Anomalous surface waves from Lop Nor nuclear explosions: Observations and numerical modeling

Surface waves from the Chinese test site of Lop Nor are analyzed using long-period and broadband stations located at regional and teleseismic distances and at different azimuths. For most azimuths, strong Love waves between 0.02 and 0.045 Hz are observed with an amplitude of up to 10 times that of the Rayleigh waves. In addition, an anomalous early Rayleigh wave train is observed at some stations in western Europe. Due to a particularly favorable station and source configuration, it is possible to isolate the areas where the anomalies are created. The high-amplitude Love waves must be attributed to either source effects or path effects immediately north of Lop Nor. The early wave train is shown to be due to a partial energy conversion between Love and Rayleigh waves, probably at the Tornquist Zone. To estimate the possible contribution from surface wave conversions to the observed anomalies, numerical simulations are carried out with the indirect boundary element method. The simulations show that a relatively small variation of crustal thickness can induce Rayleigh to Love wave conversions between 0.02 and 0.1 Hz frequency. The calculated amplitudes of the Love waves are significant (up to 35% of the amplitude of the incoming Rayleigh waves), but they are too small to fit the observed amplitude anomaly. The observed converted waves and the numerical results nevertheless indicate that surface wave conversions can be significant across strong lateral crustal heterogeneities. In particular, the conversions due to changes in crustal thickness are located in the period interval which is routinely used for estimation of Ms

Influence of the seismic noise characteristics on noise correlations in the Baltic shield

International audienceIt has recently been shown that correlations of seismic noise can contain significant information about the Green's function along the station profile. Using an array of 38 temporary broad-band stations located in Finland between 1998 September and 1999 March, we study the resulting 703 noise correlations to understand how they are influenced by the directivity of the noise field. The latter information is obtained through f-k analysis of data from two permanent seismic arrays in Germany and Norway and from a subset of stations of the array in Finland. Both types of analysis confirm that the characteristics of the seismic noise is strongly frequency-dependent. At low frequencies (0.02–0.04 Hz), we observe diffuse noise and/or randomly distributed sources. In contrast, the noise is strongly direction-dependent and not fully diffuse in the intermediate period ranges (0.04–0.25 Hz) which correspond to the first and second microseismic peak, created at the Irish and Scottish coast and the western coast of Norway. In this frequency interval the noise is sufficiently close to a plane wave to introduce systematic errors in group velocities for station pairs which are not parallel to the direction of the dominant incident noise. Phase velocities calculated by slant stack over many traces are however correct, independently of profile direction. In the high-frequency band (0.25–1.0 Hz), the situation is a mix between the low-frequency and the intermediate frequency cases. Average phase velocities and individual group velocities from well-oriented profiles are in excellent agreement with results from Rayleigh wave studies of the area

Emergence of body waves from cross-correlation of short period seismic noise.

International audienceAmbient noise correlation is now widely used in seismology to obtain the surface waves part of Green's function. More difficult is the extraction of body waves from noise correlations. Using 42 temporary broad-band three components stations located on the northern part of the fennoscandian region, we identify high-frequency (0.5-2 Hz) body waves emerging from noise correlations for inter-station distances up to 550 km. The comparison of the noise correlations with earthquake data confirms that the observed waves can be interpreted as P and S waves reflected from the Moho. Because the crustal model of the area is well known, we also compared the noise correlations with synthetic seismograms, and found an excellent agreement between the travel times of all the observed phases. Polarization analysis provides a further argument to confirm the observation of body waves

Short-Term Memory in the Production Phase of Sight Translation

This article reports on an empirical study on short-term memory in sight translation. The aim of the study was to test the hypothesis that sight translation requires the use of short-term memory during target-text production, as suggested by previous research. The hypothesis was tested on the basis of an experiment involving sight translation from Spanish into Danish and subsequent interviews with the translators. The data – the Spanish source text, seven sight translations into Danish, and the post-interviews – were analysed using both quantitative and qualitative methods, and the results of the study confirmed the hypothesis. In fact, the (quantitative) analyses of the sight-translated texts indicated that the subjects needed their short-term memory extensively during target-text production. However, the (qualitative) analyses of the interviews showed that the subjects had little awareness of this need

Dispersion Estimation From Linear Array Data in the Time-Frequency Plane

International audienceWe consider the problem of estimating the dispersion of a wave field from data recorded by a linear array of geophones. The fact that the data we are looking at may contain several propagating waves make this even more challenging. In this paper, a new algorithm is proposed to solve this issue. Currently, there are two methods for estimating wave dispersion described in the literature. The first method estimates the group delay function from the time-frequency representation (TFR) of each sensor separately. It is efficient as long as the patterns of the different waves do not overlap in the time-frequency plane. The second method estimates the dispersion from the two-dimensional (2-D) Fourier transform of the profile (or more generally from a velocity-frequency representation). This assumes that the dispersion is constant along the entire sensor array. It is efficient as long as the patterns of the waves do not overlap in the frequency domain. Our method can be thought of as a hybrid of the above two methods as it is based on the construction of a TFR where the energy of waves that propagate at a selected velocity are amplified. The primary advantage of our algorithm is the use of the velocity variable to separate the patterns of the propagating waves in the time-frequency plane. When applied to both synthetic and real data, this new algorithm gives much improved results when compared with other standard methods