3}{f}^{-1.52\pm 0.22}$
${Q}_{i}\left(f\right)=\left(32\pm 2\right){f}^{1.27\pm 0.07}$	${Q}_{s}^{-1}=(31 \pm 1){10}^{-3}{f}^{-1.27\pm 0.03}$

${Q}_{s}\left(f\right)$ increases with frequency with $\alpha =1.52$ faster than the other quality factors, indicating that the more pronunciate increase of ${Q}_{s}$ may be caused by the present half-space assumption, as already observed by Akinci et al. (2020) for the central Apennine.

We obtained the first estimation of ${Q}_{\beta },{Q}_{i},{Q}_{s}$ quality factors in the GP and a new estimation of ${Q}_{c}$. We used the micro-seismicity of GP recorded by the OT and the RSN seismic network in the period 2013–2018, recently released in a database of seismic waveforms (Filippucci et al., 2021c,d). The new estimation of ${Q}_{c}$ was achieved by the implementation of an automatic procedure to pick the starting time of envelope decay over coda waves with Eq. (2). Since the slope of the envelope decay can vary over time (in general the slope decreases with time, Filippucci et al., 2021a), the choice of the starting point ${T}_{start}$ could control the ${Q}_{c}$ results. Theoretically, Eq. (2) could be applied to a time window that starts immediately after ${T}_{S}$ but this is not the common choice. Commonly, ${T}_{start}=2{T}_{S}$ (e.g., Jin & Aki, 1988; Ibáñez et al., 1990; Eyidogan & Akinci, 1996; Mamada et al., 1997) or in other cases ${T}_{start}=1.5{T}_{S}$ (e.g., Padhy et al., 2011 and references therein). Mukhopadhyay and Sharma (2010), for the Himalayan region, analyzed the effect of ${T}_{start}$ on attenuation and observed: non-significative differences on ${Q}_{c}$ for different ${T}_{start}$; significative decrease in the total number of available waveforms as ${T}_{start}$ increases from $1.5{T}_{S}$ to $2.5{T}_{S}$, especially for lapse times below 50 s. So, ${T}_{start}=1.5{T}_{S}$ is the most conservative choice in terms of data selection. To avoid “a priori” choices on ${T}_{start}$ and to eliminate envelopes with abrupt variations along the coda decay (e.g., signal bumps), some authors prefer to manually pick the decay onset by visually inspecting the envelopes (de Lorenzo et al., 2013; Filippucci et al, 2019a; 2021a). The comparison between ${Q}_{c}$ retrieved from the same dataset but with a manual picking of ${T}_{start}$ (Filippucci et al., 2021a) and ${Q}_{c}$ of this work reveals that ${T}_{start}=1.5{T}_{S}$ systematically falls into a zone of the envelope with a less decay rate respect to the manual picking and produces a small shift between the two estimates, inside the standard deviation. This effect can be observed in Fig. 5, revealing a slightly less attenuating crust for GP than the previously estimated one. Being these differences not dramatic and considering the great costs saved in terms of human resources and time, we considered as acceptable the automatic picking procedure with ${T}_{start}=1.5{T}_{S}$.

${Q}_{c}$ is confirmed to be frequency dependent and increases with increasing frequency, as already observed worldwide both in tectonic and in volcanic contests.

${Q}_{\beta }$ was estimated by the coda-normalization method (Aki 1980). This method eliminates source, site and geometrical spreading effects by normalizing S-wave amplitudes with coda waves. It reveals the attenuation on body waves due to the medium anelasticity and to elastic scattering on heterogeneities. Generally, the normalized amplitudes of S-waves decrease with increasing of hypocentral distances, demonstrating that body waves attenuate in amplitude with increasing travel distance and this attenuation depends on both frequency and geometrical spreading. This effect is shown in Fig. 3 where, from the slope of the linear fit line [eq. (1)], ${Q}_{\beta }$ can be computed for different frequency bands. As it can be observed from Table 2 and Fig. 4, ${Q}_{\beta }$ regularly increases in all the frequency range except for $6\text{H}\text{z}<f<$ 8Hz where it is flat. This observation can be inferred also from plots in Fig. 3. The revealed S-wave attenuation at ${f}_{c}=8$Hz might be due to the scattering loss at random heterogeneities having a characteristic length or alternatively the 8 Hz frequency might be the predominant frequency band of the anelastic response of the medium, as discussed by Sil et al. (2022) for the Kathmandu region, Nepal. The S-wave attenuation was computed by the assumption of the half-space approximation with uniform ${V}_{\beta }$, that is quite unrealistic especially for the shallower layers in the upper crust. This simplification may produce a bias in the estimation of ${Q}_{\beta }$. Some authors (Akinci et al., 2020; Pisconti et al., 2015) estimated the effect of a depth dependent crustal model on the attenuation for the Central Apennine (Italy). They found out that ${Q}_{s}$ and ${Q}_{i}$ are slightly affected by these assumptions (depth-dependent or homogeneous Earth) in the case of a continental crust, where shallow earthquakes occur, while, with increasing the source-receiver distance, the observed apparent attenuation decreases, suggesting an increasing of propagation efficiency with depth below the Moho. The seismicity of GP occurs at crustal depth above the Moho discontinuity (Miccolis et al., 2021) ${Q}_{\beta }$attenuation should not be severely affected by the homogeneous half-space approximation.

