Passive seismic experiment ‘AniMaLS’ in the Polish Sudetes (NE Variscides)

The paper presents information about the seismic experiment AniMaLS which aims to provide a new insight into the crust and upper mantle structure beneath the Polish Sudetes (NE margin of the Variscan orogen). The seismic network 10 composed of 23 temporary broadband stations was operated continuously for about two years (October 2017 and October 2019). The dataset was complemented by records from 8 permanent stations located in the study area and in the vicinity. The stations were deployed with inter-station spacing of approximately 25-30 km. As a result, recordings of local, regional and teleseismic events were obtained. We describe the aims and motivation of the project, the stations deployment procedure, as well as the characteristics of the temporary seismic network and of the permanent stations. Furthermore, this paper includes a 15 description of important issues like: data transmission set-up, status monitoring systems, data quality control, near-surface geological structure beneath stations and related site effects etc. Special attention was paid to verification of correct orientation of the sensors. The obtained data set will be analysed using several seismic interpretation methods, including analysis of seismic anisotropy parameters, with the objective of extending knowledge about the lithospheric and sublithospheric structure and the tectonic evolution of the study area. 20


Introduction
The passive seismic experiment AniMaLS (Anisotropy of the Mantle beneath the Lower Silesia) aims at studying the structure of the crust and upper mantle of the Polish Sudetes and Sudetic Foreland, as well as the processes of their orogenic evolution, using seismological and petrological methods. Up to now, the upper mantle in this region was only sparsely 25 sampled by seismic data (Wilde-Piórko et al., 1999;Wilde-Piórko et al., 2008). A temporary seismic array deployed in the Polish Sudetes in a period from October 2017 to October 2019 collected broadband seismological data, which are an important prerequisite to image the lithospheric and sub-lithospheric properties of the Sudetes and the Lower Silesia.
The Lower Silesian region comprises two major tectonic units: the Sudetes mountains and the Sudetic Foreland, forming 30 north-eastern part of the Bohemian Massif (BM) and representing NE termination of the Variscan internides in the Central Europe (Figures 1 and 2). The lithosphere of this area was consolidated during the Variscan orogeny (Late Devonian to Early Carboniferous) as the result of multi-stage collision between paleocontinents of Laurussia and Gondwana and accretion of a group of smaller, Gondwana-derived, Proterozoic to Palaeozoic microplates (Armorican Terrane Assemblage, ATA) at the Laurussia margin (Franke et al., 2017). Accreted Neoproterozoic to Cambrian metamorphic blocks and nappe complexes, as 35 well as early Palaeozoic volcano-sedimentary rocks, were intruded by several Carboniferous granitoid plutons. In some parts, the region of the Sudetes was covered by sedimentary sequences of Late Carboniferous syn-and postorogenic intramontane basins and Cretaceous to Cenozoic cover (Mazur et al., 2007).
At present, the lithosphere of the Sudetes is a mosaic of several units with distinct tectonic histories and with consolidation ages ranging from the upper Proterozoic to the Quaternary. The area is cut by three major right-lateral faults with WNW-40 ESE general orientation: Odra Fault Zone (OFZ), Sudetic Marginal Fault (SMF), and Intra-Sudetic Fault (ISF) (Aleksandrowski et al., 1997). The SMF divides the Sudetes block into the Sudetes mountains and Sudetic Foreland ( Figure   2). The mountain ridge originated from the Cenozoic rejuvenation and differential uplift of an old Variscan area due to collision-related intraplate stress at the Alpine foreland during the last episode of formation of the Alps and Carpathians. As a result of the uplift, the Sudetes mountains are the most exposed fragment of the NE Variscan basement in Europe (Mazur 45 et al., 2007).
Due to complex structure of the region, several controversies and open questions concerning its evolution are still presente.g., on the validity of the strike-slip tectonics model vs. oroclinal bending model as general mechanism responsible for the present-day lithospheric structure (Mazur et al., 2020), as well as more detailed issues, concerning, for instance, the roles of the regional fault-and shear zones, the relationships between individual tectonic units and their ties with the structure and 50 deformations of the underlying mantle. Therefore, presented project attempts to provide new data on the structure, tectonic evolution and geodynamics of the NE Variscides with the use of seismic methods, based on recordings of local, regional and teleseismic events. The depth range of the experiment comprises the crust and the mantle lithosphere, the lithosphereasthenosphere boundary (LAB) and the sub-lithospheric upper mantle.

