Synchronization between tides and sustained oscillations of the hydrothermal system of Campi Flegrei (Italy)

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1 Article Volume 14, Number 8 2 August 2013 doi: ISSN: Synchronization between tides and sustained oscillations of the hydrothermal system of Campi Flegrei (Italy) E. De Lauro, S. De Martino, and M. Falanga Dipartimento di Ingegneria dell Informazione, Ingegneria Elettrica e Matematica Applicata, Universita di Salerno, Fisciano, Salerno, Italy (demartino@sa.infn.it) S. Petrosino Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Napoli Osservatorio Vesuviano, Naples, Italy [1] Long continuous seismic data recorded at five broadband seismic stations during 2006 at Campi Flegrei caldera have been analyzed. Introducing a coarse-grained method, we evaluate the time evolution of amplitude and polarization of the seismic noise in the frequency band common to long-period events. The series are modulated on tidal time scales: the root-mean square is basically dominated by solar contribution, while the azimuth of the polarization vector shows lunar diurnal and semidiurnal constituents. In addition, we find that in the frequency band common to long-period events the azimuths are polarized toward a specific area, suggesting that these persistent oscillations can be induced by the activity of the shallow geothermal reservoir. Components: 6,271 words, 5 figures, 1 table. Keywords: sustained hydrothermal tremor; Campi Flegrei Caldera; polarization analysis; tidal modulation; synchronization. Index Terms: systems Volcano seismology; 8440 Calderas; 0450 Hydrothermal systems; 5770 Tidal forces; 4430 Complex Received 12 December 2012; Revised 3 April 2013; Accepted 12 April 2013; Published 2 August De Lauro, E., S. DeMartino, M. Falanga, and S. Petrosino (2013), Synchronization between tides and sustained oscillations of the hydrothermal system of Campi Flegrei (Italy), Geochem. Geophys. Geosyst., 14, , doi:. 1. Introduction [2] In recent years, there has been a growing interest in the study of synchronization mechanisms between slow variables and fast-oscillating parameters in systems with a hierarchy of time scales. These phenomena have often been observed in many branches of natural sciences [see Pikovsky et al., 2001; Capuano et al., 2011, 2012, De Martino et al., 2011a, 2011b]. In some cases, like in studies of fully developed hydrodynamic turbulence, such scales cannot be separated but form a cascade, making the description of the dynamics extremely difficult [Bogoliubov and Mitropolsky, 1961]. However, if well-separated time scales can be attributed to particular variables, then a significant simplification of system complexity is possible. When the fast variables exhibit a nontrivial dynamics, a simplified description is based on introducing suitable methods of averaging and/or coarse graining [Omelchenko et al., 2010] American Geophysical Union. All Rights Reserved. 2628

2 [3] This is certainly true in the framework of volcano seismology, where active volcanoes display a variety of phenomena on different time scales. In this context, a number of observations regarding the analysis of long-time series, such as number of seismic events, energy release of volcanic earthquakes/tremor, ground movement, and gravity variations, often show a periodical behavior that can be related to dynamics of the same volcano on a variety of time scales from years to seconds. This information is relevant to the state of the volcano and may be useful for eruption forecasting and monitoring improvement. For instance, coarsegrained variables have been shown to vary with nonstationary phenomena, such as volcanic eruptions [De Martino et al., 2011a, 2011b]. [4] In time series related to seismovolcanic activity, the slow variables often correspond to tidal constituents (e.g., diurnal and/or semidiurnal). Many authors attribute this modulation of the geophysical series to the earth tidal stress field, which acts as an external triggering mechanism of the activity of the volcano [McNutt and Beaven, 1981; Rydelek et al., 1988]. Recently, De Lauro et al. [2012] observed a diurnal modulation of the temporal energy release of long-period (LP) events at Campi Flegrei, which they ascribe to a tidal influence on the mechanism of fluid charge/discharge in the branches of the hydrothermal system. On the other hand, some authors [see e.g., Neuberg, 2000] propose other possible modulation mechanisms related to the variations of atmospheric temperature, barometric