The separated contribution on coda waves of anelastic attenuation ${Q}_{i}$and elastic scattering ${Q}_{s}$ was inferred by using the Wennerberg (1993) method. The application of this method requires the availability of independent estimates of ${Q}_{\beta }$ and ${Q}_{c}$ as functions of frequency for the same Earth volume in order to avoid bias in the results. In our case we used the same dataset, representative of the same crust volume of the Gargano Promontory (Southern Italy), for the estimates of the total attenuation of body waves${Q}_{\beta }$ and of the coda wave attenuation ${Q}_{c}$ in the single-scattering approximation. Results in Fig. 4 indicate a regular descending trend of attenuation as functions of frequency. ${Q}_{s}$ presents an irregular low value at 8 Hz reinforcing the idea that the lower value of ${Q}_{\beta }$ at 8 Hz might be due to a scattering effect. Assuming a uniform half space with constant velocity ${V}_{\beta }=3.86$km/s as we did, $f=8$Hz corresponds to a wavelength $\approx 0.5$ km, which could represent the average distance of the random scatterers in the Gargano crust. For all the other frequencies, scattering on heterogeneities turns out to be less important than anelasticity in the coda attenuation in agreement with the preceding results in regional studies of Southern Apennine which included marginally the GP area (Bianco et al., 2002).

Results of ${Q}_{i}$and ${Q}_{s}$ in tectonic contests worldwide suggest that the attenuation of coda waves is dominated by the intrinsic attenuation (Padhy et al, 2011; Farrokhi et al., 2016; Pujades et al., 1997; Akinci et al., 1995; Aki & Chouet, 1975; Bianco et al., 2005; Tuvè et al., 2006 among the others). The predominance of the anelasticity on coda waves increases by increasing frequency since the percentage ratio ${(Q}_{s}-{Q}_{i})/{Q}_{s}$ moves from 48% at 3Hz to 70% at 12Hz (Table 2). The seismic albedo is ${B}_{0}<0.5$ for all the frequency bands which indicates that anelasticity is the predominant attenuation effect in the region. The only exception is for $f=8$Hz where ${B}_{0}\cong 0.5$ indicating a predominance of scattering at the scale length of this frequency. The extinction length ${L}_{e}$ ranges between 18 and 31 km, increases with frequency (with the exception for $f=8$ Hz where ${L}_{e}$ is lower) and it is comparable with other studies in tectonic domains (Akinci et al., 2020; Londono et al., 2022; Sharma et al., 2015; Shengelia et al., 2020; Talebi et al., 2021 among the others). It is worth noting that the results might be biased by the constant velocity half space assumption (Del Pezzo et al., 2019). The comparison between the outcomes of this study and those previously obtained for other tectonically active regions in Italy and worldwide reveals that the GP values of seismic quality factors ${Q}_{i}$ and ${Q}_{s}$ are within the end members at all frequencies (Fig. 6).

The frequency dependence relationships of ${Q}_{\beta },{Q}_{c},{Q}_{i},{Q}_{s}$ show estimates of ${Q}_{0}$ up to 40 and values of $\alpha$ greater than 1.25. The paradox consists of both the small values of ${Q}_{0}$ (less than 48) and the high values of $\alpha$ (greater than 1.1) that should indicate a high tectonic activity and the general absence of high magnitude earthquakes in the GP (Morozov, 2008). The ${M}_{W}=5.7$ Molise earthquake (Southern Italy, 2002 October 31th ) occurred in an adjacent area previously classified as low hazard area, may reinforce the hypothesis that the GP could reasonably located in a tectonically active regime.

At 12 Hz we can observe in Fig. 4 the maximum difference between ${Q}_{s}$ and ${Q}_{i}$, so it might be stated that coda amplitudes at 12 Hz are controlled by anelastic damping and it can be considered predominantly as attenuation of body waves, since attenuation of surface waves is detectable at lower frequencies, less than 10 Hz (Aki & Chouet, 1975). Therefore ${Q}_{c}\approx {Q}_{i}$ at all frequencies and this result has relevant consequences if we examine the recent 3D tomography of coda attenuation in GP (Filippucci et al., 2021a). The 3D images of ${Q}_{c}$ were obtained for three frequencies (3Hz, 6Hz and 12 Hz in Filippucci et al., 2021a) by using the Del Pezzo & Ibanez (2020) approach which consists of computing the polynomial approximation of the analytical sensitivity kernels. The polynomial sensitivity kernels were then used as weighting functions for estimating ${Q}_{c}$ in an Earth volume, which was subdivided in cubic pixels with side of 5 km, producing a horizontal ${Q}_{c}$image every 8 km of depth for the GP crust. We reported in Fig. 7 the images of the 3D tomography of ${Q}_{c}$ at 12Hz (modified from Filippucci et al., 2021a). Now we can consider ${Q}_{c}\approx {Q}_{i}$ and give a physical interpretation of the observed anomalies by interpreting them as attenuation of body waves. The well-defined high ${Q}_{i}$ anomaly, extending down to 24 km, reveals the presence of a body embedded in a more attenuating one in the northern GP which might agree with the hypothesis of the existence of a high-density and high susceptibility body in the same area (Loddo et al., 1996). This hypothesis agrees also with the observation of some igneous rocks that crop out in GP in a land named Punta delle Pietre Nere (black star in Fig. 1), intruding the upper Triassic sedimentary successions. These magmas are interpreted as derived from an amphibole-bearing lithospheric mantle source at 70–90 km depth (Mazzeo et al, 2018).

Figure 7 shows a ${Q}_{i}$ decreasing trend (attenuation increasing trend) moving toward the Northeast sector of GP. This sector is characterized by an anomalous absence of seismic activity down to 20 km (Miccolis et al., 2021). Therefore, the observed ${Q}_{i}$ decreasing trend well correlates with the hypothesis of a ductile behavior characterizing the upper basement and the sedimentary cover, as confirmed by a recent thermo-rheological model (Lavecchia et al., 2022). At depths greater than 20 km, a seismogenic layer is encountered (Miccolis et al., 2020) and it was modelled as due to the presence of fluids in the deepest part of the basement (Lavecchia et al., 2022). These results agree with the presence of general high ${Q}_{i}$ (low attenuation) values that can be a hint of a brittle and low-strength lower crust in the deepest seismogenic layer ( Fig. 7, 32 km). It is worth to note that at all depths the most part of earthquake foci falls in areas characterized by high ${Q}_{i}$, indicating a quite good agreement between the presence of seismicity and lower levels of anelastic damping both correlated to the brittle behavior of rocks.

