International audienceAmbient noise tomography is a rapidly emerging field of seismological research. This paper presents the current status of ambient noise data processing as it has developed over the past several years and is intended to explain and justify this development through salient examples. The ambient noise data processing procedure divides into four principal phases: (1) single station data preparation, (2) cross-correlation and temporal stacking, (3) measurement of dispersion curves (performed with frequency–time analysis for both group and phase speeds) and (4) quality control, including error analysis and selection of the acceptable measurements. The procedures that are described herein have been designed not only to deliver reliable measurements , but to be flexible, applicable to a wide variety of observational settings, as well as being fully automated. For an automated data processing procedure, data quality control measures are particularly important to identify and reject bad measurements and compute quality assurance statistics for the accepted measurements. The principal metric on which to base a judgment of quality is stability, the robustness of the measurement to perturbations in the conditions under which it is obtained. Temporal repeatability, in particular, is a significant indicator of reliability and is elevated to a high position in our assessment, as we equate seasonal repeata-bility with measurement uncertainty. Proxy curves relating observed signal-to-noise ratios to average measurement uncertainties show promise to provide useful expected measurement error estimates in the absence of the long time-series needed for temporal subsetting

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[1] We demonstrate that the coherent information about the Earth structure can be extracted from the ambient seismic noise. We compute cross-correlations of vertical component records of several days of seismic noise at different pairs of stations separated by distances from about one hundred to more than two thousand kilometers. Coherent broadband dispersive wavetrains clearly emerge with group velocities similar to those predicted from the global Rayleigh-wave tomographic maps that have been constrained using ballistic surface waves. Those results show that coherent Rayleigh waves can be extracted from the ambient seismic noise and that their dispersion characteristics can be measured in a broad range of periods. This provides a source for new types of surfacewave measurements that can be obtained for numerous paths that could not be sampled with the ballistic waves and, therefore, can significantly improve the resolution of seismic images.

Seismic velocity changes and nonvolcanic tremor activity in the Parkfield area in California reveal that large earthquakes induce long-term perturbations of crustal properties in the San Andreas fault zone. The 2003 San Simeon and 2004 Parkfield earthquakes both reduced seismic velocities that were measured from correlations of the ambient seismic noise and induced an increased nonvolcanic tremor activity along the San Andreas fault. After the Parkfield earthquake, velocity reduction and nonvolcanic tremor activity remained elevated for more than 3 years and decayed over time, similarly to afterslip derived from GPS (Global Positioning System) measurements. These observations suggest that the seismic velocity changes are related to co-seismic damage in the shallow layers and to deep co-seismic stress change and postseismic stress relaxation within the San Andreas fault zone.

Summary We describe a method to invert surface wave dispersion data for a model of shear velocities with uncertainties in the crust and uppermost mantle. The inversion is a multistep process, constrained by a priori information, that culminates in a Markov‐chain Monte‐Carlo sampling of model space to yield an ensemble of acceptable models at each spatial node. The model is radially anisotropic in the uppermost mantle to an average depth of about 200 km and is isotropic elsewhere. The method is applied on a 2°× 2° grid globally to a large data set of fundamental mode surface wave group and phase velocities (Rayleigh group velocity, 16–200 s; Love group velocity, 16–150 s; Rayleigh and Love phase velocity, 40–150 s). The middle of the ensemble (Median Model) defines the estimated model and the half‐width of the corridor of models provides the uncertainty estimate. Uncertainty estimates allow the identification of the robust features of the model which, typically, persist only to depths of ∼250 km. We refer to the features that appear in every member of the ensemble of acceptable models as ‘persistent’. Persistent features include sharper images of the variation of oceanic lithosphere and asthenosphere with age, continental roots, extensional tectonic features in the upper mantle, the shallow parts of subducted lithosphere, and improved resolution of radial anisotropy. In particular, we find no compelling evidence for ‘negative anisotropy’ anywhere in the world's lithosphere.

We present a method that uses a global seismic model of the crust and upper mantle to guide the extrapolation of existing heat-flow measurements to regions where such measurements are rare or absent. For any chosen spatial point on the globe, the procedure generates a histogram of heat-flow values determined from existing measurements obtained from regions that are structurally similar to the target point. The inferred histograms are based on a ''structural similarity functional'', which is introduced to quantify the structural analogy between different regions. We apply this procedure world-wide using the global heat-flow data base of Pollack et al. [Rev. Geophys. 31 (1993) The method results in an inferred probability distribution for the heat flux for each geographical region of interest. These distributions are strongly non-Gaussian, but are well approximated by the log-logistic distribution which is completely specified by two parameters. The inferred distributions agree well with observed distributions of heat flux taken in 300-km radius circles regionally in numerous locations. Particular attention is drawn to the inferred surface heat flux distributions across Antarctica, where direct measurements are rare but information about heat flow may be needed to help understand the dynamics of the Antarctic ice sheets and ice streams. Mean heat flow in West Antarctica is expected to be nearly three times higher than in East Antarctica and much more variable. This high heat flow may affect the dynamics of West Antarctic ice streams and the stability of the West Antarctic Ice Sheet. D

Volcanoes are among the most dynamic geological objects and their eruptions provide a dramatic manifestation of the Earth's internal activity. However, strong eruptions are only short 1

[1] We study the origin of the background seismic noise averaged over long time by cross correlating of the vertical component of motion, which were first normalized by 1-bit coding. We use 1 year of recording at several stations of networks located in North America, western Europe, and Tanzania. We measure normalized amplitudes of Rayleigh waves reconstructed from correlation for all available station to station paths within the networks for positive and negative correlation times to determine the seasonally averaged azimuthal distribution of normalized background energy flow (NBEF) through the networks. We perform the analysis for the two spectral bands corresponding to the primary (10-20 s) and secondary (5-10 s) microseism and also for the 20-40 s band. The direction of the NBEF for the strongest spectral peak between 5 and 10 s is found to be very stable in time with signal mostly coming from the coastline, confirming that the secondary microseism is generated by the nonlinear interaction of the ocean swell with the coast. At the same time, the NBEF in the band of the primary microseism (10-20 s) has a very clear seasonal variability very similar to the behavior of the long-period (20-40 s) noise. This suggests that contrary to the secondary microseism, the primary microseism is not produced by a direct effect of the swell incident on coastlines but rather by the same process that generates the longer-period noise. By simultaneously analyzing networks in California, eastern United States, Europe, and Tanzania we are able to identify main source regions of the 10-20 s noise. They are located in the northern Atlantic and in the northern Pacific during the winter and in the Indian Ocean and in southern Pacific during the summer. These distributions of sources share a great similarity with the map of average ocean wave height map obtained by TOPEX-Poseidon. This suggests that the seismic noise for periods larger than 10 s is clearly related to ocean wave activity in deep water. The mechanism of its generation is likely to be similar to the one proposed for larger periods, namely, infragravity ocean waves.Citation: Stehly, L., M. Campillo, and N. M. Shapiro (2006), A study of the seismic noise from its long-range correlation properties,