70
Interpretation of the data with P-and S-receiver function will be attempted in order to trace the lithospheric and deeper (410 km and 660 km) discontinuities. The project seeks to determine with more detail seismic anisotropy of the mantle with the use of the shear-wave splitting method applied to SKS and SKKS phases. The analysis of the P-wave polarization may also contribute to anisotropy studies. Seismic anisotropy is closely related to mantle processes -its character reflects the degree and the direction of tectonic deformations of the lithosphere (or the orientation of the sub-lithospheric mantle flow). Potential 75 spatial variations of anisotropy parameters can be a proxy for discrimination between lithospheric blocks with different petrological composition or subject to different tectonic evolution. Obtained seismic results will be complemented with information from ongoing petrological studies of anisotropy of the mantle xenoliths in the Cenozoic volcanics, abundant in the Sudetes (Puziewicz et al., 2015) in order to get more constraints on the nature of the mantle anisotropy. Acquired recordings of local events may also be useful for other fields of seismological research, e.g., for studies of the local 80 seismicity, seismotectonics and seismic hazard assessment.
The main purpose of this paper is to present the research objectives of the AniMaLS project, technical information concerning the data acquisition and obtained dataset. In Sect. 2.1, we describe the characteristics of the temporary seismic 90 network and of the permanent stations in the study area. Also, in Sects 2.2-2.5, we present details of the stations deployment procedure, including the site selection, sensor orientation, data transmission set-up and status monitoring systems. We describe the technical aspects of field measurements, distribution, acquisition parameters of the stations, and stages of data quality control. The near-surface geological setting of the sites is presented in Sect. 2.6. We describe data completeness andpresent data examples in Sect. 3. The noise characteristics, observed site effects and their relation to near-surface geology 95 are discussed in Sect. 3.1. Finally, in Sect. 3.2, attention is paid to the data-based verification of the sensor orientation.
2 Station deployment

The network layout and equipment 100
The AniMaLS seismic network had been deployed between October 2017 and January 2018 and was operated for a period of about two years, until October 2019. Two institutions contributed to the temporary seismic networkthe Institute of Geophysics, Polish Academy of Sciences (IG PAS) provided 10 Güralp CMG-6T (30s corner period) seismometers with Güralp DM24S3EAM data acquisition units and one CMG-6TD 30s seismometer and data acquisition unit. The Institute of Geophysics of the University of Warsaw (IG UW) supplied 12 Reftek-130B data acquisition systems with broadband 6 seismometers Reftek 151-120 "Observer" with bandwidth of 0.0083-50 Hz (120-0.02 s). Additionally, for observations of local seismicity, IG PAS deployed 6 units with short-period (1s corner period) Mark L-4C sensors. All stations had 130 dB dynamic range and used 100 Hz sampling frequency. Timing was provided by GPS receivers. The average inter-station distance in the array was about 25-30 km.
As several permanent seismic stations were operated in the study area, it was possible to enlarge the dataset with recordings 110 of stations: KSP (Polish Seismological Network) and CHVC, DPC, KRLC, MORC, OKC, OSTC, and UPC (Czech Regional Seismic Network), all equipped with 120 s sensors. The short-period (1s-5s sensors) LUMINEOS network, designed by IG PAS for monitoring of the induced seismicity in Legnica-Głogów Copper District (LGCD) (Mirek and Rudziński, 2017) is also in the area we are investigating. The distribution of the AniMaLS stations and permanent seismic stations used in the experiment is shown in detail in Figure 2. The coordinates of the stations, locations names and technical details are 115 summarized in Table 1.

Site selection and array design
Usually, the sites for permanent broad-band seismic stations are carefully selected in areas with extremely low noise. The sensors are located in vaults designed to minimize noise resulting from thermal and atmospheric variations. Such a careful site preparation and installation is often not possible in case of temporary seismic projects, where selection of the location, installation and formal issues (permissions, rental contracts) have to be done in a short time and with limited resources. 125 Additionally, to form a more or less uniform network, the sites should be located at similar inter-station distances, which is another constraint for the site location. When deploying the array, we attempted to obtain a compromise between several factors: low seismic noise, site availability, continuous power supply and high signal level of the mobile telecommunications network (UMTS/LTE). An important issue was high level of security, in order to avoid the damage or loss of the equipment.
Meeting all these requirements was not straightforward, since in most of the locations the level of anthropogenic noise was 130 elevated due to high population density and industrial activities. In these areas, fulfilling both constraints (stations spacing and low noise) has been extremely hard. When possible, we placed the units at the unused basements of buildings, in the outbuildings or in rarely used public utility buildings. The sensors were placed on a hard surfaceconcrete or tiled floor, and in some cases a 5 cm thick granite slab was used for this.

