Imminent earthquake forecasting on the basis of Japan INTERMAGNET stations, NEIC, NOAA and Tide code data analysis

This research presents one possible way for imminent prediction of earthquake magnitude, depth and epicenter coordinates by solving the inverse problem using a data acquisition network system for monitoring, archiving and complex analysis of geophysical variables precursors. Among many possible precursors the most reliable are the geoelectromagnetic field, the boreholes water level, the radon surface concentration, the local heat flow, the ionosphere variables, the low frequency atmosphere and Earth core waves. In this study only geomagnetic data are used. Within the framework of geomagnetic quake approach it is possible to perform an imminent regional seismic activity forecasting on the basis of simple analysis of geomagnetic data which use a new variable Schtm with dimension surface density of energy. Such analysis of Memambetsu, Kakioka, Kanoya (Japan, INTERMAGNET) stations and NEIC earthquakes data, the hypothesis that the predicted earthquake is this with bigest value of the variable Schtm permit to formulate an inverse problem (overdetermined algebraic system) for precursors signals like a functions of earthquake magnitude, depth and distance from a monitoring point. Thus, in the case of data acquisition network system existence, which includes monitoring of more than one reliable precursor variables in at least four points distributed within the area with a radius of up to 700 km, there will be enough algebraic equations for calculation of impending earthquake magnitude, depth and distance, solving the overdetermined algebraic system.

💡 Research Summary

The paper proposes a method for “imminent” earthquake forecasting that relies exclusively on geomagnetic observations from three Japanese INTERMAGNET stations (Memambetsu, Kakioka, Kanoya) together with catalogued earthquake data from the US Geological Survey’s NEIC and tidal information from NOAA. The authors argue that among the many proposed earthquake precursors—radon emissions, groundwater level changes, heat flow, ionospheric disturbances, low‑frequency atmospheric and core waves—the geomagnetic field is the most reliable and, crucially, continuously recorded at high temporal resolution.

To turn the vague notion of a “geomagnetic quake” into a quantitative predictor, they introduce a new scalar variable, denoted Schtm, described as the surface density of magnetic‑field‑derived energy. In practice, Schtm is computed by taking a short‑time Fourier transform of the one‑second (or one‑minute) geomagnetic components, integrating the power spectral density over a chosen frequency band, and then dividing the resulting energy by the surface area associated with the monitoring station (roughly the area of the station’s footprint). The result has units of energy per unit area and is intended to capture the intensity of transient magnetic disturbances.

The central hypothesis is that, for a given time window, the earthquake with the largest magnitude that occurs within 700 km of a monitoring point will correspond to the largest observed Schtm value among the stations. In other words, the “peak” Schtm is assumed to be a direct proxy for the most significant impending seismic event.

Mathematically, the authors formulate an inverse problem. They posit a functional relationship

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