Funding: Not applicable
Conﬂict of interest/Competing interests (check journal-speciﬁc guidelines for which heading to use): all authors declare not to have any conflict of interest.
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Consent to participate: all authors agree to participate.
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Availability of data and materials: data and materials are available under request
Code availability: code is available under request.
Authors’ contributions: All authors contributed to the study conception and design. Conceptualization: [Salvatore de Lorenzo, Edoardo Del Pezzo, Marilena Filippucci], Data curation: [Salvatore Lucente, Teresa Ninivaggi]; Formal analysis and investigation: [Salvatore de Lorenzo, Marilena Filippucci, Salvatore Lucente, Teresa Ninivaggi]; Writing - original draft preparation: [Salvatore de Lorenzo, Marilena Filippucci, Salvatore Lucente]; Writing - review and editing: [ ]; Funding acquisition: [Andrea Tallarico]; Resources: [Andrea Tallarico, Giacomo Prosser]; Supervision: [Edoardo Del Pezzo]; Visualization: [Salvatore Lucente, Teresa Ninivaggi]

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Abdel-Fattah, A. K.; Morsy, M.; El-Hady, S.; Kim, K. Y. & Sami, M. (2008). Intrinsic and scattering attenuation in the crust of the Abu Dabbab area in the eastern desert of Egypt. Physics of the Earth and Planetary Interiors, 168(1-2), 103-112, https://doi.org/10.1016/j.pepi.2008.05.005.
Aki, K. (1969). Analysis of the seismic coda of local earthquakes as scattered waves. Journal of geophysical research, 74(2), 615-631, https://doi.org/10.1029/JB074i002p00615.
Aki, K. (1979). Characterization of barriers on an earthquake fault. Journal of Geophysical Research: Solid Earth, 84(B11), 6140-6148, https://doi.org/10.1029/JB084iB11p06140.
Aki, K. (1980). Attenuation of shear-waves in the lithosphere for frequencies from 0.05 to 25 Hz. Phys. Earth Planet. Inter. 21, 50-60, https://doi.org/10.1016/0031-9201(80)90019-9.
Aki, K. & Chouet, B. (1975). Origin of Coda Waves: Source, Attenuation, and Scattering Effects. J. Geophys. Res., 80, 3322-3342, https://doi.org/10.1029/JB080i023p03322.
Aki, K. & Tsujiura M. (1959). Correlation study of near earthquake waves. Bull. Earthq. Res. Inst. Univ. Tokyo, 37, 207-232, doi: 10.15083/0000033884.
Akinci, A.; Del Pezzo, E. & Ibáñez, J.M. (1995). Separation of Scattering and Intrinsic Attenuation in Southern Spain and Western Anatolia (Turkey). Geophys. J. Int., 121, 337-353, https://doi.org/10.1111/j.1365-246X.1995.tb05715.x.
Akinci, A.; Del Pezzo, E. & Malagnini, L. (2020). Intrinsic and scattering seismic wave attenuation in the Central Apennines (Italy), Physics of the Earth and Planetary Interiors, Volume 303, 106498, ISSN 0031-9201, https://doi.org/10.1016/j.pepi.2020.106498.
Bentivenga, M.; Palladino, G.; Prosser, G.; Guglielmi, P.; Geremia, F. & Laviano, A. (2017). A geological itinerary through the Southern Apennine thrust belt (Basilicata - southern Italy). Geoheritage, 9(1), 1-17.
Bertotti, G.; Casolari E. & Picotti V. (1999). The Gargano Promontory: a Neogene contractional belt within the Adriatic plate. Terra Nova-Oxford, 11(4), 168-173, http://dx.doi.org/10.1046/j.1365-3121.1999.00243.x.
Bianco, F.; Del Pezzo, E.; Castellano, M.; Ibanez, J. & Di Luccio, F. (2002). Separation of Intrinsic and Scattering Seismic Attenuation in the Southern Apennine Zone, Italy. Geophys. J. Int., 150, 10-22, http://dx.doi.org/10.1046/j.1365-246X.2002.01696.x.
Bianco, F.; Del Pezzo, E.; Malagnini, L.; Luccio, F.D. & Akinci, A. (2005). Separation of Depth-Dependent Intrinsic and Scattering Seismic Attenuation in the Northeastern Sector of the Italian Peninsula. Geophys. J. Int., 161, 130-142, https://doi.org/10.1111/j.1365-246X.2005.02555.x.
Biescas, B.; Rivera, Z. & Zapata, J.A. (2007). Seismic Attenuation of Coda Waves in the Eastern Region of Cuba. Tectonophysics, 429, 99-109, https://doi.org/10.1016/j.tecto.2006.09.013.
Bosellini, A. & Morsilli, M. (2001). Il Promontorio del Gargano cenni di Geologia e Itinerari Geologici: Claudio Grenzi Editore. Sant’Angelo: Parco Nazionale del Gargano, 1-48.
Boulanouar, A.; Moudnib, L.E.; Padhy, S.; Harnafi, M.; Villaseñor, A.; Gallart, J.; Pazos, A.; Rahmouni, A.; Boukalouch, M. & Sebbani, J. (2018). Estimation of Coda Wave Attenuation in Northern Morocco. Pure Appl. Geophys., 175, 883-897, https://doi.org/10.1007/s00024-017-1726-4.
Bucci, F.; Tavarnelli, E.; Novellino, R.; Palladino, G.; Guglielmi, P.; Laurita, S.; ... & Bentivenga, M. (2019). The history of the southern Apennines of Italy preserved in the geosites along a geological itinerary in the High Agri Valley. Geoheritage, 11(4), 1489-1508.
Cassinis, G.; Cortesogno, L.; Gaggero, L., Perotti, C. & Ronchi, A. (2007). Volcanic products from the Early Permian Collio Basin (southern Alps) and their geodynamic implications. Per. Mineral., 76, 25-47, Doi: 10.2451/2007/PM0007.
Castro-Melgar, I., Prudencio, J., Cannata, A., Del Pezzo, E., & Ibáñez, J. M. (2021). Small-scale volcanic structures of the Aeolian volcanic arc revealed by seismic attenuation. Frontiers in Earth Science, 9, 725402, http://dx.doi.org/10.3389/feart.2021.725402.
Chilovi, C.; De Feyter, A. J. & Pompucci, A. (2000). Wrench zone reactivation in the Adriatic Block: the example of the Mattinata Fault System (SE Italy). Boll. Soc. Geol. Ital. 119, 3-8.