Figure 3: Deployment of seismic stations in the Sudetes: a) Reftek unit during installation, b) Installed Güralp unit, c) datatransmission module -Raspberry Pi microcomputer with UMTS modem and watchdog, d) Installing the UMTS antenna for data transmission.
At the sites, a thermal insulation of the sensor was ensured in a form of a styrofoam box covering the sensor. A few pictures from installation of a typical station are shown in Fig. 3. Each station was powered by power grid system. The 12V power 140 supply was buffered with 40-60 Ah batteries in order to ensure continuous operation of the units in case of the power outages. Near real-time data transfer was done with the use of UMTS/LTE mobile network connection.

Orientation of sensors
A precise orientation of seismic sensor axes with respect to geographical North direction is of great importance during installation of a 3-component seismic station. Incorrect orientation of the seismometer can result in substantial errors when 145 using 3-component methods of interpretation, e.g., in case of shear wave splitting analysis (Ekström and Busby, 2008;Vecsey et al., 2014;Wang et al., 2016). The simplest method of geographical North determination, using a magnetic compass, often results in uncertainty exceeding 5° (Vecsey et al., 2017), which is not satisfactory for some interpretation methods. The modern approach, involving the use of an optical gyrocompass, allows for much higher precision, but requires expensive equipment. 150 Taking these limitations into account, we have designed our own low-cost system for precise orientation of the seismometers deployed in the project. For the determination of the geographical North direction in the field, we used a global navigation satellite systems (GNSS) unit with real-time kinematic positioning (RTK) technology unit and ASG-EUPOS network (Ryczywolski et al., 2008) for receiving location corrections. Two ways for transferring the North direction to the seismometer location was considered. First method was geodetic tachymetry. However, this method is not only time-155 consuming but also causes problems in less accessible locations such as basements. To solve this problem, we developed a simple device for azimuth transfer which makes the process more time-efficient while retaining satisfactory precision.
The core of the device is a MEMS triple axis accelerometer and gyroscope unit MPU-6050, controlled by a single-board Raspberry Pi microcomputer. The data communication between device modules is based on I2C serial protocol over the General Purpose Input Output (GPIO) ports. The code for processing the data from the gyroscope unit was written as a 160 Python script. Raw data from the unit are converted into stable values of the rotation angle of the device. Problem of the gyroscope drift was solved by calibration of the immobile device prior to the measurement phase. During calibration the drift is evaluated, and, based on this, corrections for drift are continuously applied during the measurement.
Orienting the seismometer towards the geographic North with this method is done in two stages. First, GNSS RTK unit is used to obtain precise positions of two points of a baseline outside of the station site and to calculate the azimuth of the 165 baseline as a reference. Next, the azimuth is transferred to the place where the seismometer will be installed. To this end, the gyroscope device is aligned parallel to the baseline using laser pointer, and GNSS-measured reference azimuth value is input to the device. The device is then moved indoor to the station site where it is rotated to North, according to displayed current azimuth, and the N-S line is marked on the floor at the location of the sensor. Finally, to check if the device readings were stable during the North measurement at the site, the device is moved back to the baseline and oriented along it, where, 170 ideally, reference azimuth value should be again displayed. If the value differs substantially from the reference, it indicates excessive/variable drift or other errors, and the measurement is considered to be invalid. The procedure is repeated until 2-3 stable (negligible drift) and consistent measurements are obtained. Assuming availability of the GNSS RTK unit, this method is an affordable solution which allows for orientation of the sensor with error determined in field tests to be at the level of ±2 degrees. Additionally, a data-based verification of the orientations was done with use of polarization analysis. 175 The results are discussed in Sect. 3.2.

