Hector Gonzalez-Huizar

Unraveling the apparent magnitude threshold of remote earthquake triggering using full wavefield surface wave simulation

[1] Empirical studies with earthquake catalogs suggest that large events (M > 5) are rarely triggered in significant numbers by passing surface waves at remote distances from main shocks. Triggered, small (M 7) main shocks. Since large earthquakes involve larger rupture areas, we study the spatial and temporal characteristics of dynamic stress change for clues. Using a 3D finite element method, we model the complete wavefield from the 2002 M = 7.9 Denali earthquake recorded near the Wasatch Front in Utah, where details about triggered seismicity are known. In particular, we load our model with a displacement seismogram to acquire a time series of the stress change tensor and model failure of a representative normal fault based on these stress changes. We note that the stress-change regime varies rapidly between favoring strike-slip, thrust, and normal faulting, with durations lasting � 1–4 s. We find that these stress regimes usually affect only some fraction of a fault surface at any given time. Stress amplitudes also vary, meaning that ideal conditions for triggering are short-lived and spatially limited. Stress conditions can also rapidly reverse to regimes that inhibit slip. Given these stressing conditions, we conclude that it may be difficult for a larger rupture area to experience the temporally and spatially coherent stress change necessary to develop into a large magnitude earthquake.

Volatility models applied to geophysics and high frequency financial market data

This work is devoted to the study of modeling geophysical and financial time series. A class of volatility models with time-varying parameters is presented to forecast the volatility of time series in a stationary environment. The modeling of stationary time series with consistent properties facilitates prediction with much certainty. Using the GARCH and stochastic volatility model, we forecast one-step-ahead suggested volatility with +/- 2 standard prediction errors, which is enacted via Maximum Likelihood Estimation. We compare the stochastic volatility model relying on the filtering technique as used in the conditional volatility with the GARCH model. We conclude that the stochastic volatility is a better forecasting tool than GARCH (1, 1), since it is less conditioned by autoregressive past information.

Chile2015: Lévy Flight and Long-Range Correlation Analysis of Earthquake Magnitudes in Chile

The stochastic Truncated Lévy Flight model and detrended fluctuation analysis (DFA) are used to investigate the temporal distribution of earthquake magnitudes in Chile. We show that Lévy Flight is appropriated for modeling the time series of the magnitudes of the earthquakes. Furthermore, DFA shows that these events present memory effects, suggesting that the magnitude of impeding earthquakes depends on the magnitude of previous earthquakes. Based on this dependency, we use a non-linear regression to estimate the magnitude of the 2015, M8.3 Illapel earthquake based on the magnitudes of the previous events.