Chung, J.-K.; Chen, Y.-L. & Shin, T.-C. (2009). Spatial Distribution of Coda Q Estimated from Local Earthquakes in Taiwan Area. Earth Planet Space, 61, 1077-1088, https://doi.org/10.1186/BF03352958.
Dainty, A.M. (1981). A scattering model to explain seismic Q, observations in the lithosphere between 1 and 30 Hz. Geophys. Res. Lett., 8, 1126-1128, https://doi.org/10.1029/GL008i011p01126.
Dainty, A. M. & Toksöz, M. N. (1981). Seismic codas on the Earth and the Moon: A comparison. Physics of the Earth and Planetary Interiors, 26(4), 250-260, https://doi.org/10.1016/0031-9201(81)90029-7.
Dasović, I.; Herak, M. & Herak, D. (2013). Coda-Q and Its Lapse Time Dependence Analysis in the Interaction Zone of the Dinarides, the Alps and the Pannonian Basin. Phys. Chem. Earth Parts A/B/C, 63, 47-54, https://doi.org/10.1016/j.pce.2013.03.001.
de Lorenzo, S.; Del Pezzo, E. & Bianco, F. (2013). Qc, Qb, Qi and Qs attenuation parameters in the Umbria–Marche (Italy) region. Physics of the Earth and Planetary Interiors, 218, 19-30, https://doi.org/10.1016/j.pepi.2013.03.002.
de Lorenzo, S.; Romeo, A.; Falco, L.; Michele, M. & Tallarico, A. (2014). A first look at the Gargano (southern Italy) seismicity as seen by the local scale OTRIONS seismic network, 57, 4, doi:10.4401/ag-6594.
de Lorenzo, S.; Michele, M.; Emolo, A. & Tallarico, A. (2017). A 1D P-wave velocity model of the Gargano promontory (southeastern Italy). Journal Seismology, 21(4), 909-919, https://doi.org/10.1007/s10950-017-9643-7.
Del Gaudio, V.; Pierri, P.; Frepoli, A.; Calcagnile, G.; Venisti, N. & Cimini, G. (2007). A critical revision of the seismicity of northern Apulia (Adriatic microplate - Southern Italy) and implications for the identification of seismogenic structures. Tectonophysics, 436, 9-35, https://doi.org/10.1016/j.tecto.2007.02.013.
Del Pezzo, E. (2008). Seismic scattering in volcanoes. In: Sato, H., Fehler, M.C. (Eds.), Earth Heterogeneity and Scattering Effects on Seismic Waves. Advances in Geophysics, vol. 50. Academic Press, Elsevier, https://doi.org/10.1016/S0065-2687(08)00013-7.
Del Pezzo, E. & Ibáñez, J.M. (2020). Seismic Coda-Waves Imaging Based on Sensitivity Kernels Calculated Using an Heuristic Approach. Geosciences, 10, 304, https://doi.org/10.3390/geosciences10080304.
Del Pezzo, E., Bianco, F., Giampiccolo, E.; et al. (2015). A reappraisal of seismic Q evaluated at Mt. Etna volcano. Receipt for the application to risk analysis. J. Seismol., 19, 105-119. https://doi.org/10.1007/s10950-014-9453-0.
Del Pezzo, E., Giampiccolo, E., Tuvè, T., Di Grazia, G., Gresta, S., & Ibàñez, J. M. (2019). Study of the regional pattern of intrinsic and scattering seismic attenuation in Eastern Sicily (Italy) from local earthquakes. Geophysical Journal International, 218(2), 1456-1468, https://doi.org/10.1093/gji/ggz208.
Della Vedova, B.; Bellani, S.; Pellis, G. & Squarci, P. (2001). Deep temperatures and surface heat flow distribution. In Anatomy of an orogen: the Apennines and adjacent Mediterranean basins (65-76). Springer, Dordrecht, DOI:10.1007/978-94-015-9829-3_7.
Di Bucci, D. & Angeloni, P. (2013). Adria seismicity and seismotectonics: review and critical discussion. Marine and Petroleum Geology, 42, 182-190, https://doi.org/10.1016/j.marpetgeo.2012.09.005.
DISS Working Group (2021). Database of Individual Seismogenic Sources (DISS), Version 3.3.0: A compilation of potential sources for earthquakes larger than M 5.5 in Italy and surrounding areas. Istituto Nazionale di Geofisica e Vulcanologia (INGV), https://doi.org/10.13127/diss3.3.0.
Dobrynina, A.A.; Albaric, J.; Deschamps, A.; Perrot, J.; Ferdinand, R.W.; Déverchère, J.; San’kov, V.A. & Chechel’nitskii, V.V. (2017). Seismic Wave Attenuation in the Lithosphere of the North Tanzanian Divergence Zone (East African Rift System). Russ. Geol. Geophys., 13, 253-265, https://doi.org/10.1016/j.rgg.2016.03.016.
EIDA platform (European Integrated Data Archive, http://eida.rm.ingv.it/).
Eyidoğan, H.; Akıncı, A.; Gündoğdu, O.; Polat, O. & Kaypak, B. (1996). Investigation of the recent seismic activity of Gökova Basin. In National Marine Geology and Geophysical Programme Workshop, 1, 68-71.
Farrokhi, M.; Hamzehloo, H.; Rahimi, H. & Allameh Zadeh, M. (2016). Separation of Intrinsic and Scattering Attenuation in the Crust of Central and Eastern Alborz Region, Iran. Phys. Earth Planet. Inter., 253, 88-96, https://doi.org/10.1016/j.pepi.2016.02.005.
Fehler, M.; Hoshiba, M.; Sato, H. & Obara, K. (1992). Separation of scattering and intrinsic attenuation for the Kanto-Tokai Region, Japan, using measurements of S-wave energy versus hypocentral distance. Geophys. J. Int., 108, 787-800, https://doi.org/10.1111/j.1365-246X.1992.tb03470.x.
Fehler, M. & Sato, H. (2003). Coda. Pure and applied geophysics, 160(3), 541-554, https://doi.org/10.1007/PL00012549.
Filippucci, M.; Lucente, S.; De Lorenzo, S.; Del Pezzo, E.; Prosser, G. & Tallarico, A. (2021a). Seismic Envelopes of Coda Decay for Q-coda Attenuation Studies of the Gargano Promontory (Southern Italy) and Surrounding Regions. “Data” (MDPI), 6, 98. https://doi.org/10.3390/data6090098.
Filippucci, M.; Lucente, S.; Del Pezzo, E.; De Lorenzo, S.; Prosser, G. & Tallarico, A. (2021b). 3D-Kernel Based Imaging of an Improved Estimation of (Qc) in the Northern Apulia (Southern Italy). Appl. Sci. 2021, 11, 7512. https://doi.org/10.3390/app11167512.
