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Figure 1. SANA time series in ITRF2000. North component (circles, short dashed lined), East component (squares, long dashed line). Error bars show the 3-σ uncertainties. series is in error, but that its uncertainty is not correct. When using continuous measurements and daily time series, robust mathematical models of different kinds of noise (white noise, random-walk noise, flicker noise) can be tested and applied to the data (for a complete discussion see e.g. [Williams et al., 2004]). Unfortunately, for campaign like measurements it is an impossible task to infer the noise model from the data themselves and we have to use a-priori assumption on the noise nature. One way of estimating realistic uncertainties is to simply rescale them (i.e. multiply them with and “ad hoc” factor). This factor can be determined as the ratio between the long term noise (the difference between actual epoch positions and positions predicted using the linear fit) and the epoch formal uncertainty. A better way, more robust and better suited to GPS monuments behaviour, is to consider that a time dependent noise (i.e. random walk noise) is present in the determination of the stations position. In our processing, this is done by adding a moderate Markov noise (2 mm/sqrt(yr)) to the coordinates of stations when combining the daily solutions, following the procedures described in [Herring et al., 1990] and [Herring et al., 1999]. Applying this strategy does not affect the velocity determination by more than 1 to 2 mm/yr but leads to the estimation of more realistic velocity uncertainties (1-2 mm/yr instead of the formal a-priori value of 0.1 mm/yr). However, adding this noise to all stations would considerably alter the reference frame determination. Therefore we choose not to apply this noise model to the 22 global “reference” stations described earlier. Hence, these stations still exhibit submillimetre uncertainties. When used to determine a pole rotation for a given plate, we multiply these velocity uncertainties by a factor of 10, to make them comparable to the average uncertainty of regional stations (1.3 mm/yr). As an example, figure 1 depicts the time series (station position as a function of time) of our station in Sana’a, Yemen. This station was occupied 7 times between 1991 and 2001, and although the older VIGNY ET AL.: ARABIA PLATE MOTION 4 measurements suffer from higher uncertainties and are affected by a less accurate realization of the reference frame, the velocity of this station is determined with a very small uncertainty (0.7 mm/yr on both horizontal components). Inversion of velocity data to obtain an angular velocity vector and associated uncertainties was performed by minimization of the weighted, L1-norm sum of misfits. The choice of the L1 rather than L2 norm (or standard least squares) is justified by our wish to avoid too much emphasis on stations with large misfits (or “outliers”). Once an angular velocity is computed, we followed the procedure described by Fernandes et al. [2003] and checked that the obtained solution is stable with respect to the data set. First, we recompute the angular velocity vector with an unweighted scheme in order to check that the solution is not forced by the stations with the smaller uncertainties. Next, we checked that removing one or two of the stations does not change significantly the angular velocity vector. Results Velocities in the ITRF2000 and relative to different plates are given in Table 2. Figure 2 depicts large scale velocities in a Eurasian reference frame. Given the limited number (16) of Eurasian stations used in this study (most of which actually being in Europe) we choose not to estimate our own Eurasian reference frame but to use an external and well determined Eurasia [Calais et al., 2003]. Stations located in stable Eurasia exhibit very small residual velocities (< 1 mm/yr) in this reference frame, indicating that our solution is consistent with Calais et al. [2003]. However, stations in the most southern part of central Eurasia (ZECK, KIT3, POL2) show small but significant velocities relative to the rigid plate model. These