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Abstract  We demonstrate the possibility to improve the signal-to-noise ratio of superconducting gravity time-series by correcting for local hydrological effects. Short-term atmospheric events associated with heavy rain induce step-like gravity signals that deteriorate the frequency spectrum estimates. Based on 4D modeling constrained by high temporal resolution rain gauge data, rainfall admittances for the Vienna and Membach superconducting gravity stations are calculated. This allows routine correction for Newtonian rain water effects, which reduces the standard deviation of residuals after tidal parameter adjustment by 10%. It also improves the correction of steps of instrumental origin when they coincide with step-like water mass signals. [ABSTRACT FROM AUTHOR]

Abstract  The instrumental drift of the superconducting gravimeter in Membach, Belgium, is estimated using 9 years of co-located and episodic absolute gravity measurements. We show that the best model of the long-term drift of the SG-C021 is an exponential. The thermal levelers used to compensate tilts are unlikely to induce the observed drift. Rather, the capacitance bridge, magnetic variations, gas adsorption on the levitating sphere, or helium gas pressure variations around it are most likely the possible combined causes of the observed instrumental drift. In practice, either linear or exponential drift models are equivalent as long as the record duration does not exceed 10 years. For longer records, this study demonstrates that an exponential models the drift better than a simple linear trend. [ABSTRACT FROM AUTHOR]