Applications of ambient seismic noise: clock error detection and group velocity estimation in land and ocean bottom seismograms

Ambient seismic noise generated by ocean waves is continuously present in seismograms and has previously been considered as undesired, disturbing signal. However, it has been shown that cross-correlations of noise recorded at two seismic stations converge towards the Green's function. This function describes the underground properties between the two stations. Ever since this finding, a wide range of noise applications has been described, which are still under development. Temporal changes of noise cross-correlations can be used for detection of clock errors in seismic data, while group velocities derived from cross-correlations are the basis for tomographic studies. In the first part of this thesis, an extensive clock error study of land stations and ocean bottom seismometers (OBSs) is presented. A new multiple-component approach is applied, which enhances the accuracy (~20 ms) of the detected clock errors significantly. Moreover, this approach allows the retrieval of clock errors with high temporal resolution of 1-2 days, even for large interstation distances (~300 km). The application of the described approach to data sets with low timing quality could highly increase their usability for structural studies. The second part of this thesis deals with group velocity curves that are mainly retrieved from OBS cross-correlations with interstation distances of up to ~2000 km. A joint inversion of the noise group velocities together with earthquake data from a prior study yields a high-resolution crustal S-wave velocity model of the western Indian Ocean. This model highly reflects tectonic structures in this region, like ocean ridges and plateaus. These results demonstrate the feasibility of large-scale OBS noise tomography of ocean basins, while prior studies were limited to smaller scales. In the last part of this thesis, first steps towards a seismological image of the island La Réunion are presented. Group velocity curves are derived from noise cross-correlations between island stations. In agreement with gravity studies, the group velocities indicate a spacious high-velocity body beneath the ancient volcano of the island. The inversion of the group velocities will yield a tomographic model of the island, which may be used as starting velocity model for future seismic surveys. The majority of the seismic stations used in this thesis were installed in the western Indian Ocean on and around La Réunion during the RHUM-RUM project. This reflects the high applicability of noise cross-correlations (from data quality inspection to crustal imaging) within the same data set. The detailed method descriptions of this work provide a valuable guideline for future studies, that deal with land or OBS seismograms

Clock errors in land and ocean bottom seismograms: High-accuracy estimates from multiple-component noise cross-correlations

Many applications in seismology rely on the accurate absolute timing of seismograms. However, both seismological land stations and ocean bottom seismometers (OBSs) can be affected by clock errors, which cause the absolute timing of seismograms to deviate from a highly accurate reference time signal, usually provided by GPS satellites. Timing problems can occur in land stations when synchronization with a GPS signal is temporarily or permanently lost. This can give rise to complicated, time-dependent clock drifts relative to GPS time, due to varying environmental conditions. Seismometers at the ocean bottom cannot receive GPS satellite signals, but operate in more stable ambient conditions than land stations. The standard protocol is to synchronize an OBS with a GPS signal immediately before deployment and after recovery. The measured timing deviation, called “skew”, is assumed to have accumulated linearly over the deployment interval, an assumption that is plausible but usually not verifiable. In recent years, cross-correlations of ambient microseismic noise have been put to use for correcting timing errors, but have been limited to interstation distances of at most a few tens of kilometres without reducing the temporal resolution. We apply noise cross-correlations to the evaluation of clock errors in four broadband land stations and 53 wideband and broadband OBSs, which were installed on and around the island of La Réunion in the western Indian Ocean during the RHUM-RUM (Réunion Hotspot and Upper Mantle - Réunions Unterer Mantel) experiment. We correlate all three seismic components, plus a hydrophone channel in OBS stations. Daily cross-correlation functions are derived for intermediate distances (∼20 km) for land-to-land station pairs; stable, 10-day stacks are obtained for very large interstation distances up to >300 km for land-to-OBS, and OBS-to-OBS configurations. Averaging over multiple station pairs, and up to 16 component pairs per station, improves the accuracy of the method by a factor of four compared to the single-channel approaches of prior studies. The timing accuracy of our method is estimated to be ∼20 ms standard deviation, or one sample at a sampling rate of 50 Hz. In land stations, non-linear clock drifts and clock jumps of up to six minutes are detected and successfully corrected. For 52 out of 53 OBSs, we successfully obtain drift functions over time, which validate the common assumption of linear clock drift. Skew values that were available for 29 of these OBSs are consistent with our independent estimates within their observational error bars. For 23 OBSs that lacked skew measurements, linear OBS clock drifts range between 0.2 ms/day and 8.8 ms/day. In addition to linear drift, three OBSs are affected by clock jumps of ∼1 s, probably indicating a missing sample problem that would otherwise have gone undetected. Thus we demonstrate the routine feasibility of high-accuracy clock corrections in land and ocean bottom seismometers over a wide range of interstation distances