Real-time data transmission and data storage
The seismic data were written in the internal storage of the data acquisition units (Güralps -16GB Flash memory, Refteks 2x16GB CF cards) and, simultaneously, they were transmitted in near real-time to dedicated acquisition servers at the IG PAS. Additionally, state of health (SOH) information including temperature, voltage, and mass positions were transmitted.
The data transmission was done using UMTS internet connection, with all devices running IPsec VPN system to securely connect all the stations to the data acquisition server and to protect the system from unauthorized access. The Güralp units were connected to the network using Mikrotik routers with LTE modems. The data transfer to a dedicated CMG-NAM data hub was based on GDI protocol with a back-fill buffer, which allows for handling temporary loss of internet connection and retransmission of missing data packets after the connection is re-established. Connection loss and router/modem hang-up 185 situations were handled by data acquisition unit by an implemented software watchdog, which allowed for three levels of action: (1) soft reset of the modem, (2) power-cycling of the modem, and (3) power-cycling of the unit and of the modem.
For data transmission from Reftek units, a modified system designed at IG UW (Polkowski, 2016), based on Raspberry Pi Linux microcomputers with UMTS or LTE wireless modems was used. The Raspberry Pi units served both as routers and as devices scheduling the data transmission -collecting data from acquisition units and sending them to server (FTP,rsync and 190 SSH protocols). The control scripts (PHP, bash) were designed to check for gaps in transferred data (due to e.g., network connection loss, server or device hang-up) and to schedule data retransmission, if necessary. Hardware watchdog devices, designed at IG UW (Polkowski, 2016), were used to assure automatic restart of the transmitting unit on no connection or hang-up.
Both Güralp and Reftek stations were remotely controlled and monitored using their proprietary software providing a WWW 195 control interface. It allowed for checking the status of the individual units, mass positions, timing, voltages, temperature, as well as setting various recording parameters. For Reftek units, the control interface allowed for monitoring of mass positions and mass centering. Also, automatic mass centering could be triggered if mass voltages exceeded a threshold after a userdefined time.
The near real-time data transfer has well-known advantages -inspection of the current data flow and access to current SOH 200 information is useful for monitoring of the data quality and allows for fast detection of failures, such as power supply malfunctions or timing problems. Also, an increase of the noise level or the signal distortion due to an inadvertent moving or tilting of the sensor can be detected, and necessary station maintenance can be planned. This saves the number of the field trips needed for servicing the stations and helps to quickly reestablish proper acquisition of the seismic data.
The gaps in transmitted data resulting from the lack of UMTS connection were filled by periodic retrieving of the recorded 205 data directly from the data acquisition system memory during stations maintenance in the field, if needed. The transmitted and patched data were stored in miniSEED format. After unification of information in headers, the daily miniSEED files were finally stored in the form of SeisComP Data Structure (SDS)a hierarchical structure with file and directory naming convention which allows for easy access to the data, e.g., with the ObsPy package.

Station timing 210
The seismic studies require exact measurement of absolute time of the seismogram to be able to determine the arrival times of the analysed phases. An incorrect timing may lead to erroneous identification of the phases or incorrect travel-time determination. Currently, the seismic acquisition systems use GPS/GNSS receivers that allow for the synchronization of the internal clock with a high accuracy (±10 μs). However, in practice, technical malfunctions or loss of GNSS signal can introduce timing errors, and such problems should be recognized. If possible, incorrect timing should be corrected during 215 initial data processing, or reported, to avoid using badly timed data for the interpretation. During the data acquisition for the project, an important problem with timing occurred for five Reftek acquisition units due to the "Week Number Roll-Over" (WNRO) issue in the GPS system in 2019, which affected the GPS receivers with older hardware, not designed to cope with this issue. As a result, in July 2019, some of the stations started to report the date with wrong year (e.g., 2099) and incorrect day of year. However, the correct time of the day was preserved, therefore it was easy to obtain proper date by shifting the 220 time by a fixed amount of full days. Corrected date/time was then written into miniSEED headers. Nevertheless, the wrong date caused malfunction of the online data transmission system, which expected a correct date in the transmitted file names and in the headers. The transmission system software had to be temporarily modified in order to avoid the problem.
Permanent solution of the problem was later achieved by updating recorders' firmware with patched, WNRO-aware version.
Other problem was detected at the AG23 station, equipped with CMG-6TD datalogger: after few weeks, the internal clock 225 lost synchronization with GPS time, in spite of properly working and locked GPS receiver. This resulted in a linear increase of the time difference, which reached ~20 s after few months of recording. In this case, only an approximate time correction was possible. By comparing the timing of good-quality arrivals in seismograms from AG23 and neighboring, correctly timed stations, it was possible to measure the time differences over the recording period, and to apply appropriate corrections.
Here, the accuracy of time determination after the correction was estimated to ~1 s. This is a relatively large value, and it 230 prevents such data from being used for modelling methods which require exact knowledge of the absolute time, as e.g., seismic tomography. Nevertheless, such data can still be used in methods based on relative time of the seismogram components, as receiver function method or shear-wave splitting. More precise determination of timing corrections for this station is planned with the use of a method based on the noise correlation between recordings from incorrectly timed station and neighboring, correctly timed ones (Sens-Schönfelder, 2008). 235

