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We describe a new harmonic tidal analysis method, which constrains the solution to be near a reference model. This regularization stabilizes the linear regression, allowing us to infer model parameters for each tidal harmonic. This overcomes the need to create a priori groupings of harmonics. The inversion is done iteratively by adjusting the reference model to reduce the data misfit. The frequency dependence of the solution is thus data-driven. We find models for the different spherical degrees independently. Our procedure allows narrow-band variations of the tidal admittance. We test the hypothesis that some of the temporal variations of tidal parameters found in previous studies were caused by inappropriate body tide models in combination with a priori wave grouping. We determine a local response model from 11.5 years of data recorded by the superconducting gravimeter SG056 at Black Forest Observatory (BFO, Schiltach). Using this as an a priori model in a non-regularized moving window analysis of wave groups composed from summed harmonics, we find that periodic variations of groups M1, K1, μ 2, N2, L2, and S2 are reduced by up to a factor of 7 compared to earlier studies. Some variations previously seen in the M2 group are captured as well. [ABSTRACT FROM AUTHOR]

We present a case study on the detection and quantification of seismic signals induced by operating wind turbines (WTs). We spatially locate the sources of such signals in data which were recorded at 11 seismic stations in 2011 and 2012 during the TIMO project (Deep Structure of the Central Upper Rhine Graben). During this time period, four wind farms with altogether 12 WTs were in operation near the town of Landau, Southwest Germany. We locate WTs as sources of continuous seismic signals by application of seismic interferometry and migration of the energy found in cross-correlograms. A clear increase of emitted seismic energy with rotor speed confirms that the observed signal is induced by WTs. We can clearly distinguish wind farms consisting of different types of WTs (different hub height and rotor diameter) corresponding to different stable frequency bands (1.3-1.6 Hz, 1.75-1.95 Hz and 2.0-2.2 Hz) which do not depend on wind speed. The peak frequency apparently is controlled by the elastic eigenmodes of the structure rather than the passing of blades at the tower. From this we conclude that vibrations are coupled into the ground at the foundation and propagate as Rayleigh waves (and not as infrasound). The migration velocity of 320 m/s corresponds to their group velocity. The applied migration method can contribute to the assessment of local sources of seismic noise. This topic gets growing attention in the seismological community. In particular, the recent boost of newly installed wind farms is a threat to seismological observatories such as the Black Forest Observatory (BFO) and the Gräfenberg array (GRF) or gravitational wave observatories (e.g. LIGO, VIRGO) in terms of a sensitivity degradation of such observatories. [ABSTRACT FROM AUTHOR]

Surface wave methods gained in the past decades a primary role in many seismic projects. Specifically, they are often used to retrieve a 1D shear wave velocity model or to estimate the VS,30 at a site. The complexity of the interpretation process and the variety of possible approaches to surface wave analysis make it very hard to set a fixed standard to assure quality and reliability of the results. The present guidelines provide practical information on the acquisition and analysis of surface wave data by giving some basic principles and specific suggestions related to the most common situations. They are primarily targeted to non-expert users approaching surface wave testing, but can be useful to specialists in the field as a general reference. The guidelines are based on the experience gained within the InterPACIFIC project and on the expertise of the participants in acquisition and analysis of surface wave data. [ABSTRACT FROM AUTHOR]

This paper reports on different sources of errors that occur in the calibration process of a superconducting gravimeter (SG), determined by comparison with a ballistic absolute gravimeter (AG); some of them have never been discussed in the literature. We then provide methods to mitigate the impact of those errors, to achieve a robust calibration estimate at the [InlineEquation not available: see fulltext.] level. We demonstrate that a standard deviation at the level of [InlineEquation not available: see fulltext.] can be reached within 48 h by measuring at spring tides and by increasing the AG sampling rate. This is much shorter than what is classically reported in previous empirical studies. Measuring more than 5 days around a tidal extreme does not improve the precision in the calibration factor significantly, as the variation in the error as a function of $$1/\sqrt{N} $$ does not apply, considering the decrease in signal amplitude due to the tidal modulation. However, we investigate the precision improvement up to 120 days, which can be useful if an AG is run continuously: at mid-latitude it would require 21 days to ensure a calibration factor at the [InlineEquation not available: see fulltext.] level with a 99.7 % confidence interval. We also show that restricting the AG measurement periods to tidal extrema can reduce instrument demand, while this does not affect the precision on the calibration factor significantly. Then, we quantify the effect of high microseismic noise causing aliasing in the AG time series. We eventually discuss the attenuation bias that might be induced by noisy time series of the SG. When experiments are performed at the [InlineEquation not available: see fulltext.] level, 7 are needed to ensure that the error in the calibration estimate will be at the 1 per mille level with a 99 % confidence. [ABSTRACT FROM AUTHOR]

Two types of dispersive seismic waves have been acquired in different geological settings to investigate the potential to reveal the elastic parameters of the shallow marine subsurface. Scholte waves as well as acoustic guided waves are excited by a near-surface towed airgun, and recorded using two acquisition methods: (1) the towed-acquisition system using a hydrophone streamer towed close to the sea floor, and (2) the stationary-receiver method using Ocean-Bottom Seismometers and/or Hydrophones (OBS/OBH). Our diverse data sets reveal that the spatial sampling of the wavefield required to avoid aliasing may vary significantly for different geological settings. Scholte waves are characterised by a few distinct modes observed at low frequencies and low phase velocities. Their dispersion is mainly controlled by the depth profile of the shear-wave velocity. Acoustic guided waves show profound amplitude variations of numerous higher modes over a broad frequency range. These are sensitive to shear-wave velocity, but more sensitive to compressional-wave velocity than Scholte waves are. To avoid the identification of distinct modes we infer 1-D models of elastic parameters of the subsurface from the inversion of the full wavefield spectra of acoustic guided waves. In the Siberian Laptev Sea we infer the presence of a soft sediment layer (8–10 m) with a well resolved strong S-velocity gradient (150–450 m/s). In the Baltic Sea a low P-velocity layer with a strong vertical gradient (1250–1440 m/s) corresponding to a post-glacial gassy mud layer could be resolved, which agrees well with the sediment stratigraphy derived from a gravity core. [ABSTRACT FROM AUTHOR]