Assessing the completeness magnitude M c of earthquake catalogs is an essential prerequisite for any seismicity analysis. We employ a simple model to compute M c in space based on the proximity to seismic stations in a network. We show that a relationship of the form M pred c d ad b c, with d the distance to the kth nearest seismic station, fits the observations well, k depending on the minimum number of stations being required to trigger an event declaration in a catalog. We then propose a new M c mapping approach, the Bayesian magnitude of completeness (BMC) method, based on a two-step procedure: (1) a spatial resolution optimization to minimize spatial heterogeneities and uncertainties in M c estimates and (2) a Bayesian approach that merges prior information about M c based on the proximity to seismic stations with locally observed values weighted by their respective uncertainties. Contrary to the current M c mapping procedures, the radius that defines which earthquakes to include in the local magnitude distribution is chosen according to an objective criterion, and there are no gaps in the spatial estimation of M c. The method solely requires the coordinates of seismic stations. Here, we investigate the Taiwan Central Weather Bureau (CWB) seismic network and earthquake catalog over the period 1994-2010.

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Abstract. The crustal seismicity of Taiwan was investigated by means of the Allan Factor analysis and Count-based Periodogram, which allow to identify scaling behaviour in point processes and to quantify their temporal fluctuations by means of the estimate of the scaling exponent. Our findings point out to the presence of two time-scaling regions in the crustal Taiwanese seismicity. The first region, involving the intermediate timescales can be probably linked with aftershock activity, while the second region, involving the large timescales could be related with the background seismicity.

Abstract. Using the Taiwan Central Weather Bureau earthquake catalogue, the crustal seismicity of Taiwan was analyzed by means of a nonextensive approach. The time span of the analyzed catalogue is from 1 January 1990 to 30 November 2007, and only earthquakes with magnitude M≥2.0 were considered. Our findings reveal that the nonextensive statistics furnishes a very good prediction of the cumulative magnitude distribution of crustal seismicity in Taiwan, even if the aftershocks are removed, indicating that the approach is robust for clustered as well as declustered seismicity.

Abstract. The effect of tidal triggering on earthquake occurrence has been controversial for many years. This study considered earthquakes that occurred near Taiwan between 1973 and 2008. Because earthquake data are nonlinear and non-stationary, we applied the empirical mode decomposition (EMD) method to analyze the temporal variations in the number of daily earthquakes to investigate the effect of tidal triggering. We compared the results obtained from the nondeclustered catalog with those from two kinds of declustered catalogs and discuss the aftershock effect on the EMD-based analysis. We also investigated stacking the data based on inphase phenomena of theoretical Earth tides with statistical significance tests. Our results show that the effects of tidal triggering, particularly the lunar tidal effect, can be extracted from the raw seismicity data using the approach proposed here. Our results suggest that the lunar tidal force is likely a factor in the triggering of earthquakes.