velocities may be due to a slightly different rigid rotation pole, or may be representative of widespread deformation near these boundaries of the Eurasian plate [Nocquet et al., 2001; Wang et al., 2001; Banerjee and Bürgmann, 2002; Sella et al., 2002]. Motion of individual plates The Africa (Nubia), Somalia and Arabia plate motions are difficult to assess precisely given the small number of sites on these plates. Nevertheless, it is very clear that sites on the eastern side of the East African Rift and supposedly on the Somalia plate (MALI, SEY1, REUN) show a different block motion than sites on the western side of the East African Rift (MAS1, RABT, LAMP, NKLG, GOUG) and supposedly on stable Africa. Some sites located closer to the East African Rift have needed closer inspection to determine whether they belong to Africa or Somalia, but the result was generally unambigous: for instance, although HART and SUTH are located close to the plate boundary, their motion is
Plate Or country Eurasia Africa Somalia Arabia VIGNY ET AL.: ARABIA PLATE MOTION Table 2. station positions, velocities in ITRF2000 and relative to Eurasia, Africa, Somalia and Arabia plates, and uncertainties (1- ). Bold numbers highlight stations velocity residuals with respect to the plate they belong to. Station names in bold indicate stations used for the mapping in ITRF2000. ITRF2000 Eurasia Africa Somalia Arabia sigmas Corr. site Long. Lat. Ve Vn Ve Vn Ve Vn Ve Vn Ve Vn dVe dVn BRUS 4,36 50,80 18,0 13,8 -0,4 -1,7 4,5 -4,9 -3,2 -10,1 14,9 3,1 0,05 0,03 0,022 GRAZ 15,49 47,07 21,8 14,2 0,6 0,1 4,6 -4,4 -3,8 -8,3 13,6 -2,0 0,06 0,04 -0,030 MADR -4,25 40,43 18,9 15,6 0,1 -0,7 4,1 -2,7 -2,8 -8,8 7,7 9,4 0,63 0,61 -0,001 MATE 16,70 40,65 24,8 17,9 2,4 4,0 5,7 -0,7 -2,4 -4,4 11,0 1,2 0,05 0,03 0,005 METS 24,40 60,22 20,5 11,5 0,2 -1,0 4,6 -6,5 -4,3 -9,2 20,9 -8,6 0,05 0,04 -0,038 NOTO 14,99 36,88 21,5 18,1 -1,0 4,0 2,0 -0,5 -5,9 -4,4 5,0 2,2 0,91 0,90 0,000 ONSA 11,93 57,40 17,2 13,5 -1,2 -1,1 3,9 -5,2 -4,4 -9,5 18,5 -1,0 0,04 0,03 -0,045 SOFI 23,40 42,56 24,7 11,6 1,5 -1,1 4,6 -6,5 -3,9 -9,4 11,0 -8,1 0,86 0,85 0,000 WSRT 6,61 52,92 18,3 15,3 0,0 0,0 5,0 -3,5 -2,9 -8,4 16,7 3,4 0,06 0,04 -0,019 WTZR 12,88 49,14 20,9 14,4 0,5 -0,1 4,8 -4,3 -3,5 -8,5 14,9 -0,5 0,05 0,03 -0,003 ARTU 58,56 56,43 23,8 4,0 -1,5 -0,2 -0,8 -8,0 -9,9 -5,9 8,3 -26,0 0,38 0,27 -0,023 GLSV 30,50 50,36 20,9 12,2 -2,3 1,0 0,9 -5,1 -8,1 -7,0 11,6 -10,3 1,00 0,98 0,001 JOZE 21,03 52,10 22,0 12,9 0,6 -0,2 4,7 -5,4 -4,0 -8,5 16,7 -5,7 0,06 0,04 0,016 KIT3 66,89 39,14 30,9 3,2 3,8 1,4 3,2 -6,5 -5,1 -3,3 1,9 -27,7 0,07 0,04 -0,012 POL2 74,69 42,68 26,2 3,0 -0,9 3,4 -2,2 -4,5 -10,2 -0,3 -3,9 -28,2 0,08 0,04 -0,044 USUD 138,36 36,13 -4,2 -9,2 -25,7 6,0 -31,0 3,0 -34,2 11,1 -53,6 -22,8 0,71 0,67 -0,015 ZECK 41,57 43,79 25,9 10,5 0,5 1,8 2,3 -5,1 -6,6 -5,4 8,1 -15,7 0,87 0,85 0,000 ADD1 38,77 9,04 25,3 16,5 1,8 7,1 1,3 0,4 -4,4 -0,3 -12,1 -8,9 0,70 0,65 0,002 GOUG -9,88 -40,35 22,7 18,4 7,6 1,8 1,7 0,5 1,4 -6,0 -28,4 15,2 0,16 0,09 -0,219 HARK 27,71 -25,89 17,2 18,0 2,9 6,1 -0,5 0,3 -1,1 -1,9 -29,3 -3,5 0,09 0,05 0,077 LAMP 12,61 35,50 19,9 18,3 -2,4 3,8 0,5 -0,4 -7,2 -4,6 2,7 3,5 1,11 1,07 -0,002 MAS1 -15,63 27,76 16,6 17,2 -2,7 0,5 0,0 0,0 -6,0 -7,0 -4,9 17,1 0,06 0,03 0,045 NKLG 9,67 0,35 17,1 23,6 -4,5 8,7 -5,6 4,8 -10,2 0,3 -23,5 10,2 1,30 1,23 -0,004 MSKU 13,55 -1,63 34,6 28,8 13,3 14,4 12,0 10,1 7,7 6,0 -6,8 13,5 6,43 3,66 0,050 RABT -6,85 34,00 14,4 16,1 -5,1 -0,3 -1,8 -2,1 -8,4 -8,4 -2,2 11,3 1,35 1,28 -0,005 SUTH 20,81 -32,38 15,7 18,7 3,0 5,5 -1,3 0,4 -1,1 -2,8 -32,1 0,1 0,10 0,06 0,003 CBL0 43,07 11,46 29,4 16,1 5,5 7,8 5,0 0,7 -1,0 0,6 -7,3 -10,6 0,69 0,63 0,001 GOR0 42,22 11,31 31,1 16,1 7,1 7,6 6,7 0,6 0,7 0,4 -5,6 -10,3 0,88 0,67 0,002 LLL0 42,58 11,26 30,3 15,6 6,4 7,1 6,0 0,1 0,0 0,0 -6,4 -10,9 0,68 0,63 -0,002 MALI 40,19 -3,00 26,5 14,2 5,7 5,1 4,3 -1,7 0,3 -2,2 -15,1 -11,6 0,14 0,05 -0,018 REUN 55,57 -21,21 17,6 10,6 3,2 5,6 1,4 -2,1 0,1 -0,4 -24,0 -18,9 1,31 1,13 0,009 SEY1 55,48 -4,67 21,2 9,1 1,0 4,1 -0,4 -3,6 -4,2 -1,9 -20,3 -20,4 1,36 1,05 0,028 AMMN 35,88 32,03 20,8 17,5 -4,5 7,5 -3,1 0,9 -11,2 -0,2 -3,4 -6,9 1,34 1,30 0,000 BAHR 50,61 26,21 31,6 28,6 5,4 22,3 5,6 14,8 -2,1 15,8 0,6 0,1 0,07 0,03 0,023 DHAM 44,39 14,58 35,6 28,0 11,1 20,0 10,8 12,9 4,4 13,0 0,1 1,0 0,83 0,73 -0,016 HODD 42,97 14,79 35,3 26,8 10,8 18,5 10,6 11,5 4,2 11,4 0,1 0,2 1,03 0,76 -0,053 JNAR 43,44 13,32 37,2 26,7 12,9 18,5 12,6 11,5 6,3 11,4 1,2 0,0 1,29 0,83 -0,067 KHAS 56,23 26,21 30,3 29,1 3,9 24,2 3,7 16,6 -3,8 18,3 -2,0 -0,6 1,50 1,40 -0,001 KHOS 48,41 30,25 27,2 24,5 0,9 17,6 1,4 10,2 -6,6 10,9 -1,2 -3,5 1,60 1,45 -0,002 MUSC 58,57 23,56 33,9 29,9 7,7 25,7 7,3 18,0 0,0 20,1 -0,1 -0,1 1,44 1,40 -0,002 5