Characteristics of observation sites and near-surface geology
The geology of the near-surface sequences varies considerably over the study area, ranging from Proterozoic crystalline rocks to unconsolidated Quaternary sequences. The geological structure of the basement at the observation site can heavily affect the character of the recorded seismograms, therefore we summarize the differences in the near-surface lithology and discuss their possible influence on the seismic data. The Table 1  on consolidated rocks of Palaeozoic or Proterozoic basement (except AG01 and OSTC, positioned on Cretaceous rocks). The 245 stations in the NE (the less-elevated region of Sudetic Foreland) are located on a layer of Cenozoic unconsolidated sediments, overlying the Palaeozoic basement. This area is marked in Fig. 3 with a green dotted line. The presence of the low-velocity Cenozoic deposits at these sites has a distinct influence on the seismic records, and more detailed discussion of these effects is presented in Sect. 3.1.  Figure 5 shows the data availability diagram for the stations of the network, produced using ObsPy package (Krischer et al., 2015). 255 Several shorter gaps, mostly resulting from data transmission problems and some longer gaps (caused by hardware failures or power shortages due to heavy thunderstorms) are present. The overall completeness of the network-transmitted data, supplemented with untransmitted data after recovery in the field, is 97%.

km after ISC). Red lines mark the theoretical onsets of P-and S-phases at the KSP station. All seismograms are low-pass filtered (< 1 Hz).
270 Figure 6 presents an example of seismograms for an earthquake near Jan Mayen Island. The seismograms show strong Pwave arrivals and lower-amplitude S arrivals, followed by high-amplitude surface (LR) waves, showing distinct dispersion. Figure 7 shows an example of a teleseismic earthquake from Alaska area. Here, besides high-amplitude P-and S-waves, also free-surface reflections PP, PPP, SS, and SSS can be clearly observed. Starting from ~2050 s relative time, a long train of 275 surface waves with substantial dispersion is visible. This figure clearly shows differences in frequency response of sensors for two groups of stations (it should be noted that records are scaled to maximum amplitude of each seismogram). For the AR-and permanent stations, equipped with 120 s sensors, the strongest amplitude is seen for the earliest, long-period (~50 s) pulses of surface wave at ~2050-2150 s time. However, for AG-stations, these long-period pulses are outside the 30 s corner frequency of the sensors and are strongly attenuated. With maximum trace amplitude scaling applied, this leads to substantial 280 enhancement of amplitudes of remaining parts of the seismogram: the body-wave pulses and later surface wave trains (with periods < ~30 s) for AG-stations, relative to AR-and permanent stations records.   Fig. 10. Here, a spectral seismogram obtained with the use of continuous wavelet transform (Daubechies, 1992) is presented for a teleseismic event (Southern Alaska, epicentral 300 distance 67°, backazimuth 353°) recorded by AR09 station. The Morlet wavelet was used. The onset of the P-wave is visible at ~600 s relative time, in records of Z-and N-component, with maximum amplitude in 2-4 s period range. At ~1200 s travel time, the S-waves with periods in 12-15 s range are visible, with the largest amplitude on E-component. The body waves are much weaker than surface waves, which are visible at larger travel times. On the E-component, corresponding approximately to transverse direction relative to ray backazimuth, the LQ waves with a period of 50-60 s can be seen at ~1600 s time. The 305 LR waves, best visible on N-and Z-component records at ~1900 s, clearly show the dispersion, with period decreasing from

