## 2 Materials and Methods
### Shear-Wave Splitting (SWS) Analysis  
A preliminary set of 14,825 events from both the manual (Cat1) and the automatic (Cat2) catalogues were selected as candidate events for an upper-crust SWS analysis using local stations. The first selection criterion is the \"shear-wave window\" [38], which requires the S-wave seismic rays to arrive at an incidence angle smaller than 45\({}^{\circ}\), to avoid the influence of converted pS phases. The Signal-to-Noise Ratio (SNR) is measured for a signal window containing the S-wave first pulses. This is performed for a pre-defined range of frequency bands used for the application of a band-pass Butterworth filter, and the filter yielding the highest SNR is selected [39]. Waveform recordings with SNR \(<\) 1.5 are discarded. Seismic anisotropy at the upper crust is studied via SWS, which is quantified by two parameters: a) the polarization direction, \(\varphi\), of the fast shear-wave and b) the time-delay, \(t_{\mathrm{d}}\), between the arrivals of the two split shear-waves at a receiver. To process this large dataset, we employed the open-source software Pytheas [40], which offers a variety of popular SWS analysis methods and has successfully been applied in recent crustal anisotropy studies (e.g., [26; 41]). We adopt the Eigenvalue (EV) [42], rather than the Rotation-Correlation (RC) method [43], as the former is considered to be more reliable [44]. The EV method performs a grid-search at a pre-defined range of \(\varphi\), \(t_{\mathrm{d}}\) value pairs. For each grid point, the horizontal waveforms are rotated to all candidate \(S_{\mathrm{fast}}\) and \(S_{\mathrm{slow}}\) coordinates, according to the examined \(\varphi\), and then \(S_{\mathrm{slow}}\) is shifted by -\(t_{\mathrm{d}}\) for all time-delay values in the pre-defined range. The covariance matrix of the corrected waveforms is calculated in a window containing the S-wave pulse, and the major and minor eigenvalues \(\lambda_{1}\) and \(\lambda_{2}\) are determined. The solution that yields the minimum \(\lambda_{2}\) is considered as the optimal pair of \(\varphi\) and \(t_{\mathrm{d}}\). A 95% confidence interval in the range of \(\lambda_{2}\) values around the optimal grid point is considered to define the measurement uncertainties \(\delta\varphi\) and \(\delta t_{\mathrm{d}}\) (Figure 3). An important advantage of the Pytheas software is that it permits fully automatic SWS processing by defining the optimum S-wave signal window. This is performed with the application of a Cluster Analysis procedure [45]. A series of different window configurations are examined, within the bounds of the middle of S-P interval and the dominant period of the S-wave pulse multiplied by a user-defined factor [39; 40]. For each window, \(\varphi\) and \(t_{\mathrm{d}}\) are measured using the EV method and the solution pairs are sorted into clusters [45]. Then, the window yielding the (\(\varphi\), \(t_{\mathrm{d}}\)) solution pair with the smallest errors from the most constrained cluster is selected. The quality of the SWS parameter measurements is assessed by automatically calculating a score value, taking into account the ratio between \(\delta\varphi\) or \(\delta t_{\mathrm{d}}\) and a respective user-defined maximum threshold. A quality grade between A (best) and E (worst) is then attributed, depending on their resulting average score. The E grade is also reserved for cases of low SNR \(<\) 1.5. In the following, only measurements with grades A, B or C were taken into consideration. Furthermore, measurements are marked as \"null\" when their \(\varphi\) value is within \(\pm\)10\({}^{\circ}\) from \(p\) or \(p\) + 90\({}^{\circ}\), i.e., sub-parallel or perpendicular to the polarization direction, \(p\), of the corrected (for anisotropy) shear-wave. In those cases, it is not possible to distinguish whether the medium is isotropic or the initial polarization coincides with that of the \(S_{\mathrm{fast}}\) or the \(S_{\mathrm{slow}}\), which is why \"null\" measurements are discarded [46].