pressure, and ocean loading. In that case, the observed phenomena are directly influenced by the daily cycle of the Sun (S 1 and S 2, solar diurnal and semidiurnal tidal constituents, respectively). [5] The external tidal modulation is often considered as a disturbance distorting the original seismic signals. Seismologists try to filter this noise, and a lot of papers can be found in literature on this subject. In particular, it has been observed that the seismic noise recordings by long period seismometers contain tidal signals. The vertical component is less noisy than the horizontal ones and the predicted tidal signals are in agreement with the observations. On the contrary, the horizontal components can exhibit strong discrepancies with respect to theoretical signals, due to the local effects such as topography and/or geological inhomogeneities [see e.g., Lambotte et al., 2006, and references therein]. [6] However, periodicities on tidal scale in seismic recordings can be investigated to obtain significant information on both the volcanic structure and source. Recently, De Martino et al. [2011a, 2011b] at Stromboli volcano identified a 3 day periodic signal detected as volumetric deformation by the strainmeter and as modulation in the explosion amplitude by the seismometers. The observed long periodicity suggests a possible role of the tides in the dynamics of the volcanic processes that yields the authors to hypothesize a correlation between earth tides and the phenomena of nonequilibrium. Moreover, this periodic signal has been detected before the , and 2007 effusive episodes. This case shows that tidal oscillations observed in seismic time series represent a powerful tool to be used for better modeling the volcanic system and as a possible precursor rather than a disturbance to be removed. [7] Before establishing whether time records of geophysical parameters really contain slow variables affecting the fast ones and what process produces them, it is important to characterize the background signal in order to allow a comparison between the preeruptive/posteruptive state and the periods of volcanic activity. In this context, Campi Flegrei caldera is a good candidate to be investigated, because it is an area affected by volcanic, seismic, and deformation phenomena on many time scales [Orsi et al., 1999; Del Gaudio et al., 2010]. Indeed, different geophysical signals (e.g., seismic, gravimetric, vertical ground, and sea deformations) recorded in this area have been widely analyzed by many authors, who find tidal periodicities in the corresponding time series [Berrino and Corrado, 1991; Marzocchi et al., 2001; Ricco et al., 2007; De Lauro et al., 2012]. [8] In the present work, we analyze continuous seismic signal recorded at Campi Flegrei during the year 2006 at five broadband-seismic stations, looking in particular at the time evolution of amplitude and polarization parameters. Moreover, for the station with the best signal-to-noise ratio (SNR), we extend the analysis to the period Campi Flegrei and Data Set [9] Campi Flegrei volcanic complex is a nested caldera originated by two large collapses occurred during the Campanian ignimbrite (39 ka) and the Neapolitan yellow tuff (15 ka) eruptions, and it is located to the west of the town of Naples (southern Italy). The caldera is affected by the phenomenon of bradyseism, a continuous slow subsidence, interspersed with fast ground uplifts accompanied by 2629

3 seismicity. The most relevant ground deformation episodes occurred in and and generated a net uplift of 3.5 m around the town of Pozzuoli [Orsi et al., 1999]. Since that time, minor uplift episodes (i.e., 2000 and ) occurred [Saccorotti et al., 2007; D Auria et al., 2011]. [10] The presence of geothermal reservoirs plays an important role in determining the dynamics of the caldera. Velocity tomography from active and passive data provides evidence of a hydrothermal basin beneath Pozzuoli town at a depth of about 1.5 km [Vanorio et al., 2005; Battaglia et al., 2008]. Moreover, attenuation tomography indicates two more fluid-permeated volumes: one corresponding to the Agnano acquifer and the other located southwestern to the Solfatara and probably connected to the Pozzuoli basin. Indications of a medium saturated by hydrothermal fluids also arise from the small-scale shallow crustal structure of the Solfatara volcano retrieved by seismic-noise measurements and morphostructural analysis [Petrosino et al., 2012]. In particular, in the crater of Solfatara and in the area of Pisciarelli (eastern to the Solfatara), the geothermal activity drives surface phenomena (fumaroles, mud pool), as described in many papers [see Chiodini et al., 2010, and references therein]. The intrusion and migration of the fluids to the shallower hydrothermal system is the most plausible mechanism that determines unrest phases at Campi Flegrei caldera [De Natale et al., 2006]. The recent deformation episode of has been attributed to two hot fluid batches injected from a deeper reservoir below the Pozzuoli bay, reaching the surface at Pozzuoli and Solfatara area [D Auria et al., 2012]. This uplift was characterized by a large release of seismic energy and by the occurrence, in October 2006, of the most remarkable LP swarm ever recorded in the area. The LP activity lasted for about 1 week and climaxed on days 26, 27, and 28, when hundreds of events were counted [Saccorotti et al., 2007; Ciaramella et al., 2011]. The LP signals appear like spindleshaped monochromatic oscillations, and their spectra exhibit a main peak at frequency around 0.8 Hz attributed to a source effect [Cusano et al., 2008]. These LP events have been studied in detail and have been attributed to the fluid-rock interaction in the hydrothermal system [Cusano et al., 2008; D Auria et al., 2011; Falanga and Petrosino, 2012; De Lauro et al., 2012]. [11] Data used for the present analysis were collected by five broadband three-component seismic stations of the Campi Flegrei seismic monitoring network, managed by the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Vesuviano (INGV-OV) (for details, see Saccorotti et al., [2007]). Three-component Lennartz LE-3D/20s seismometers with transduction constant G ¼ 1000 V/m/s operate at ASB2, OMN2, and AMS2 sites, while stations BGNG and TAGG are equipped with Guralp CMG40T 60 s geophones, having transduction constant G ¼ 800 V/m/s. The sampling rate of all the digital stations is 125 Hz. An example of recording is shown in Figure Methods and Results [12] The slow quantities we investigate are obtained by coarse-graining the variables related to the background seismic signal. A very intuitive coarse-grained variable is the root-mean square (RMS) of the seismic amplitude because it is a measure of the energy [Lay and Wallace, 1995]. [13] We compute RMS over 1 hour long samples of the seismic noise recorded during 2006 at all the stations, using both the single components of motion (N-S, E-W, and vertical) and their average value. The interesting frequency content for LP is Hz, thus we band-pass filter the seismic signals in that range. LPs are generated in the conduits of the hydrothermal system in the form of self-oscillations with a typical spectrum [Bianco et al., 2012; De Lauro et al., 2012]; therefore, we expect that this particular frequency band contains the imprinting of the volcanic source. Notice that this band is not affected by anthropogenic activity, which has relevant effects for frequencies greater than 1 Hz and causes daily and weekly cycles in the noise amplitude [see, De Lauro et al., 2012]. Time evolution of the average value of the RMS over the three components of motion and the relative spectral amplitude are reported in Figure 2. The analysis clearly provides evidence of the typical diurnal constituents, with a dominant S 1, suggesting a tidal influence on the seismic noise in the LP band. The same peaks also appear in the spectra of the individual components. [14] The Rayleigh criterion assures that two tidal constituents of frequencies f j and f k can be distinguished if the latter satisfies the relation [Godin, 1972]: Dt f j f k 1; j 6¼ k; where Dt is the length of the record. For our analysis, the criterion is fulfilled with a resolution on 2630

4 Figure 1. One hour long sample of seismic signal recorded at all the three component stations on 1 June 2006 at 06:00 UT. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] the order of day 1, thus allowing a fine distinction among the tidal constituents. [15] A further analysis has been performed over a 4 year long data set from 2007 to 2010 at station ASB2, which has the highest SNR. The results confirm the periodicities observed in 2006 and support the observations by Lambotte et al. [2006] that the amplitude of the seismic noise contains information on the tidal constituents. [16] To have more insight into the characteristics of the background noise, we propose the time evolution of the polarization parameters as an interesting coarse-grained variable. In the literature, the polarization method [Montalbetti and Kanasevic, 1970] is usually applied to transients or short-time windows of continuous signals [see e.g., Acernese et al., 2004]. Here, we perform this analysis on the continuous seismic noise recorded during the entire year We apply the covariance matrix technique [see e.g., De Lauro et al., 2009a, 2009b] to the filtered signal in the Hz frequency band, and we estimate the polarization parameters: rectilinearity (RL), azimuth and incidence angle of the polarization vector over a 2 s long time window, with an overlap of 96%. [17] In order to enhance tidal-scale phenomena, we apply the coarse-graining procedure considering the dynamics stationary on time scale of a few minutes and calculating, by using circular statistics [Berens, 2009], the average values of RL, azimuth, and incidence angle over 15 min long time windows. Finally, we select the latter two parameters with RL higher than 0.7, because they are indicative of body waves [Montalbetti and Kanasevic, 1970]. From this analysis, we observe that more than 90% of the incidence angles are greater than 80 for the entire analyzed period and for all the stations (Figure 3). These values are indicative of horizontal polarization and are compatible with a shallow source [Vidale, 1986]. An interesting 2631

5 Figure 2. Time evolution of the amplitude estimated by RMS of the seismic recordings at all stations and relative periodogram. A clear diurnal periodicity can be observed for the RMS series filtered in the Hz frequency band as confirmed by spectra dominated by a strong peak at 24:00 h (S 1 ). [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] 2632

6 Figure 3. Relative frequency histograms of the incidence angle at all stations for the continuous seismic signal recorded in More than 90% of the incidence angles are greater than 80. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] observation regarding the time evolution of the azimuths arises from Figure 4: each station is characterized by a predominant direction of the polarization vector, although some fluctuations affect the time series. Specifically, for each station, the azimuth has an oscillatory character (of about ) around a well-defined mean value. It is important to note that the oscillations occur synchronously at all the stations (zoom in Figure 4, right bottom), thus excluding instrumental or local/site effects and leading to hypothesize a common origin (whether internal or external/ induced). The largest peaks in the amplitude values observed on time scales of the order of days in the azimuth series, especially evident at BGNG station, can be ascribed to the occurrence of bad meteorological conditions. This is supported by the comparison between azimuth and atmospheric pressure time series (Figure 4). Indeed, low-pressure values can cause an increase in the seismic noise amplitude, and coastal stations are more affected [Bianco et al., 2012]. [18] The overall pattern of the azimuth values over the entire year is represented by the rose plots in Figure 5. As shown, the average value of the azimuth points toward a specific region within the Campi Flegrei caldera. [19] In order to better investigate the nature of these oscillations, we perform a spectral analysis on the azimuth time series. The periodogram of Figure 4 shows predominately diurnal and semidiurnal components. Moreover, even longer periodicities not reported in the spectrum of Figure 4 corresponding roughly to days are observed Figure 4. Time evolution of the polarization azimuths at all stations and relative periodogram. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] 2633

7 Figure 5. Rose plots of the polarization azimuths calculated over the entire year The bins of the rose plots were chosen equal to 30, to account for the fluctuations of the azimuth values. in the time domain. We note that the lunisolar fortnightly component (M f ) plays an important role in modulating the semidiurnal tidal constituents of the water-level oscillations in a semienclosed sea basin [Capuano et al., 2011]. As in the case of RMS analysis, the length of the series guarantees that the Rayleigh criterion is fulfilled, allowing a fine discrimination among the tidal constituents. As reported in Table 1, polarization azimuth has a dominating 12 h periodicity related to the S 2, except for BGNG and ASB2. For BGNG, the predominant components are S 1 (solar) and K 1 (Sun- Moon declination, likely influenced by sea-level oscillations), which were also observed in the tiltmetric time series recorded in 2006 