Seismic noise characteristics and site effect
To estimate the level of the ambient noise at various frequencies, we calculated the probabilistic power spectral density (PPSD) distributions (McNamara and Buland, 2004) for the data recorded at each station with the use of ObsPy package 310 (Krischer et al., 2015). The PPSDs was calculated for continuous recordings from the period 01.12.2018-01.10.2019 (22 months).
The PPSD calculation was based on analysis of 1-hour-long windows of continuous seismic data (with 0.5 h overlap). The processing sequence consisted of demeaning, tapering, FFT computation and instrument response removal. The obtained frequency spectra for all windows were smoothed and summed to form a histogram representing the frequency distribution 315 of noise amplitudes at various period ranges. The result shows which amplitudes are observed for a given period. The PPSD medians were also calculated. Figure 11 shows a comparison of the PPSDs for three types of stations: AG10 (with 30s CMG-6T sensor), AR06 (RT 151-120s sensor) and permanent station UPC (STS-2 sensor). Diagrams for three components are presented. Figure 12 shows the PPSDs of Z-component for 12 selected temporary and permanent stations used in this study (PPSDs for all stations are pre-320 sented in supplement Figure S1). Figure 13 shows a comparison of PPSD median curves for all sites used, including permanent and temporary stations. There is a systematic difference in the noise level between permanent and temporary sites. The difference is notable for long-period range (> 10 s), and is particularly large for the horizontal components. High amplitude of the noise for the long periods of the horizontal components is often experienced in case of temporary stations, mainly due to an imperfect protection from environmental thermal/pressure changes or the sensor base tilt (Wilson et al., 2002). Another 325 factor contributing to higher long-period amplitudes on the horizontal component with respect to vertical amplitudes, in particular for stations located on young/low velocity sediments, could be the ellipticity of the Rayleigh waves. In presence of a low-velocity layer, the Rayleigh waves exhibit horizontally flattened particle motion, whereas at hard-rock sites on consolidated/crystalline basement, the particle motion is vertically elongated (Tanimoto et al., 2013). However, here, this factor seems to have a minor influence, considering relatively small (< 1 km) thickness of the low-velocity layer in this area, which 330 should not affect the ellipticity of long-period (> 10 s) waves in question.  sites with 30 s CMG-6T sensors. Similar behaviour of these sensors, independently of the actual noise at the site was reported by Tillmann (2006). This is most likely due to high self-noise of this device type, and, partially (for T noise > 30 s), to lower corner period of the instrument (30 s vs. 120 s for other units). It is worth noting that the CMG-6T high long-period noise is 340 at the very similar level as for the OBS version of the Güralp CMG-40T (30 s) sensor (Stähler et al,. 2018), while the land version of CMG-40T shows substantially lower (by about 20 dB) self-noise in this period range (Custodio et al., 2014;Tasič and Runovc, 2012). The short-period (SP) parts of the all PPSD medians (Fig. 13) show amplitude differences independent of the station type, and can be subdivided into two groups. Stations located on Palaeozoic, or older, consolidated basement (solid lines in Fig.   13) show much lower noise in this part of the spectrum than the stations on the basement covered by unconsolidated, alluvial Cenozoic sequences (dotted lines). This area represents NE part of the network, marked with green dotted line in Fig. 3. The stations with high amplitude of the short-period noise, marked with light blue color, mostly fit into this region, which sug-355 gests a high correlation of this effect with the basement type. When attempting to interpret these differences in terms of the near-surface geology, care must be taken, because the high-noise sites installed on the Quaternary cover are, in the same time, located in the area with higher population density, denser network of roads, expressways and railroads, with typically higher anthropogenic noise. To check if the anthropogenic effects are responsible for these differences in short-period noise level, two variants of the PPSD medians were calculated for the same time span: only for day hoursfrom 12:00h to 16:00h 360 local time, and only for night hoursfrom 00:00h to 04:00h local time. Comparison of results (Fig. 13c,d) shows that the SP noise level during day generally exceeds the night noise by 5-15 dB for all stations, irrespectively of their location. In the same time, differences in the short-period noise level between the sites located on old Palaeozoic rocks and the sites on the young Quaternary cover are of similar amplitude (~ 25 dB) for day-and night-time PPSDs, suggesting that they are indeed related to the basement type at the sites. 365 The presence of the low-velocity sediments in the area of Sudetic Foreland is also related to another effect, affecting the character of the P-phase onsets. The P-wave pulses on the horizontal components are followed by a prominent, high-375 amplitude coda/reverberations, extending over up to several hundreds of seconds (Fig. 14). The coda is characterized by a narrow frequency range, with a central frequency of 0.25 -0.40 Hz (periods of 2.5 -4 s), depending on the station location.
The corresponding P pulses on the vertical component are much shorter and seem to be only weakly affected (or not affected) by the coda. In contrast, for the stations located on the consolidated basement such reverberations are not observed on any component (Fig. 14a). 380 Such phenomenon is well known for a long time and described by several authors, e.g. by Zelt and Ellis (1999) or Yu et al. (2015), as it may heavily distort the results of 3-component interpretation methods. A layer of low-velocity sediments, with a strong impedance contrast relative to the consolidated or crystalline basement, produces multiple P-to-S conversions and reflections between the free surface and the base of the sediments. This results in high-amplitude reverberations in a narrow frequency range, mostly visible on the horizontal components. The frequency of the multiples is directly related to the seis-385 mic velocity and the thickness of the low-velocity layer. A systematic determination of the properties of the near-surface layer is out of scope of this paper. However, these observations can be compared with studies of the North Eastern part of the study area (LGCD), where the properties of the low-velocity layer were studied by Mendecki et al. (2016). They used the Horizontal to Vertical Spectral Ratio (HVSR) method to analyse the resonance frequencies and amplification factors based on the data collected by a broadband station in Tarnówek (Fig. 3), located ~15 km to the East of AR20 station. The HVSR 390 peaks at 3.6-4.2 s were found, and Vs of ~0.4 km/s was estimated for a ~380 m thick Cenozoic layer at this location. In our study, the Fig. 14b shows shorter (3.3 s) main period of the coda for AR20 station, which most likely correspond to thinning of the sedimentary layer, or, higher S-wave velocity.
The reverberations related to a low-velocity layer pose significant problems for the interpretation of the data, e.g., with the receiver function technique, as they overprint Ps conversion pulses on the radial component. One of the methods to 395 overcome this problem was presented by Yu et al. (2015). As the reverberations exhibit a resonant frequency related to the two-way traveltime of the wave in the sediment layer, the approach is based on designing a resonance removal filter in the frequency domain with filter parameters derived from the properties of the autocorrelation of the calculated RF. Our first tests showed that such filter, applied to the data from Sudetic Foreland, is quite effective and significantly reduces the effect of reverberations. 400

