1 Geophysical Journal International - Supplementary material for 2 3 The GPS velocity field of the Aegean. New observations, contribution of the earthquakes, 4 crustal blocks model. 5 6 Briole, P., Ganas, A., Elias, P & Dimitrov, D. 7 8 SUMMARY 9 10 The analysis of the secular component of the velocity field of the Aegean presented, discussed and 11 modelled in the main text, requires the accurate determination of the transient part of the velocity 12 field. This transient part is dominated by the coseismic displacements produced by the major 13 earthquakes that occurred in the area during the analysed time window. Another significant 14 component is due to the postseismic relaxations associated with those earthquakes. In this 15 supplementary material we review the coseismic and postseismic displacements induced by the 16 crustal earthquakes of magnitude Mw ≥ 5.3 during the period 2000-2020. In addition, several GPS 17 stations have their time series disrupted by other sources of transients with different origins, that we 18 also present and discuss. Once the transient velocity field is estimated it can be removed from the 19 total velocity field to extract what can be considered as the secular velocity field. We discuss the 20 gradients of this secular velocity field as they are measured along three sections originated at the 21 Euler pole of rotation Anatolia-Eurasia. 22 23 24 S1. INTRODUCTION 25 1 26 During the period 2000-2020 several strong earthquakes occurred in the Aegean region, with a 27 concentration in western Greece around and near the Ionian Islands: Lefkada 2003, Movri 2008, 28 Cephalonia doublet 2014, Lefkada 2015, and Zakynthos 2018. The strongest events of the period 29 are the Methoni earthquake of February 14, 2008 and the Samothraki earthquake of May 24, 2014. 30 Those large events generated coseismic displacements observable in a large number of GPS 31 stations, up to distances larger than 200 km. The data from the Bulgarian and Turkish stations are 32 essential for the correct analysis of the Samothraki 2014 and Kos 2017 earthquakes. 33 Tab. 1 reports twenty-one earthquakes (plotted in Fig. 1 and Fig. S1) with minimum magnitude 34 5.3, having induced a movement observed at least at one of the analysed GPS stations. A previous 35 inventory of displacements induced by earthquakes can be found in Ganas et al. (2018a). In two 36 cases (Zakynthos 2006 and Gulpinar 2017) we are not considering a single earthquake but a swarm. 37 The formulas of Okada (1992) show that for a shallow earthquake of magnitude Mw ≥ 5.3, a station 38 located in a radius of 5 km from the epicentre can in most cases detect a deformation signal large 39 enough to be separated from the noise. The largest population of analysed events in 2019 is not only 40 due to the occurrence of several moderate earthquakes that year but also to the higher density of the 41 array in the recent years. The period we studied includes also the volcanic unrest of Santorini in 42 2011-2012 (Foumelis et al. 2013; Parks et al. 2015). The deformation produced by the analysed 43 earthquakes comprises also in most cases a postseismic relaxation which can represent a significant 44 percentage of the coseismic deformation. Fig. S2 shows the example of the coseismic and 45 postseismic signals of the north component of the LEMN station located near the epicentre of the 46 Samothraki 2014 earthquake. In the following we model the postseismic signals by assuming that 47 they obey the negative exponential law of a Maxwell material (see Thatcher & Rundle 1984). 48 Fig. S3 shows the locations of the sites mentioned in this supplementary material. Tab. S2 gives 49 details on the toponymy of the sites used in the main text and in this supplementary material. 50 2 51 52 S2. GPS DATA PROCESSING 53 54 First, the RINEX (Receiver Independent Exchange, v2.11) files were checked for antenna type, 55 receiver type, and a priori point coordinates. Tab. S1 indicates the observation period of each 56 station. Fig. S4 shows the histogram of duration of the time series, the average being 6.5 years. Fig. 57 S5 shows the percentage of daily data completeness of the time series, the average value being 85%. 