at the same site [Ricco et al., 2007]. In addition, the spectrum of ASB2 shows the typical lunar constituents O 1 and M 1. Therefore, the polarization pattern of seismic noise recorded at these two stations is dominated by moon tidal effects. [20] Notice that the presence of tidal diurnal/semidiurnal constituents affect the estimates of azimuths with a variability up to 15. This has to be taken into account for accurate and precise estimates of the polarization parameters, including source location and radiation pattern. [21] Ocean loading could affect the tidal oscillation recordings for the stations located in proximity of the sea, like BGNG. Indeed, the perturbations due to the global ocean and the Mediterranean Sea loading for the Italian Peninsula are of about 10% 20% [Chiaruttini, 1976], which would lead to a correction of less than 5 to the average value of the azimuth retrieved for BGNG. Topography could also induce perturbations; however, the seimometers used for the present analysis are located in an almost flat area, with characteristic slopes [Meertens and Wahr, 1986] on the order of 0.1. The corresponding correction for the topographic effect is less than 1%, thus negligible. [22] In contrast to the RMS analysis that provides the same results for the entire period , the time series of the azimuth of the polarization vector obtained for the data set at station ASB2 show a dominant solar diurnal component (S 1 ), while O 1 and M 1 components observed for the 2006 data are absent. 4. Discussion [23] From the analysis of a long data set, we observe that the seismic background noise in the LP frequency band at Campi Flegrei is polarized toward a specific area that corresponds to a fluidpermeated region [De Siena et al., 2010], suggesting a source property. A possible origin of this polarized signal could be related to the activity of the shallow geothermal reservoir; therefore, we could call it sustained hydrothermal tremor. Similar oscillations but on different time scales in hydrothermal systems have been detected in other caldera volcanoes. One of the first observation of this phenomenology has been described in the pioneering work of Kieffer [1984], who studied the source of periodic hydrothermal noise at Old Faithful Geyser, Yellowstone (USA), and hypothesized possible mechanisms related to fluid motion. Temporal fluctuation of microseismic noise at Yellowstone have been observed by Tikku et al. [2006] too; these authors detect a variation over 8 day long records of the RMS amplitude and gravity data related to active hydrothermal processes. At Nysiros, caldera (Greece) oscillations on the order of min observed in 10 day long records of geodetic, gravimetric, seismic, and electromagnetic data have been interpreted as shortterm processes associated to gas instability [Gottsmann et al., 2007]. Laboratory experiments aimed Table 1. Tidal Constituents Affecting Polarization Azimuth at All Stations Tidal Constituents AMS2 ASB2 BGNG TAGG OMN2 O 1 S 1 K 1 - M 1 S 2 S

8 at reproducing the cyclic oscillations in the level of seismic noise, related to the interaction of crater lakes with hydrothermal systems, have been carried out by Vandemeulebrouck et al. [2005], and the results have been compared with two natural systems in New Zealand (Inferno Crater Lake and Ruhapehu). Finally, longer seismic recordings (47 days) available at Fogo Volcano (Capo Verde Republic) have allowed Custodio et al. [2003] to identify well-resolved diurnal and semidiurnal components in the spectrum of the RMS series of seismic noise, suggesting the occurrence of tidal modulation. [24] At Campi Flegrei caldera, we observe that the time evolution of coarse-grained variables, such as polarization parameters and RMS series, show diurnal/semidiurnal tidal modulations. In the RMS analysis, the tides have a mixed character but with a strong dominance of the solar diurnal S 1, which may be related to thermal effects (lunar components are negligible). Instead, the azimuth time evolution is characterized by the dominance of solar semidiurnal and solar/lunar diurnal periodicities. Specifically, semidiurnal tides are basically originated by the principal solar (S 2 ) contribution, except for BGNG and ASB2. For these stations, the predominant components are due to solar and lunar declination effects (K 1 ) and to the main lunar (O 1 and M 1 ) and solar (S 1 ) constituents. On the contrary, no typical lunar contributions (O 1, M 1, and K 1 ) are observed in the azimuth time series from 2007 to 2010 (as shown in