Filippucci, M.; Miccolis, S.; Castagnozzi, A.; Cecere, G.; de Lorenzo, S.; Donvito, G.; Falco, L.; Michele, M.; Nicotri, S.; Romeo, A.; et al. (2021c). Seismicity of the Gargano Promontory (Southern Italy) after 7 Years of Local Seismic Network Operation: Data Release of Waveforms from 2013 to 2018. Data Brief 2021, 35, 106783, https://doi.org/10.1016/j.dib.2021.106783.
Filippucci, M.; Miccolis, S.; Castagnozzi, A.; Cecere, G.; de Lorenzo, S.; Donvito, G.; Falco, L.; Michele, M.; Nicotri, S.; Romeo, A.; et al. (2021d). Gargano Promontory (Italy) Microseismicity (2013-2018): Waveform Data and Earthquake Catalogue. Mendeley Data 2021, 3, DOI:10.17632/7b5mmdjpt3.3.
Filippucci, M.; Pierri, P.; de Lorenzo, S. & Tallarico, A. (2020). The Stress Field in the Northern Apulia (Southern Italy), as Deduced from Microearthquake Focal Mechanisms: New Insight from Local Seismic Monitoring. In: International Conference on Computational Science and Its Applications; Springer: Cham, Switzerland, 2020; Volume 12255 LNCS, 914-927, https://doi.org/10.1007/978-3-030-58820-5_66.
Filippucci, M.; Del Pezzo, E.; de Lorenzo, S. & Tallarico, A. (2019a). 2D kernel-based imaging of coda-Q space variations in the Gargano Promontory (Southern Italy). Physics of the Earth and Planetary Interiors, 297, 106313, https://doi.org/10.1016/j.pepi.2019.106313.
Filippucci, M.; Tallarico, A.; Dragoni, M. & de Lorenzo, S. (2019b). Relationship Between Depth of Seismicity and Heat Flow: The Case of the Gargano Area (Italy). Pure Appl. Geophys. 2019, 176, 2383-2394, https://doi.org/10.1007/s00024-019-02107-5.
Frankel, A. (2015). Decay of S‐wave amplitudes with distance for earthquakes in the Charlevoix, Quebec, area: Effects of radiation pattern and directivity. Bulletin of the Seismological Society of America, 105(2A), 850-857, https://doi.org/10.1785/0120140249.
Giampiccolo, E. & Tuvè, T. (2018). Regionalization and dependence of coda Q on frequency and lapse time in the seismically active Peloritani region (northeastern Sicily, Italy). J Seismol 22, 1059-1074, https://doi.org/10.1007/s10950-018-9750-0.
Giampiccolo, E.; Tusa, G.; Langer, H. & Gresta, S. (2002). Attenuation in Southeastern Sicily (Italy) by Applying Different Coda Methods. J. Seismol., 6, 487-501, https://doi.org/10.1023/A:1021150819311.
Goldstein, P. & Snoke, A. (2005). SAC Availability for the IRIS Community. Incorporated Research Institutions for Seismology Newsletter, 7(1). Retrieved from https://ds.iris.edu/ds/newsletter/vol7/no1/193/sac-availability-for-the-iris-community/.
Goldstein, P.; Dodge, D.; Firpo, M. & Minner, L. (2003). “SAC2000: Signal processing and analysis tools for seismologists and engineers, Invited contribution to “The IASPEI International Handbook of Earthquake and Engineering Seismology”, Edited by WHK Lee, H. Kanamori, P.C. Jennings, and C. Kisslinger, Academic Press, London, https://doi.org/10.1016/S0074-6142(03)80284-X.
Gupta, A.K.; Sutar, A.K.; Chopra, S.; Kumar, S. & Rastogi, B.K. (2012). Attenuation Characteristics of Coda Waves in Mainland Gujarat (India). Tectonophysics, 530-531, 264-271, https://doi.org/10.1016/j.tecto.2012.01.002.
Ibáñez, J. M., Castro-Melgar, I., Cocina, O., Zuccarello, L., Branca, S., Del Pezzo, E., & Prudencio, J. (2020). First 2-D intrinsic and scattering attenuation images of Mt Etna volcano and surrounding region from active seismic data. Geophysical Journal International, 220(1), 267-277, https://doi.org/10.1093/gji/ggz450.
Ibáñez, J.M.; Pezzo, E.D.; Miguel, F.D.; Herraiz, M.; Alguacil, G. & Morales, J. (1990). Depth-Dependent Seismic Attenuation in the Granada Zone (Southern Spain). Bull. Seismol. Soc. Am., 80, 1232-1244, https://doi.org/10.1785/BSSA0800051232.
Improta, L., De Gori, P. & Chiarabba, C. (2014). New insights into crustal structure, Cenozoic magmatism, CO2 degassing, and seismogenesis in the southern Apennines and Irpinia region from local earthquake tomography. Journal of Geophysical Research: Solid Earth, 119(11), 8283-8311, https://doi.org/10.1002/2013JB010890.
INGV Seismological Data Centre (2006, January 1). Rete Sismica Nazionale (RSN). Istituto Nazionale di Geofisica e Vulcanologia (INGV), Italy, https://doi.org/10.13127/SD/X0FXNH7QFY.
Jin, A. & Aki, K. (1988). Spatial and temporal correlation between coda Q and seismicity in China. Bulletin of the Seismological Society of America, 78(2), 741-769, https://doi.org/10.1785/BSSA0780020741.
Kandel, T.P.; Yamada, M. & Pokhrel, P. (2020). Determination of High-Frequency Attenuation Characteristic of Coda Waves in the Central Region of Nepal Himalaya. J. Nepal Geol. Soc., 60, 75-86, https://doi.org/10.3126/jngs.v60i0.31259.
Kosuga, M. (1992). Dependence of Coda Q on Frequency and Lapse Time in the Western Nagano Region, Central Japan. J. Phys. Earth , 40, 421-445, https://doi.org/10.4294/jpe1952.40.421.
Lavecchia, A.; Filippucci, M.; Tallarico, A.; Selvaggi, G.; Cecere, G. & Cloetingh, S. (2022). Role of crustal fluids and thermo-mechanical structure for lower crustal seismicity: the Gargano Promontory (southern Italy). Global and Planetary Change, 217, 103929, https://doi.org/10.1016/j.gloplacha.2022.103929.
Loddo, M.; Quarto, R. & Schiavone, D. (1996). Integrated geophysical survey for the geological structural and hydrogeothermal study of the North-western Gargano promontory (Southern Italy). Annals of Geophys., 39(1), 201-219, http://dx.doi.org/10.4401/ag-3962.
