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Group 1 – CSEP | Poster Abstracts
underway within the U.S. branch of CSEP. The experiment, designed to compare time-invariant 5year
earthquake rate forecasts, is now approximately halfway to its completion. We present, for the
first time, preliminary results of this unique experiment. While these results are preliminary--the
forecasts were meant for an application of five years--we find interesting results: most of the
models are consistent with the observation and one model is identified as forecasting the spatial
distribution of earthquakes best.
1-078
TIME-DEPENDENT FLUCTUATIONS OF THE EARTHQUAKE MAGNITUDE
DISTRIBUTION: STATISTICAL ESTIMATION AND PREDICTIVE POWER Olsen S,
and Zaliapin I
This study reports new results on statistical analysis of time-dependent earthquake magnitude
distribution and connection between fluctuations in the magnitude distribution and large regional
earthquakes. Specifically, we consider the following two problems: 1) How to effectively describe
and detect local deviations of the magnitude distribution from the long-term Gutenberg-Richter
(GR) approximation? 2) What is the connection between those deviations and the occurrence of
large regional earthquakes? We develop a statistical estimation framework for the b-value (slope of
the GR approximation to the observed magnitude distribution) and for the ratio a(t) between
intensities of earthquake occurrence in two non-overlapping magnitude intervals. The timedependent
dynamics of these relevant parameters of the magnitude distribution is analyzed using
sequential Bayesian estimation (filtering) based on homogeneous Markov chain models. The main
advantage of this approach over the traditional window-based estimation is its ”soft”
parameterization, which allows one to obtain reliable and stable results with realistically small
samples available for analysis. The developed methods are applied to the observed seismicity of
California, Nevada, and Japan on different temporal and spatial scales. We report an oscillatory
dynamics of the estimated GR parameters and find that the detected oscillations are positively
correlated with the occurrence of large regional earthquakes. The reported results have important
implications for further development of earthquake prediction and seismic hazard assessment
methods and contribute to the SCEC science program in the framework of the Collaboratory for the
Study of Earthquake Predictability.
1-079
A PROBABILISTIC COMPLETENESS STUDY IN JAPAN Schorlemmer D, Hirata N,
Euchner F, Ishigaki Y, and Tsuruoka H
The Japan Meteorological Agency (JMA) operates a seismic network and additionally gathers realtime
seismic data from many other seismic networks in Japan, among them the Hi-net of the
National Research Institute for Earth Science and Disaster Prevention (NIED) and many local and
regional networks operated by universities. In total, this aggregated network comprises more than
1000 stations distributed over the many islands of Japan. Locally this network is able to detect
earthquakes with magnitudes of less than M=0, however, estimates about recording completeness
were only given for seismically active regions. Here, we present the first application of the
probability-based magnitude of completeness (PMC) method to the JMA network. We show
detection probabilities for any given magnitude and completeness magnitudes for selected
probability levels for the entire area of Japan. The results show the strong performance of the JMA
network and that the network can provide the data of required quality for CSEP (Collaboratory for
the Study of Earthquake Predictability) testing.
2008 SCEC Annual Meeting | 111