Verification of sensors misorientation
During the installation of stations in the field, to assure correct orientation, an azimuth measurement system with GNSS RTK unit and a MEMS gyroscope was used, as described in Sect. 2.3. According to our estimates, such system allows for determination of the N direction at the sensor location with ±2° accuracy, if appropriate care is taken by the operator during all steps of the procedure. In order to additionally check for possible misorientation of the sensors after deployment, using 405 the acquired data, a method based on the analysis of the P-wave polarization described by Fontaine et al. (2009) was applied.
These estimates were verified with the use of a method proposed by Braunmiller et al. (2020), based on the P-wave polarization, and with approach of Doran and Laske (2017) based on polarization of the Rayleigh waves. The two latter methods are implemented in the OrientPy package (Audet, 2020).
For a correctly oriented sensor and a homogeneous, isotropic medium, the polarization of the P-wave and of the Rayleigh 410 wave particle motion is expected to be confined to the ray plane, and its horizontal component to be polarized parallel to the event backazimuth. The misorientation of the seismometer (deviation of the N seismometer axis from the geographical North by A degrees -equivalent to rotation of the coordinate frame of the measurement system) will obviously result in an apparent deviation of polarization of the P-wave from the ray direction by an angle -A, independently of the event backazimuth.
However, in real medium, this deviation can be superimposed by the effects of the heterogeneity (dipping velocity 26 discontinuities) or anisotropy of the medium under the station (Crampin et al., 1982;Schulte-Pelkum et al., 2001;Fontaine et al., 2009). These effects show a specific azimuthal dependence of resulting deviation angles (periodic with 180° or 360° period), therefore it is often possible to separate these factors, if data from a wide range of backazimuths are available. The total directional variability of the polarization deviation can be decomposed as (Schulte-Pelkum et al., 2001): For the analysis, from 165 events in the epicentral distance range of 5°-100°, the recordings with high signal-to-noise ratio 425 on the vertical component of the P-phase (SNR > 5) were selected for each station. Selected data were filtered (various subbands of 2-16 s period band were used) and 3-D particle motion at the P-onset was analysed with the use of the orthogonal distance regression (ODR) method implemented in the ObsPy package, providing the azimuthal angle of the motion in the horizontal plane and incidence angle. Also, rectilinearity as defined by Fontaine et al. (2009) was calculated and was used to reject arrivals with poor rectilinearity of the particle motion, as contaminated by noise or other effects, and likely to produce 430 distorted results. The error of the azimuthal angle was determined based on calculated eigenvalues of the particle motion (Fontaine et al., 2009). In order to improve stability of final results, individual D pol values were sorted into backazimuthal bins of 30° width and averaged. Subsequently, these mean values were used for fitting the curve based on the equation (1) and for calculation of A-E parameters. The constant parameter A corresponds to the sensor misorientation.
To verify the results, we also analysed the same data set with a recently released software package OrientPy (Audet, 2020). 435 The package implements two methods of determination of sensor orientation. The method described by Braunmiller et al.
(2020) (BNG) determines the direction of P-wave polarization by minimizing the energy on the transverse component in a selected window around P-wave onset (Wang et al., 2016). Subsequently, polarizations for all events are averaged. The averaged value represents the constant component of the azimuth-dependent deviations, and is related to the misorientation angle for given station. It should be noted that the BNG method relies on relatively uniform backazimuthal coverage of the 440 analysed dataaveraging of a non-uniformly sampled sinusoidal curve is likely to result in a biased estimate of the mean value. Obtaining the mean value A by fitting the function (1)    For some permanent stations of the Czech Regional Seismic Network (CHVC, DPC, KRLC, OKC, OSTC and UPC ) the orientation angles obtained from direct, high accuracy gyrocompass measurements in field were available (Vecsey L., Institute of Geophysics of Czech Academy of Sciences, personal communication, 2020). They are presented as a reference in Fig. 15. For almost all these stations (except CHVC) our results are in a good agreement (in a ± 2-3° range) to the gyrocompass measurements. 465

