Analysis of gravity field variations derived from Superconducting Gravimeter recordings, the GRACE satellite and hydrological models at selected European sites
© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences. 2008
Received: 16 November 2006
Accepted: 30 September 2007
Published: 16 May 2008
If we restrict the spatial resolution to a half-wavelength of about 1500 km and the temporal resolution to 1 month, GRACE-derived temporal gravity variations can be resolved within the μgal (10-8 m/s2) range. A comparison with ground gravity measurements from selected Superconducting Gravimeter (SG) stations forming the Global Geodynamics Project (GGP) provides an independent validation. For this study, five European SGstations were selected that both cover a large test field and allow closely located SG-stations to be studied. Prior to this comparison, GRACE and SG data sets have to be reduced for the same known gravity effects due to Earth and ocean tides, pole tide, and atmosphere. After these reductions, the remaining part can be mainly attributed to mass changes in terrestrial water storage. For this reason, gravity variations derived from global hydrological models are included in the comparison of SG and GRACE results. Conversely, the hydrology models can be checked by gravity variations determined from GRACE and SG observations. For most of the SG locations investigated here, the comparison based primarily on computed correlations shows quite a good agreement among the gravity variation derived from the three different kinds of data sets: SG, GRACE, and hydrology models. The variations in SG gravity (point measurements) prove to be representative for a large area within the μgal accuracy range, if local gravity effects are removed correctly. Additionally, a methodology for an analysis of dominant common features based on the EOF-technique is proposed and illustrated. The first principal component shows strong periodicity, and the search for arbitrary periods confirms a strong common annual component, which reduces the total signal content considerably. The first eigenvector reveals common features and differences between distinct SG stations. Discrepancies between SG, GRACE, and hydrology models at individual SG stations, detected by both methods, may provide valuable hints for further investigations of respective data series.