Londoño, J. M., Velásquez, L. V., & Bermudez, J. C. (2022). Seismic Wave Attenuation at Valle Medio Del Magdalena, Colombia, http://dx.doi.org/10.2139/ssrn.4066289.
Mamada, Y.; Okumura, T.; Takenaka, H.; Suzuki, S.; Saito, S.; Furumura, M.; ... & Furumura, T. (1997). Coda Q-1 in Awaji Island estimated from the aftershock records of the 1995 Hyogo-ken Nanbu earthquake. Journal of Physics of the Earth, 45(2), 147-154, https://doi.org/10.4294/jpe1952.45.147.
Mantovani, E.; Viti, M.; Babbucci, D.; Tamburelli, C. & Albarello, D. (2006). Geodynamic connection between the indentation of Arabia and the Neogene tectonics of the central-eastern Mediterranean region. Special Papers-Geological Society of America, 409, 15, https://doi.org/10.1130/2006.2409(02).
Matsunami, K. (1991). Laboratory tests of excitation and attenuation of coda waves using 2-D models of scattering media. PEPI, 67, 36-47, https://doi.org/10.1016/0031-9201(91)90058-P.
Mazzeo, F. C.; Arienzo, I.; Aulinas, M.; Casalini, M.; Di Renzo, V. & D'Antonio, M. (2018). Mineralogical, geochemical and isotopic characteristics of alkaline mafic igneous rocks from Punta delle Pietre Nere (Gargano, Southern Italy). Lithos, 308, 316-328, https://doi.org/10.1016/j.lithos.2018.03.015.
Miccolis, S.; Filippucci, M.; de Lorenzo, S.; Frepoli, A.; Pierri, P. & Tallarico, A. (2021). Seismogenic Structure Orientation and Stress Field of the Gargano Promontory (Southern Italy) From Microseismicity Analysis. Frontiers in Earth Science, 179, http://dx.doi.org/10.3389/feart.2021.589332.
Michelini, A.; Margheriti, L.; Cattaneo, M.; Cecere, G.; D'Anna, G.; Delladio, A.; ... & Selvaggi, G. (2016). The Italian National Seismic Network and the earthquake and tsunami monitoring and surveillance systems. Advances in Geosciences, 43, 31-38, https://doi.org/10.5194/adgeo-43-31-2016.
Mittal, H.; Sharma, B.; Chao, W. A.; Wu, Y. M.; Lin, T. L. & Chingtham, P. (2022). A comprehensive analysis of attenuation characteristics using strong ground motion records for the Central Seismic Gap Himalayan Region, India. Journal of Earthquake Engineering, 26(5), 2599-2624, https://doi.org/10.1080/13632469.2020.1768969.
Morozov, I. B. (2008). Geometrical attenuation, frequency dependence of Q, and the absorption band problem. Geophysical Journal International, 175(1), 239-252, https://doi.org/10.1111/j.1365-246X.2008.03888.x.
Mukhopadhyay, S. & Sharma, J. (2010). Attenuation characteristics of Garwhal–Kumaun Himalayas from analysis of coda of local earthquakes. J. Seismol., 14, 693-713, https://doi.org/10.1007/s10950-010-9192-9.
Mukhopadhyay, S. & Tyagi, C. (2007). Lapse Time and Frequency-Dependent Attenuation Characteristics of Coda Waves in the Northwestern Himalayas. J. Seism., 11, 149-158, https://doi.org/10.1007/s10950-006-9042-y.
Ortolani, F. & Pagliuca, S. (1987). Tettonica transpressiva nel Gargano e rapporti con le catene Appenninica e Dinarica. Mem. Soc. Geol. It, 38, 205-224.
Padhy, S.; Subhadra, N. & Kayal, J.R. (2011). Frequency-dependent attenuation of body and coda waves in the Andaman Sea Basin. Bull. Seismol. Soc. Am. 101 (1), 109-125. http://dx.doi.org/10.1785/0120100032.
Palombo, B.; Ninivaggi, T.; Cogliano, R.; Moschillo, R.; Falco, L.; Mazza, S. & Selvaggi, G. (2022). RecSec: una applicazione web per la consultazione delle Record Sections dei terremoti euro-mediterranei. Rapp. Tec. INGV (in press).
Parvez, I.A.; Sutar, A.K.; Mridula, M.; Mishra, S.K. & Rai, S.S. (2008). Coda Q Estimates in the Andaman Islands Using Local Earthquakes. Pure Appl. Geophys., 165, 1861-1878, https://doi.org/10.1007/s00024-008-0399-4.
Patacca, E. & Scandone, P. (2004). The 1627 Gargano earthquake (Southern Italy): Identification and characterization of the causative fault. J. Seismol. 8, 259-273, https://doi.org/10.1023/B:JOSE.0000021393.77543.1e.
Patacca, E.; Scandone, P. & Mazza, P. (2008). Oligocene migration path for Apulia macromammals: the Central-Adriatic bridge. Bollettino della Società Geologica Italiana, 127, 337-355, ISSN: 00378763.
Petrullo, A.V.; Agosta, F.; Prosser, G. & Rizzo, E. (2017). Cenozoic tectonic evolution of the northern Apulian carbonate platform (southern Italy). Italian Journal of Geosciences, 136(2), 296-311, https://doi.org/10.3301/IJG.2017.08.
Pisconti, A.; Del Pezzo, E.; Bianco, F. & de Lorenzo, S. (2015). Seismic Q estimates in Umbria Marche (Central Italy): hints for the retrieval of a new attenuation law for seismic risk, Geophysical Journal International, Volume 201, Issue 3, 1370-1382, https://doi.org/10.1093/gji/ggv055.
Prudencio, J., Del Pezzo, E., Ibáñez, J. M., Giampiccolo, E., & Patané, D. (2015). Two‐dimensional seismic attenuation images of Stromboli Island using active data. Geophysical Research Letters, 42(6), 1717-1724, https://doi.org/10.1002/2015GL063293.
Pujades, L.G.; Ugalde, A.; Canas, J.A.; Navarro, M.; Badal, F.J. & Corchete, V. (1997). Intrinsic and Scattering Attenuation from Observed Seismic Codas in the Almeria Basin (Southeastern Iberian Peninsula). Geophys. J. Int., 129, 281-291, https://doi.org/10.1111/j.1365-246X.1997.tb01581.x.
QGIS. Available online: https://www.qgis.org/it/site/index.html (accessed on 28 May 2021).
Rota, F. A. & Fichera, R. (1987). Magnetic interpretation related to geo-magnetic provinces: the Italian case history. Tect., 138(2-4), 179-196, https://doi.org/10.1016/0040-1951(87)90038-2.
