The potential of the cross least squares wavelet analysis for estimating the time-frequency transfer function of atmospheric variations effect of superconducting gravity data

Atmospheric pressure variations introduce significant systematic effects on gravity observations that can reach up to 10 percent of tidal signal. In this study, a time-frequency dependent admittance is determined based on the least squares wavelet and cross least squares wavelet analyses. Five superconducting gravimeters distributed in northern and southern hemisphere are used in this investigation. First, the time-frequency representation (spectrogram) of both gravity and pressure is estimated. Subsequently, gravity and pressure cross-spectrogram is determined to estimate their coherency. Cross-spectrogram probability density function is used to stipulate the stochastic surface at the 95 percent confidence level to identify significant common spectral components, which are subsequently estimated (amplitude/phase as functions of time) to determine time-frequency pressure admittance. The new method is compared with the constant and frequency-dependent admittances determined from the standard 1-D frequency response analysis. The results show significant improvements in gravity residuals allowing better detectability of minute gravity signals.