2018/12/07 by John B. Rundle, Alexis Giguere, Donald L. Turcotte +2 · 3 citations
Earth and Planetary Sciences · Computer Science · Mathematics · #Earthquake Detection and Analysis #earthquake and tectonic studies #Seismology and Earthquake Studies #Nowcasting #Seismology #Geology #Earthquake simulation #Scaling #Earthquake prediction #Proxy (statistics) #Earthquake magnitude #Entropy (arrow of time) #Statistics #Mathematics #Physics
paper · pdf · doi:10.1029/2018ea000464
openalex publication_date 2018/12/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Abstract Seismic nowcasting uses counts of small earthquakes as proxy data to estimate the current dynamical state of an earthquake fault system . The result is an earthquake potential score that characterizes the current state of progress of a defined geographic region through its nominal earthquake “cycle.” The count of small earthquakes since the last large earthquake is the natural time that has elapsed since the last large earthquake (Varotsos et al., 2006, https://doi.org/10.1103/PhysRevE.74.021123 ). In addition to natural time, earthquake sequences can also be analyzed using Shannon information entropy (“information”), an idea that was pioneered by Shannon (1948, https://doi.org/10.1002/j.1538‐7305.1948.tb01338.x ). As a first step to add seismic information entropy into the nowcasting method, we incorporate magnitude information into the natural time counts by using event self‐information. We find in this first application of seismic information entropy that the earthquake potential score values are similar to the values using only natural time. However, other characteristics of earthquake sequences, including the interevent time intervals, or the departure of higher magnitude events from the magnitude‐frequency scaling line, may contain additional information.