Solid Earth Sciences (S)
Session Sub-categorySS
Session IDS-SS03
Title New trends in data acquisition, analysis and interpretation of seismicity
Short Title Seismicity
Date & Time
AM1, AM2 Tue, 23 MAY
PM3 Tue, 23 MAY
AM2 Wednesday, 24 MAY
Main ConvenerName Bogdan Enescu
Affiliation Department of Geophysics, Kyoto University
Co-Convener 1Name Francesco Grigoli
Affiliation University of Pisa
Co-Convener 2Name Yosuke Aoki
Affiliation Earthquake Research Institute, University of Tokyo
Session Language E
Scope In the last two decades, the number of high-quality seismic instruments installed worldwide has grown exponentially and likely will continue to grow in the coming decades, producing larger and larger datasets. This dramatic increase in the volume of available seismic data is partially due to the rising popularity of new technologies for seismic data acquisition based on fiber optics, characterized by an extremely high spatial and temporal sampling. Such systems are making seismological datasets grow in size and variety at an exceptionally fast rate, pushing the limit of current data analysis techniques. This data explosion, combined with new data analysis paradigms, is opening new research horizons in seismology and related fields. Exploiting the massive amount of data is a challenge that can be overcome by adopting new approaches for seismic data analysis that can lead to enhanced seismic catalogs that can be used in conjunction with advanced statistical or physics-based methods to forecast seismicity or to correlate the seismic activity with other geophysical processes, including stress changes and migration of fluids in the crust or aseismic processes. This session aims to bring to light new methods for the analysis (either offline or in real-time) and quantitative interpretation of seismicity datasets collected across different scales and environments or with new seismic data acquisition technologies, such as fiber-optics-based sensors. Relevant topics to be presented include but are not limited to methods for seismicity characterization, statistical analysis of seismicity patterns in the space-time-magnitude domain, modeling and forecasting of seismicity, and case studies. We thus encourage contributions that demonstrate how the proposed methods or the analysis of large datasets help to improve our understanding of earthquake and/or volcanic processes.
Presentation Format Oral and Poster
Collaboration Joint with -