Rovida, A.; Locati, M.; Camassi, R.; Lolli, B.; Gasperini, P. & Antonucci, A. (2022). Catalogo Parametrico dei Terremoti Italiani (CPTI15), versione 4.0. Istituto Nazionale di Geofisica e Vulcanologia (INGV), https://doi.org/10.13127/CPTI/CPTI15.4.
Salvi, S.; Quattrocchi, F.; Brunori, C. A.; Doumaz, F.; Angelone, M.; Billi, A.; et al. (1999). A multidisciplinary approach to earthquake research: implementation of a geochemical geographic information system for the Gargano Site, Southern Italy. Nat. Hazards 20, 255-278, https://doi.org/10.1023/A:1008105621134.
Sato, H. (1977). Energy propagation including scattering effect: single isotropic scattering approximation. J. Phys. Earth, 25, 27-41, https://doi.org/10.4294/jpe1952.25.27.
Sato, H. & Fehler, M.C. (2008). Earth Heterogeneity and Scattering Effects on Seismic Waves. Springer-Verlag, New York, ISSN 0065-2687.
Scherbaum, F. (2001). The digital anti-alias filter. In Of Poles and Zeros, 117-136. Springer, Dordrecht, https://doi.org/10.1007/978-1-4020-6861-4_8.
Sharma, B., Chingtham, P., Sutar, A. K., Chopra, S., & Shukla, H. P. (2015). Frequency dependent attenuation of seismic waves for Delhi and surrounding area, India. Annals of Geophysics, 58(2), 0216, doi:10.4401/ag-6636.
Shengelia, I., Jorjiashvili, N., Godoladze, T., Javakhishvili, Z., & Tumanova, N. (2020). Intrinsic and Scattering Attenuations in the Crust of the Racha Region, Georgia. Journal of Earthquake and Tsunami, 14(02), 2050006, https://doi.org/10.1142/S1793431120500062.
Sil, A.; Kumar, V. N. & Venketesh, C. (2022). Frequency-dependent quality factor of body waves in the Kathmandu region, Nepal. Natural Hazards Research, 2(3), 193-201, https://doi.org/10.1016/j.nhres.2022.06.002.
Speranza, F. & Chiappini. M. (2002). Thick-skinned tectonics in the external Apennines, Italy: New evidence from magnetic anomaly analysis. J. Geophys. Res., 107(B11), ETG-8, https://doi.org/10.1029/2000JB000027.
Stein, S. & Wysession, M. (2003). An Introduction to Seismology, Earthquakes and Earth Structure. Blackwell, Malden, MA, https://doi.org/10.1017/S0016756803318837.
Stucchi, M.; Meletti, C.; Montaldo, V.; Akinci, A.; Faccioli, E.; Gasperini, P.; Malagnini, L. & Valensise G. (2004). Pericolosità sismica di riferimento per il territorio nazionale MPS04 [Data set]. Istituto Nazionale di Geofisica e Vulcanologia (INGV), https://doi.org/10.13127/sh/mps04/ag.
Talebi, A., Rahimi H., Moradi, A., Mirzaei, M. & Koulakov, I. (2021). Qp, Qs, Qc, Qi, and Qsc Attenuation Parameters in the Zagros Region, Iran. Pure and Applied Geophysics, 178(11), 4487-4505, https://doi.org/10.1007/s00024-021-02879-9.
Tallarico, A. (2013). OTRIONS project. http://www.otrions.uniba.it/. Accessed May 2018.
Thirunavukarasu, A.; Kumar, A. & Mitra, S. (2017). Lateral Variation of Seismic Attenuation in Sikkim Himalaya. Geophys. J. Int., 208, 257-268, https://doi.org/10.1093/gji/ggw384.
Tripaldi, S. (2020). Electrical signatures of a permeable zone in carbonates hosting local geothermal manifestations: Insights for the deep fluid flow in the Gargano area (south-eastern Italy). Boll. Geofis. Teor. Appl., 61, 219-232, https://doi.org/10.4430/bgta0312.
Tselentis, G.A. (1998). Intrinsic and scattering seismic attenuation in W. Greece. Pure Appl. Geophys. 153, 703-712, https://doi.org/10.1007/s000240050215.
Tuvè, T.; Bianco, F.; Ibáñez, J.; Patanè, D.; Del Pezzo, E. & Bottari, A. (2006). Attenuation Study in the Straits of Messina Area (Southern Italy). Tectonophysics, 421, 173-185, https://doi.org/10.1016/j.tecto.2006.04.005.
Ugalde, A., Carcolé, E., & Vargas, C. A. (2010). S-wave attenuation characteristics in the Galeras volcanic complex (south western Colombia). Physics of the Earth and Planetary Interiors, 181(3-4), 73-81, https://doi.org/10.1016/j.pepi.2010.04.009.
Vedova, B.D.; Bellani, S.; Pellis, G. & Squarci, P. (2001). Deep temperatures and surface heat flow distribution. In: Vai, G.B., Martini, I.P. (eds) Anatomy of an Orogen: the Apennines and Adjacent Mediterranean Basins. Springer, Dordrecht, https://doi.org/10.1007/978-94-015-9829-3_7.
Vieira Barros, L.; Assumpção, M.; Quintero, R. & Ferreira, V.M. (2011). Coda Wave Attenuation in the Parecis Basin, Amazon Craton, Brazil: Sensitivity to Basement Depth. J. Seism., 15, 391-409, https://doi.org/10.1007/s10950-011-9231-1.
Wennerberg, L. (1993). Multiple-scattering interpretations of coda-Q measurements. Bull. Seismol. Soc. Am., 83, 279-290, https://doi.org/10.1785/BSSA0830010279.
Wu, R.S. (1985). Multiple scattering and energy transfer of seismic waves – separation of scattering effect from intrinsic attenuation – I. Theoretical modelling. Geophys. J. R. astr. Soc., 82, 57-80, https://doi.org/10.1111/j.1365-246X.1985.tb05128.x.
Yoshimoto, K. (2000). Monte Carlo simulation of seismogram envelopes in scattering media. J. Geophys. Res. 105, 6153-6161, https://doi.org/10.1029/1999JB900437.
Yoshimoto, K.; Sato, H. & Ohtake, M. (1993). Frequency-dependent attenuation of P and S waves in the Kanto area, Japan, based on the coda-normalization method. Geophysical Journal International, 114(1), 165-174, https://doi.org/10.1111/j.1365-246X.1993.tb01476.x.
Zeng, Y. (1991). Compact solutions for multiple scattered wave energy in time domain. Bulletin of the Seismological Society of America, 81(3), 1022-1029, DOI:10.1785/BSSA0810031022.