470
It must be noted that the results of the indirect, polarization-based, methods are not as precise as direct orientation measurements, e.g., with the optical gyrocompass. According to Rueda and Mezcua (2015), the Rayleigh wave polarization method achieves 1-5° uncertainty in case for long time spans of observations, e.g., at permanent stations, while for shorter time intervals the uncertainty can exceed 10°. Therefore, as pointed out by Vecsey et al. (2017), in case of temporary arrays with limited period of data acquisition, the methods based on polarization analysis are able to detect only substantial (> 475 ~10°) misorientation of seismometers.
For most of the stations, the orientation values obtained from polarization analysis agree, within the error bounds, with the orientations measured directly at the sites with GPS/gyroscope system, as can be seen in the Figure 15 and in the Table 2 (the estimated error bounds for both methods are ~ ±3-7° (largely) and ±2°, respectively). Therefore, we assume that the orientation of these stations determined by GPS/gyroscope can be considered as correct (0° misorientation). However, for 480 five other stations, the polarization analysis results differ significantly from the orientations measured at the sites -AR07, OSTC and GKP (absolute orientation values of ~ 20°-37°), CHVC and OKC (~9°), suggesting that these sensors were incorrectly oriented during installation. The seismograms from these stations need to be rotated to a correct NE coordinate frame before use, and orientation codes in the headers of original (unrotated) data need to be set to Z, 1 and 2 instead of Z, N and E, according to the Standard for the Exchange of Earthquake Data (SEED) definition. 485

Conclusions and perspective
The AniMaLS project is an experimental seismic study of the physical properties and geological structure of the lithosphere and sub-lithospheric mantle beneath the Polish Sudetes (NE margin of the Variscan orogen), with a complex history of tectonic evolution. The acquisition of the seismic data involved deployment of 23 broadband stations for the period of about two years (Oct 2017 -Oct 2019). The selection of sites and installation was done using a low-cost approach, with the 490 stations deployed inside the unused basements, sheds or in rarely used public utility buildings. The stations were powered through the power grid, and the data were collected with the use of near real-time data transmission over the UMTS network.
During the measurement period, over 97% of data were retrieved. Location of the sites in the inhabited areas increased the safety, the ease of installation and the reliability of the data transmission, however, at the cost of the noise level, which was higher compared to the permanent stations in the region. Overall, the installed network provided a reliable acquisition of the will be used as data for various seismic interpretation methods in order to determine velocity distribution, anisotropy and location of discontinuities in the upper mantle.
Obtained geophysical results will be integrated with geological research, as, e.g., studies of anisotropy of the mantle xenoliths from the Sudetes. A multidisciplinary synthesis involving the results of the seismic interpretation can serve as a 500 basis for inferences about relative movements of the tectonic units forming the area, about the impact of orogenic and other deformational events on the present structure, and can help to reconstruct the history of geological evolution of the NE Variscan orogen and of the neighboring areas.
Data availability: The data from the AniMaLS experiment are stored at the IG PAS (https://dataportal.igf.edu.pl/dataset/ 505 animals), currently with restricted access (https://doi.org/10.25171/InstGeoph_PAS_IGData_AniMaLS_2021_002). The dataset will be open for the scientific community three years from the completion of the database, i.e., in 2023.

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