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Thèse en vue d'obtenir le diplôme
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Résumé Depuis une quinzaine d'ann
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écepteur GPS devient un sismograph
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au diamètre de l'enveloppe du nuag
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Figure 3. répétabilités (c'est
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Les domaines d’application a) con
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cours desquels la faille va moins v
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- Y a-t-il un régime permanent ? o
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temps en temps (pour refaire régul
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Conclusion Pour tous les objectifs
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Les vitesses calculées sur la pér
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A cause des progrès des mesures en
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Il est probable que l'on va bientô
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attendre longtemps pour que ce mouv
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Les réseaux GPS en Birmanie et les
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Chargement élastique sur la faille
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à l'échelle de toute la Birmanie
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vitesses observées et modélisées
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Le séisme de Sumatra (Banda Aceh)
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la composante Nord-Sud du mouvement
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Propagation de la rupture et des on
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La subduction Chilienne Contexte :
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La modélisation (dislocation en "b
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Mesures dans la lacune de Coquimbo
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Là encore, nous avons montré qu
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Erosion: GPS cinématique sur un pl
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Christophe VIGNY Né le 02 Mars 196
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d) j’ai été pendant 4 ans charg
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18. Instantaneous and finite kinema
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C] Publications dans des revues à
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Michel, G., Y. Yu, S. Zhu, C. Reigb
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X - 2 SIMONS ET AL.: GPS MEASUREMEN
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X - 10 SIMONS ET AL.: GPS MEASUREME
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X - 12 SIMONS ET AL.: GPS MEASUREME
Page 77 and 78: 1 JOURNAL OF GEOPHYSICAL RESEARCH,
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Page 101 and 102: Vol 436|14 July 2005|doi:10.1038/na
Page 103 and 104: NATURE|Vol 436|14 July 2005 ARTICLE
Page 105 and 106: NATURE|Vol 436|14 July 2005 ARTICLE
Page 107 and 108: JOURNAL OF GEOPHYSICAL RESEARCH, VO
Page 109 and 110: MICROBLOCK ROTATIONS IN SULAWESI, I
Page 127: Table 1. Data set used for this stu
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Page 133 and 134: Figure 4. African plate stations re
Page 135 and 136: exception of AMMN and, to a less ex
Page 137 and 138: is still too fast by 10%, Sella et
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