統計数理研究所

第21回統計地震学セミナー

日時(Time): 2011年10月18日（火）/ 18 October 2011 (Tuesday)　15:00～

※Danijel Schorlemmer氏が体調不良とのことで、講演がキャンセルとなりました。John Rundle氏の講演はスケジュール通り16時から行う予定です。

場所(Location): 統計数理研究所 D312A室
/ Room D312A @ Institute of Statistical Mathematics

講演題目(Title): Advancements in Probabilistic Seismic Network Completeness Studies

講演者 (Speaker): Dr. Danijel Schorlemmer
(German Research Center for Geosciences, Telegraphenberg, 14473 Potsdam, Germany,
and Southern California Earthquake Center, University of Southern California, 3651 Trousdale Parkway, MC-0740, Los Angeles, CA 90089-0740, USA)

時間 (Time): 15:00～16:00

概要(Abstract)

An important characteristic of any seismic network is its detection completeness, which should be considered a function of space and time. Many researchers rely on robust estimates of detection completeness, especially when investigating statistical parameters of earthquake occurrence.

We present the Probability-based Magnitude of Completeness (PMC) method for computing the spatial variation and temporal evolution of detection capability of seismic networks based on empirical data only : phase data, station information, and the network specific attenuation relation. New developments are extending this method to complex 3D structures like mining environments.

We present studies of regional networks from California, Switzerland, Italy, Japan, New Zealand, and compare the result with estimated completeness levels of other methods. We report on the time evolution of monitoring completeness in these regions. Scenario computations show the impact of different possible network failures and offer estimates of possible network optimization strategies. Optimizations are reducing the necessary processor time for computing. All presented results are published on the CompletenessWeb (www.completenessweb.org) from which the user can download completeness data from all investigated regions, software codes for reproducing the results, and publication-ready and customizable figures.

講演題目(Title): Forecasting Large Earthquakes: Problems, Pitfalls and Promise

講演者 (Speaker): John B. Rundle
(Distinguished Professor, Departments of Physics and Geology, University of California, Davis, CA, USA　 https://www.geology.ucdavis.edu/faculty/rundle.html)

時間 (Time): 16:00～

概要(Abstract)

Forecasting the future behavior of a stochastic complex system is a necessary and critical activity with wide applications. As the mathematician Edward Thorp showed many years ago [1,2], forecasting has applications in games of chance as well as in financial markets. Both fields represent applications of statistics, stochastic random walks, and probability theory. Objective evaluation of forecasts by established tests and measures is also a necessary and important component of a forecasting system. Many of the modern tests have been tabulated at [3]. Earthquake forecasts are a special case of the forecasting problem, particularly as applied to large earthquakes such as the March 11, M9 Off the Pacific Coast of Tohoku earthquake.

Forecasts of future events in complex systems are in general plagued by incomplete information, a problem that must be considered in constructing forecasts. In addition to these problems, delivery of real-time forecast information to the scientific community and to the public is an issue as well. Here, web 2.0 technology is helpful in allowing rapid dissemination of information. In this lecture, I shall discuss these general aspects of the forecasting problem as applied to earthquake forecasting. I will discuss ideas based on the Natural Time Weibull method of earthquake forecasting, recently developed by our group. I will also discuss our experiences with numerical earthquake simulations, as well as with public outreach using the World Wide Web (see www.openhazards.com).

[1] E. Thorp and S. Kassouf, Beat the Market: A Scientific Stock Market System, Random House (1967)
[2] E. Thorp, Beat the Dealer: A Winning Strategy for the Game of Twenty-One, Random House (1962)
[3] http://www.cawcr.gov.au/projects/verification/

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