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\({Q}_{\beta }\left(f\right)=(20\pm 3){f}^{1.34\pm 0.10}\)	\({Q}_{\beta }^{-1}=(51 \pm 4){{10}^{-3}f}^{-1.34\pm 0.06}\)	(8)
\({Q}_{c}\left(f\right)=\left(37\pm 2\right){f}^{1.25\pm 0.05}\)	\({Q}_{c}^{-1}=(27 \pm 1){10}^{-3}{f}^{-1.25\pm 0.03}\)
\({Q}_{s}\left(f\right)=\left(40\pm 9\right){f}^{1.52\pm 0.22}\)	\({Q}_{s}^{-1}=(25 \pm 6){10}^{-3}{f}^{-1.52\pm 0.22}\)
\({Q}_{i}\left(f\right)=\left(32\pm 2\right){f}^{1.27\pm 0.07}\)	\({Q}_{s}^{-1}=(31 \pm 1){10}^{-3}{f}^{-1.27\pm 0.03}\)

Q_β, Q_c, Q_i and Q_s of the Gargano Promontory (Southern Italy)

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Geological And Seismological Setting Of The Studied Area

3. Earthquake Dataset

4. Methods And Results

4.1. Q_β estimation

4.2. Processing for Q_c estimation

4.3. Separation of \({Q}_{i}\) and \({Q}_{s}\) effects

4.4 Dependence of \({Q}\) on\({f}\)

5. Discussion And Conclusions

Declarations

References

Additional Declarations

Status:

Journal Publication

Version 1

Qβ, Qc, Qi and Qs of the Gargano Promontory (Southern Italy)

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. Geological And Seismological Setting Of The Studied Area

3. Earthquake Dataset

4. Methods And Results

4.1. Qβ estimation

4.2. Processing for Qc estimation

4.3. Separation of \({Q}_{i}\) and \({Q}_{s}\) effects

4.4 Dependence of \({Q}\) on\({f}\)

5. Discussion And Conclusions

Declarations

References

Additional Declarations

Status:

Journal Publication

Version 1

Q_β, Q_c, Q_i and Q_s of the Gargano Promontory (Southern Italy)

4.1. Q_β estimation

4.2. Processing for Q_c estimation