58 All a priori coordinates are the result of a precise preliminary calculation that we carried out 59 beforehand. Their accuracy is within a few centimetres, which is better that the needs of the 60 processing software in terms of initial conditions. The reference height in the files and for 61 calculations is the Antenna Reference Point (ARP) height of the antenna. For stations with log- 62 sheets providing information on changes in equipment (receiver, antenna) that could have led to 63 jumps, we took this information into account from the beginning of the calculations. For some of 64 the other stations, we found jumps during the examination of the time series, and we corrected 65 them. We processed the data with Gipsy-Oasis software (https://gipsy-oasis.jpl.nasa.gov) version 66 6.4. We used the flinnR orbits, 15° minimum elevation and ambiguity resolution, but no parameter 67 of lateral variation of the troposphere and no a priori tropospheric model. These last settings are 68 intended to keep all tropospheric residuals together (stratified and laterally variable components) so 69 that they can be used directly to correct the InSAR interferograms produced on the area. By 70 comparing our results with those published by the Nevada Geodetic Laboratory (NGL, 71 http://geodesy.unr.edu) we found that the dispersion of our daily solutions is ~30% higher than that 72 of the NGL. This small increase has no impact on the average velocity of the stations, even with 73 only one year of time series. Fig. S6 shows that the difference between the velocities estimated by 74 the two calculations is below 0.05 mm yr-1. 75 3 76 77 S3. COSEISMIC AND POSTSEISMIC DEFORMATIONS 78 79 This section supports the eponymous section 3 of the main text, providing a detailed analysis of 80 each seismic event. The events of the Tab. 1 are analysed one by one. The parameters of the 81 modelled fault that are used to correct the velocity field are listed in Tab. 2. For a number of 82 earthquakes, we have used models already published by us. For the others we re-analysed the data 83 and produced a model, this is mentioned in Tab. 2. 84 Our modelled faults are simple, with the assumption of homogeneous slip on a single fault plane. 85 Some articles published for certain earthquakes present more refined slip models characterized by 86 heterogeneous slip and geometries that may not be planar. These models are of interest, particularly 87 when they are built in synergy with the constraints given by seismology, notably an accurate 88 aftershocks location. However, they also have their drawbacks. The first of them is that their 89 complexity makes it easy to obtain ad hoc solutions fitting well the GPS displacements thanks to 90 the insufficient density of the GPS stations. The other reason for us to use simple models is that we 91 do not need highly refined coseismic models to extract a precise velocity field and to extract and 92 model the postseismic signals. Indeed, with the exception of the rare cases of GPS stations located 93 very close to the sources, both simple and complex models produce theoretical displacements 94 almost equal in medium (~20 km) or far field (> 50 km). This is because, once the depth of the fault 95 and its angular parameters are defined, all well constrained by seismology, as well as the seismic 96 moment, the detail of the slip on the fault has minor, if not undetectable, impact on the theoretical 97 displacements expected at a medium and large distances. 98 The formalism we use to model coseismic and postseismic deformations is that of Okada (1992). 99 It assumes a homogeneous elastic half-space. The earthquake is represented by a dislocation 100 occurring homogeneously in a rectangle originally centred at the hypocentre of the earthquake, and 4 101 then tuned by inverting the geodetic data. We model the postseismic deformations with this same 102 formalism. We therefore assume that the postseismic slip has a nature comparable to coseismic one, 103 thus affecting a fault or a narrow fault zone, but in a continuous manner instead of stick slip. Under 104 these simple assumptions, we can produce models that fit the data at first order. Even if, in some 105 cases, these models may not reflect completely the exact physics of the processes, their capacity to 106 map with fidelity the postseismic movements is good and they therefore allow a good separation 107 between the transient effects of the earthquakes and the secular part of the deformation. 108 We used the inverse6 code (Briole et al. 1986; Briole 2017). The GPS observations used as input 109 to model the fault parameters are those already published for the earthquakes of Movri 2008, 110 Efpalion 2010, Kefalonia 2014, Lefkada 2015, Gulpinar 2017, Kos 2017, Zakynthos 2018, and 111 those calculated here for the earthquakes of Methoni 2018, Samothraki 2014, Lesvos 2017, and all 112 other small earthquakes. 113 We found several cases in which it was needed to combine two exponentials laws to fit the 114 postseismic relaxation, e.g. in the case of the Samothraki 2014 earthquake (Fig. S2), one short 115 relaxation time (65 days) and one long relaxation time (1295 days). The need to involve two time 116 constants arises also for the earthquakes of Methoni 2008, Lefkada 2015 and Zakynthos 2018.