2019年5月27日(月) 17:15 〜 18:30 ポスター会場 (幕張メッセ国際展示場 8ホール)

コンビーナ:庄 建倉(統計数理研究所)、Schorlemmer Danijel(GFZ German Research Centre for Geosciences)、Matt Gerstenberger(GNS Science)、鶴岡 弘(東京大学地震研究所)

Probabilistic models have been developed for describing, analyzing, and forecasting seismicity
since more than 100 years and, with the advent of large-scale digital networks, in high
resolution during the last 30 years. These models include recurrence and stress-release models
for long-term earthquake hazard assessment, and short-term models describing earthquake
clustering, e.g. the ETAS model. Some models have become standard tools in seismic hazard
assessment. However, the overall probabilities remain on the low end and the uncertainties of
the forecasts are not well described. Rigorous data-based development and testing of models
will help further improving forecasting power and accuracy of these models. Similarly, new
hypotheses shall be evaluated rigorously using some existing model as the null hypothesis
model or in dedicated tests addressing the hypothesis directly. In this context, the Collaboratory
for the Study of Earthquake Predictability and its Japan branch provides the necessary testing
capabilities for rigorous and unbiased evaluation of models and hypotheses. This session
focuses on research that increases information on seismicity, being with respect to a reference
model or as an independent hypothesis. We solicit contributions of model developments and
hypothesis formulation based on the increased understanding of the physical process of
earthquakes, such as the preparation and rupture processes of the earthquake source and the
interaction between earthquakes and tectonic environments. We also welcome development
and implementation of improved statistical methods for testing and validating physical
hypotheses based on observed data. In particular, we welcome contributions about model- or
hypothesis-test experiments that could be implemented in the Japan testing center.