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The Membach (B) and POL (UK) stations

P(f). k = -2  f -2  : random walk (Brownian). First-order Gauss-Markov. AG (f > 1 cpd). White noise. F cross-over. k = -1  f -1  : flicker. f. The Membach (B) and POL (UK) stations. Accuracy of absolute gravity measurements when measuring crustal deformation.

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The Membach (B) and POL (UK) stations

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  1. P(f) k = -2  f-2 : random walk (Brownian) First-order Gauss-Markov AG (f > 1 cpd) White noise F cross-over k = -1  f-1 : flicker f The Membach (B) and POL (UK) stations Accuracy of absolute gravity measurements when measuring crustal deformation Van Camp M.1, Williams S.D.P.2, Francis, O.3 and Camelbeeck T.1 1Royal Observatory of Belgium (ROB), Avenue Circulaire 3, BE-1180 Brussels mvc@oma.be 2Proudman Oceanographic Laboratory, Joseph Proudman Building,6 Brownlow Street, Liverpool L3 5DA sdwil@pol.ac.uk 3Université du Luxembourg and ECGS, rue Coudenhove Kalergi, 6, LU-1359 Luxembourg olivier@ecgs.lu Introduction To observe secular land movements of the order of a few millimetres per year, a very precise instrument with long-term stability is required. This can be achieved using absolute gravimeters [Williams et al., 2001]. Vertical land movements would modify the gravity at a rate of about -10 nms-2 (1 µGal) for 5 mm of uplift [Ekman and Mäkinen, 1996]. The deformation rates is given by the slope of a linear trend fitted to the repeated time series. Usually the regression estimator used is some form of least-squares adjustment and the measurement errors are assumed to be normal (Gaussian) and statistically uncorrelated from one another (white-noise). However, many geodetic data sets have now provided evidence for error sources that introduce large temporal correlations into the data [Agnew, 1992]. One common statistical model for many types of geophysical signal (which may contribute to the noise) maybe described as a power-law process [Mandelbrot, 1983](Figure1). The power-law process has been observed in geodetic time series such as continuously recording strainmeters [Agnew, 1992], GPS [Zhang et al., 1997, Mao et al., 1999, Williams et al., 2004] or sea level changes [Harrison, 2002]. Accounting for the type of noise is very important when estimating the related uncertainties and slope. A total of 96 absolute gravity (AG) measurements at the Membach station and 221 at the Proudman Oceanographic Laboratory (POL) are analyzed for noise content. The lengths of the series were around 10 years (POL) and 8 years (Membach). Unlike AGs SGs provide continuous data between episodic AG measurements. SG data however has the disadvantage of drifting with time, which is evaluated and removed by performing regular side-by-side AG measurements. Then, comparing drift-free SG with AG time series provides information on the noise affecting AG at low frequencies (except DC). With an improved understanding of the noise, we estimate the ability of AG to monitor vertical crustal deformations and provide more realistic uncertainties of the geophysical trend. Moreover, using the Membach experience, we evaluate the uncertainties that can be expected when carrying out repeated AG campaigns at other stations. This study can be very useful considering the repeated AG measurement campaigns undertaken since the 1990’s to measure crustal deformation (intraplate and interplate tectonic deformation, post-glacial rebound, anthropogenic subsidence or ice-mass and water-mass changes. Figure 1 : Power-law processes : spectra of the White, Flicker (pink), FOGM and Random-Walk (Brownian) noises • Membach: 96 AG measurements since 1996 • POL: 221 since 1993 • AGs are mobile but not suited for continuous measurements Membach: continuous SG measurements since 08/1995. SGs measure continuously but are not mobile The AG set-up noise Removing AG data from drift free-SG and the higher precision at high frequencies of the SG (Fig. 3) allows us to evaluate the noise due to the set-up of the FG5. The distribution of the difference [AG-SG] is normal and the FG5#202 agrees with the SG C021 at the 10-20 nms-2 level (Fig. 4). This noise can be due to poor alignment of the instrument, error in height measurement, slight perturbations due to transportation or different instrument-floor coupling. The AG set-up instrumental noise is white at frequencies lower than 1 cycle per day. Noise at low frequencies (< 1 cpd) and the effect on the linear trend estimate Figure 2 : Comparison between gravity measurements of the SG C-021 and the AG FG5-202 at the Membach station. Each AG gravity value represents the average of 2000 to 20 000 drops, equivalent to 1 to 8 days. The Earth tides, ocean loading and atmospheric effects, and polar motion have been removed. The SG C-021 instrumental drift of 43 nms-2/yr was evaluated by fitting a first order polynomial on the difference between the SG and the AG gravity data. The initial exponential decrease from August to December 1995 is due to the SG C-021 setup. What remains in these corrected SG residuals, from March 1996 to June 2004, is a geophysical trend, mainly linear (see Table 1 for values and uncertainties). After removing removing the SG instrumental drift, AG and SG data produces the same spectra, as shown in Figure 3. However, as only 96 AG values are available, and as they are not evenly spaced, we used the drift corrected continuous SG data to investigate the geophysical power-law process at low frequencies, which affects both instruments equally. The AG cross-over frequency appears to be around 1 cpd and increases towards 10 cpd when AG measurements are quiet. The SG cross-over frequency at 10-3 Hz is already visible with 24 h of data. MLE technique was used to fit power-law and FOGM noises. We estimated the noise amplitudes of a white noise process plus power-law model whilst simultaneously solving for the spectral index and we estimated the noise amplitudes of a white noise process plus FOGM noise model whilst simultaneously solving for the cross-over frequency. Taking into account different spectral indexes, using MLE, we calculated the slope and uncertainties using the AG POL and Membach AG & SG (Fig. 1) times series. Our preferred noise model is either the FB or the FOGM for several reasons. First, the Random Walk model (and the power law noise model where the spectral index was estimated to be -2.4) results indicate that it would take on the order of 100 years to observe a gravity rate of change of 10 nms-2/yr. Given the excellent results from AG already shown [Williams et al., 2001; Larson and Van Dam, 2000; Lambert et al., 2001; Francis et al., 2004] we believe these uncertainties are too pessimistic. This argument was also put forward to reject some noise models for geodetic data by Langbein [2004]. It is quite easy to believe that geophysical processes should be stationary (and therefore have a flat spectrum at low frequencies) as there are probably some physical bounds to the range of these processes. Secondly, tests were performed by applying the MLE on simulated time series and looking at what frequency range the derived spectra agreed for the various models. It turns out that the derived spectra mostly agreed at frequencies close to the high-end (perhaps an order or two magnitudes below the Nyquist frequency). So if the noise spectra did lower at low frequencies or the chosen spectral index was lower than predicted the MLE would tend to overestimate both the spectral index and the amplitude of that noise leading to widely pessimistic results. As a conclusion the preferred models give an uncertainty of between 1 and 1.5 nms-2/yr and a slope of -6.0 nm/s². The spectral index probably reflects a mixture of geophysical origins such as hydrology, atmospheric effects and to a lesser extent, station instability. At the Membach station, this new statistical analysis confirms that there is a significant gravity rate of change of about 6.0 nms-2/yr if a FB or FOGM noise is considered. Table1 : Uncertainties on the slope estimated using the 96 (rep. 211) AG values at the Membach (resp. POL) station for different power-law processes. Uncertainties calculated using the MLE method (Williams, 2003)

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