We present evidence for
precursors to the ScS and sScS (SDS and sSDS) phases observed at
epicentral distances smaller than 30 deg. These precursors are
intermittently observed in broadband recordings from the six
Incorporated Research Institutions for Seismology stations used
(western Pacific region and South America). They appear approximately
35-50 s ahead of the ScS arrival on the transverse component and are
independent of hypocentral depth. The observed precursors are
characterized by relatively large amplitudes in the frequency band
from 0.05 to 0.2 Hz. A more detailed analysis is restricted to a
subsidiary data set from station SNZO (New Zealand). The coherency,
frequency dependence, slowness, polarity, and polarization of the
precursors are discussed. Many explanations for SDS can be rejected,
and we conclude that a reflector 180 km above the core-mantle
boundary causes these occasionally strong precursors. The large
SDS/ScS amplitudes at low frequencies require an unrealistically
large impedance contrast for a one-dimensional model. We test the
possibility of focusing the SDS phase by a discontinuity with
topography and show that structure with scale lengths of ~19 deg - 25
deg (1200--1600 km, i.e., larger than the Fresnel zone) can account
for large intermittently observed SDS amplitudes with their
geometrical reflection points within the same Fresnel zone. This is
surprising, since it is often assumed that scale lengths smaller than
the Fresnel zone must be responsible for variations within a Fresnel
zone. The limited data set permits no conclusions about the global
properties of this phase or its implied reflector.
We present a new tool for efficient incoherent noise reduction for array data employing complex trace analysis. An amplitude unbiased coherency measure is designed based on the instantaneous phase which is used to weight the samples of an ordinary, linear stack. The result is called the phase weighted stack (PWS) and is cleaned from incoherent noise. PWS thus permits detection of weak but coherent arrivals. The method presented can easily be extended to phase weighted cross-correlations or be applied in the tau - p domain. We illustrate and discuss the advantages and disadvantages of PWS in comparison to other coherency measures and present examples. We further show that our non-linear stacking technique enables us to detect a weak lower mantle P-to-s conversion from a depth of approximately 840 km on array data. Hints of a 840 km discontinuity have been reported, however such a discontinuity is not yet established due to lack of further evidence.
We present a new coherence functional to evaluate quantitatively the goodness of waveform fit between two time series as function of lag time. The proposed coherence measure is called phase cross-correlation (PCC) since it is based on the similarity of instantaneous phases. No amplitudes are explicitly involved and PCC is therefore an amplitude unbiased measure which equally weights every sample in the correlation window. As consequence PCC enables to discriminate between closely similar waveforms and is suited to detect weak arrivals which are concealed in larger amplitude signals. Besides, for signal recognition PCC can be applied for arrival time picking, as misfit function or it can be used in combination with stacking techniques. The performance of PCC is illustrated and discussed in comparison with the conventional cross-correlation normalized with the geometric mean energy. Both measures are based on different concepts and the differences in their performance can be significant. The choice of the proper coherence measure depends on the data and application. We show in a data example the ability of PCC to detect weak P-to-s conversions in the P-wave coda of teleseismic events. With this example we give confirming evidence for a crust which is thicker than the global average and the existence of the 410-km and 660-km discontinuities underneath SE-Brazil. In addition, we observe hints of a 510-km discontinuity.
The Lomb-Scargle periodogram was introduced in astrophysics to detect sinusoidal signals in noisy unevenly sampled time series. It proved to be a powerful tool in time series analysis and has recently been adapted in biomedical sciences. Its use is motivated by handling non-uniform data which is a common characteristic due to the restricted and irregular observations of, for instance, free-living animals. However, the observational data often contain fractions of non-Gaussian noise or may consist of periodic signals with non-sinusoidal shapes. These properties can make more difficult the interpretation of Lomb-Scargle periodograms and can lead to misleading estimates. In this letter we illustrate these difficulties for noise-free bimodal rhythms and sinusoidal signals with outliers. The examples are aimed to emphasize limitations and to complement the recent discussion on Lomb-Scargle periodograms.
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