XY373 EGU2010-12075
Loading phenomena impact on velocity field computation in the Pyrenees from GPS campaigns a- L2G/ESGT /CNAM, Le Mans, France b- CNES/GRGS, Toulouse, France c- DTP UMR5562, Observatoire Midi – Pyrénées, Toulouse, France d- Faculté des Sciences, de la Technologie et de la Communication, University of Luxembourg, Luxembourg e- Department of Geodesy and Mine Surveying, University of Miskolc, Miskolc, Hungary
Nicolas J. a, F. Perosanz b, A. Rigo c, T. van Dam d, and M. Ferenc a,e
Contact:
[email protected]
1. Introduction
3. Results
The region of the Pyrenees Mountains, which represents the boundary between France and Spain, is subject to continuous and moderate seismic activity. The horizontal surface deformation rate is expected to be at a maximum of ~1 mm/yr. In order to quantify the present-day tectonic deformation in this region, different GPS ResPyr campaigns were performed in 1995, 1997, and 2008. Figure 1 indicates the different sites monitored during the 2008 ResPyr campaign. Considering the expected rate of deformation in this area (maximum of ~1.3 cm over the 13 years between the first and the last campaigns), we would like to consider what would be the impact of variable surface mass loads on the predicted velocity field computed from sparse GPS campaigns. Indeed, atmospheric, oceanic, and hydrological loading phenomena due to mass redistribution can induce crustal deformations up to several centimeters of amplitude with different characteristic time periods (annual, semi-annual, diurnal, sub-diurnal…). Thus, spatial and temporal variability of these loads may potentially change the velocity field determination and thus its geodynamical interpretation. Velocities determined from the study region, which has high topographic relief and is located between the Atlantic Ocean and the Mediterranean Sea, may be particularly sensitive to such loading effects.
The mean modeled amplitude of the various loading effects over all the different ResPyr stations velocities are shown in Table 2. Figures 2 and 3 show the spatial distribution of these impacts for the different loads. We remind the reader that these numbers represent a correction that should be applied to the GPS velocity field before any interpretation. In the most cases, the vertical effects are all higher than the horizontal ones, as we expected from the model time series. Even if the impact is essentially on the vertical component, it is not negligible on the horizontal component. For the horizontal components, the ATML effect dominates. This effect can reach 0.2 mm/yr but can also has no impact, depending on the considered site. Nevertheless, it is lower than 0.5 mm/yr in all cases. It has a moderate distribution without general pattern. In the eastern part of the network this effect induces southeast impact whereas in the western part of the network it induces a northeast impact. It also seems to be higher in the middle of the mountain range, even if similar magnitudes can be observed near the western coastline. The CWSL effect is oriented to the northeast for all the stations, but is larger for the eastern stations, even if there is no clear west-east gradient. It can reach about 0.1 mm/yr. Finally, the NTOL impact is the smaller. It dominates on the east side of the network, and has essentially a southeast orientation. Nevertheless, it is always lower than 0.1 mm/yr. Finally, we can say that the velocities of the stations of the Mediterranean side of the network are more influenced by these loads. Table 2: Mean impact of the various loading effects over the different ResPyr campaigns on velocity. Figure 1: 2008 ResPyr campaign sites
2. Loading effects
2D
The impact of variable loading impact atmospheric, non tidal ocean, and continental water storage loading effects on the velocity determination was computed. In this study, we did not considered the ocean tide loading effect since this well known effect is implemented in most geodetic software packages. For each ResPyr site, we computed the mean value of each load for each GPS campaign epoch from the following models: the atmospheric loading (ATML): NCEP reanalysis, 6h, 2.5x2.5deg; the Non-Tidal Ocean Loading (NTOL): ECCO, 12h, 1x1deg; and the hydrological loading (CWSL): GLDAS monthly interpolated to weekly, 1x1deg. Figure 2 illustrates the time variability of the different loading signals for the ESNO station located in the western part of the network for the different components. Table 1 summarizes the statistics of the amplitude of the different loading effects over all the ResPyr stations coordinates.