the analysis conducted until 2010). This can be an indication that the lunar constituents are a marker of the 2006 miniuplift crisis. We remark that Earth tides are basically due to a synchronization among the Earth motions, the planets gravitational attraction, and the local characteristics (rheology, geometry and basin effects, and oceanic loading) [see e.g., Melchior, 1978]. Variations in the local characteristics can induce changes in the amplitude ratios among the standard frequency peaks and/or enrichments in the tidal spectrum. In line with these thoughts, recently, De Lauro et al. [2012] have observed a diurnal modulation of the temporal energy release of LP events at Campi Flegrei, which they relate to the mechanism of fluid charge/discharge in the branches of the hydrothermal system. In the present work, we place stress on the role of fluids both in LP activity and in hydrothermal sustained oscillations and how tidal periodicities like the lunar diurnal (e.g., O 1 and M 1 ) can detect variations of local parameters. [25] Indeed, in 2006 many geochemical and seismological observations provide evidence of anomalous activity and expulsion of dark mud at the fumaroles of Pisciarelli, increase of the flow rate at the fumaroles of Solfatara [Chiodini et al., 2010], and huge swarms of LP events [Saccorotti et al., 2007]. On the basis of the variations of geochemical indicators like the CO 2 =CH 4 and CO 2 =H 2 O and the sharp increase in the CO 2 flux in September and November 2006, Chiodini et al. [2012] have recently estimated the amount of magmatic fluid injected into the shallower hydrothermal system by performing numerical simulations. For the 2006 injection episode, they obtain a mass equal to 4.1 Mt. In this dynamical context, D Auria et al. [2012] hypothesize that two fluid protrusions departed from a reservoir below Pozzuoli bay, further expanded rapidly toward the center of caldera and reached the surface in the area of Pozzuoli and Solfatara. On this basis, we can infer that the enrichment of the tidal constituents in the background signal observed in 2006 is likely to be attributed to the fluid injection from the geothermal reservoir of Pozzuoli toward the shallower hydrothermal system of the Solfatara. It is noteworthy that statistically significant lunar diurnal constituents (besides the solar ones) were also observed in the time history of gravimetric and seismic data during the bradyseismic crises [Berrino and Corrado, 1991], which has been interpreted as an unrest episode caused by the migration of fluids in the caldera hydrothermal system [Battaglia et al., 2006]. Probably in , we do not observe lunar tidal effects due to lower quantity of fluids, and only solar diurnal and semidiurnal components are present in the seismic noise. Of course, this hypothesis needs to be further investigated by future observations in periods of intense hydrothermal activity. 5. Conclusions [26] The analysis of the long continuous seismic data set during the year 2006 at Campi Flegrei allows us to detect, for the first time, low-frequency persistent oscillations of the caldera induced by the activity of the shallow geothermal reservoir and modulated by a tidal contribution on the diurnal/ semidural time scale. This is representative of a synchronization mechanism between slow and fast variables. Finally, more investigations of continuous measurements of ground movement, seismicity, and gravity changes are needed in order to establish a transfer function between earth tides 2635

9 and activity in Campi Flegrei on longer time scale. In this perspective, coarse-grained variables could be effective markers in detecting variations of the dynamical state of the system and providing new elements for the volcanic risk assessment. Acknowledgment [27] We are sincerely grateful to the mobile seismic network of the INGV-OV for providing the data. We wish to thank Francesca Bianco for the many helpful discussions. References Acernese, F., A. Ciaramella, S. De Martino, M. Falanga, C. Godano, and R. Tagliaferri (2004), Polarisation analysis of the independent component of low frequency events at Stromboli volcano (Eolian Islands Italy), J. Volcanol. Geotherm. Res., 137, , doi: /j.jvolgeores Battaglia, M., C. Troise, F. Obrizzo, F. Pingue, and G. De Natale (2006), Evidence of fluid migration as the source of deformation at Campi Flegrei caldera (Italy), Geophys. Res. Lett., 33, L01307, doi: /2005gl Battaglia, M., A. Zollo, J. Virieux, and D. 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