A comparison of the gravity field over Central Europe from superconducting gravimeters, GRACE and global hydrological models, using EOF analysis

Abstract

SUMMARY We analyse data from seven superconducting gravimeter (SG) stations in Europe from 2002 to 2007 from the Global Geodynamics Project (GGP) and compare seasonal variations with data from GRACE and several global hydrological models—GLDAS, WGHM and ERA‐Interim. Our technique is empirical orthogonal function (EOF) decomposition of the fields that allows for the inherent incompatibility of length scales between ground and satellite observations. GGP stations below the ground surface pose a problem because part of the attraction from soil moisture comes from above the gravimeter, and this gives rise to a complex (mixed) gravity response. The first principle component (PC) of the EOF decomposition is the main indicator for comparing the fields, although for some of the series it accounts for only about 50 per cent of the variance reduction. PCs for GRACE solutions RL04 from CSR and GFZ are filtered with a cosine taper (degrees 20–40) and a Gaussian window (350 km). Significant differences are evident between GRACE solutions from different groups and filters, though they all agree reasonably well with the global hydrological models for the predominantly seasonal signal. We estimate the first PC at 10‐d sampling to be accurate to 1 μGal for GGP data, 1.5 μGal for GRACE data and 1 μGal between the three global hydrological models. Within these limits the CNES/GRGS solution and ground GGP data agree at the 79 per cent level, and better when the GGP solution is restricted to the three above‐ground stations. The major limitation on the GGP side comes from the water mass distribution surrounding the underground instruments that leads to a complex gravity effect. To solve this we propose a method for correcting the SG residual gravity series for the effects of soil moisture above the station.

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“…A few studies tried to link these surface soil moisture patterns derived from EOF analysis with relevant features (topography, soil properties, and land use/land cover) with different conclusions depending on study locations, the main hydrological processes, the period considered (wet, dry, and intermediate) and also on the scales (both temporal and spatial) at which the method was applied [Kim and Barros, 2002;Yoo and Kim, 2004;Jawson and Niemann, 2006;Perry and Niemann, 2007]. In the field of gravimetry, EOFs have been applied over Europe to compare ground-based superconducting gravimeter data sets, GRACE solutions, and outputs from global hydrological models, mainly for validating GRACE solutions [Crossley et al, 2004;Neumeyer et al, 2008;Abe et al, 2012;Crossley et al, 2012].…”

Comment on: ‘The quest for a consistent signal in ground and GRACE gravity time-series’, by Michel Van Camp, Olivier de Viron, Laurent Metivier, Bruno Meurers and Olivier Francis

“…We should also point out that EOF analysis should not be confined (as in [MVC]) to only the first mode; more than two modes are needed to represent the variability of all the GGP stations as recognized in the previous EOF publications. Crossley et al (2012) found no large difference in the PC1 solutions whether using the three above-ground stations or the full set of stations, but the second and higher modes clearly reveal the contribution of opposite signals from the below-ground stations, a point missed by [MVC].…”

“…The difference lies in the way the loading is used. In previous papers, for example, Crossley et al (2012), the goal was to extract continental-scale coherence (EOF modes) from the total signal at all SG stations in order to compare with GRACE. But when [MVC] do the loading for site-by-site comparisons using pairwise correlations, it is crucial to choose the appropriate sign for the local contribution depending on the location of the local masses with respect to the gravimeter.…”

“…In support of their point of view, they refer to Von Storch & Zwiers (1999), which is a general textbook quoted without an explicit page reference, and hence of limited use. Crossley et al (2012) showed explicitly (in their Appendix) that an EOF analysis when applied only to the annual components of the SG series made perfect sense when interpreting the modes in terms of the phases and amplitudes of the individual series. EOF decomposition is able to satisfactorily combine individual series even where pairwise correlations may be weak or even partly reversed (due to some stations being underground).…”

“…those using empirical orthogonal function (EOF) analysis: Neumeyer et al (2008), Crossley et al (2012), Abe et al (2012) and Weise et al (2012). In these papers, comparisons are made using the EOF decomposition of GRACE satellite gravity fields (computed as if at the Earth's surface), surface gravity as measured by a sparse network of superconducting gravimeters (SGs) that are part of the global geodynamics project (GGP) and global hydrology models.…”