Up
Mean
Std
Min
Max
ATML
0.12
0.06
0
0.23
NTOL
0.01
0.01
0
0.05
CWSL
0.09
0.03
0.05
0.12
Accumulated effect
0.13
0.06
0.03
0.28
ATML
0.06
0.21
-0.31
0.42
NTOL
-0.13
0.02
-0.18
-0.10
CWSL
0.23
0.18
-0.02
0.47
Accumulated effect
0.12
0.40
-0.52
0.74
For the vertical component, the CWSL effect is always upward. It largely dominates for the western part of the network and can reach 0.5 mm/yr. It seems to illustrate the Atlantic Ocean influence. The ATML effect is moderate over the entire area, but can reach 0.4 mm/yr. The effect is upward for the west part of the network whereas it is downward for the east part of the network. It is very small for all the stations closed to the Mediterranean Sea. The NTOL is always downward and this effect seems to have nearly the same impact whatever the considered site, with larger amplitudes for the eastern part of the network. It can reach 0.2 mm/yr. To conclude for the Mediterranean side ATML and NTOL effects have the same direction and CWSL has no influence, whereas for the Atlantic side ATML and CWSL are in the same direction and NTOL is in the opposite direction.
a) ATML Table 1: Amplitude of the various loading effects over the different ResPyr stations and campaigns Loading effect
b) NTOL
E (mm)
N (mm)
Up (mm)
Atmosphere
Mean Std Min Max
0.03 1.19 - 5.18 3.59
0.04 1.29 - 4.89 4.73
0.17 3.17 - 11.88 13.96
Non Tidal Ocean
Mean Std Min Max
0.04 0.22 - 1.46 0.63
- 0.08 0.21 - 1.36 1.07
- 0.52 0.91 - 7.53 0.89
Hydrology
Mean Std Min Max
- 0.64 0.83 - 2.03 1.81
0.16 0.86 - 2.94 2.64
- 2.20 4.18 -10.44 8.13
c) CWSL
North
East
Up
Figure 2: Time series at ESNO station for the different loading effects: a) ATML, b) NTOL, c) CWSL, for North, East, and Up component, respectively
From these loading time series, we computed the differential loading effect between each sparse campaign in terms of velocity using different approaches. The different loads impact velocity estimates in a standard deviation sense by 0.01, 0.002, and < 0.001 mm/yr for the planimetry and of 0.02, 0.004, and 0.005 mm/yr for the vertical component, for ATML, NTOL, and CWSL, respectively. The final results presented here are obtained using the mean value of each model during each observation campaign since we estimate that it is the best suited for GPS. Indeed, GPS data processing provides mean coordinates over the entire observation duration for each campaign from which velocity field is computed.
Figure 3: Horizontal loading effect impact on velocity (in mm/yr)
Figure 4: Vertical loading effect impacton velocity (in mm/yr)
4. Conclusion and prospects This study demonstrates the importance to take loading effects into account for geodynamical interpretations of sparse GPS campaign measurements, especially in very low tectonic deformation regions as Pyrenees. We demonstrated that the various loading phenomena may have a non negligible impact on the velocity field resulting from the different campaigns and therefore on the characterization of the Pyrenees deformation. Indeed, the non tidal ocean, atmospheric and hydrological accumulated loading effect on horizontal velocity estimates can reach 0.3 mm/yr, which is to be compared to the level of the searched signal of maximum 1 mm/yr. Furthermore, these loading effects are not yet taken into account in routine GPS data processing. We recommend to applying a posteriori corrections to the coordinates series. Our results also demonstrate that it is essential, but not sufficient, to perform the surveys at the same seasonal time frame (summer in this case). Then, it may be necessary to subtract an estimate of the loading effects from the velocity field obtained from GPS data analysis. This will ensure better accuracy on the determination of the velocity field derived from different GPS campaigns, which are typically used for geodynamical studies.
