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Swarms of earthquakes with no apparent cause have puzzled scientists for years. This may be what causes them.

Swarms of earthquakes with no apparent cause have puzzled scientists for years. This may be what causes them.

 


Since late 2020, the Noto Peninsula in northern Japan has experienced a constant reoccurrence of earthquake swarms, a series of puzzling seismic events that, so far, do not appear to have any clear trigger.

Now, a newly published study by an international team of researchers has revealed that mysterious earthquake swarms may be linked to weather events. The discovered correlations between weather systems and an earthquake swarm that occurred in northern Japan appear to highlight the link between changes in underground pressure that can trigger earthquakes and monsoon rainfall.

The new findings were reported by researchers from the Massachusetts Institute of Technology, Université Grenoble Alpes, University of Vienna, Tohoku University, and the University of Tokyo.

Mysterious earthquake swarms

Earthquake swarms are seismic events that occur sequentially within a local area. Earthquakes are usually short in duration, and seismologists have realized that they differ from major earthquakes in that no single event in an earthquake sequence can be identified as the primary shock. For this reason, earthquake swarms differ from large primary earthquakes, which are often followed by a series of smaller aftershocks.

In the team's new research study, lead author Qing-Yu Wang and colleagues reviewed seismic data collected from the Japan Meteorological Agency spanning more than a decade, and calculated seismic velocities across the Noto Peninsula. During their research, clear patterns began to emerge that coincided with changes in seasonal rainfall.

Using a hydromechanical model that allowed them to simulate pore fluid pressure changes associated with heavy snow or rain, the team was able to integrate meteorological data from the region and compare it to seismic velocity patterns.

Confirmation of seismic models

Based on their findings, seismic velocity appears to change according to predictions based on the team's models, which showed some of the strongest correlations with periods of heavy snowfall. Based on these observations, Wang and his team believe that heavy snowfall has a noticeable effect on underground pressure conditions, which has been shown to be related to both the intensity and timing of earthquake swarms in the region.

The team's findings help underscore the need for additional research into the role of climate conditions as secondary triggers of seismic events. This is of particular importance when considered in relation to climate change and how warming trends in many parts of the world are helping to facilitate extreme rainfall events, which could provide a viable explanation for the sudden increase in earthquake swarms in locations such as northern Japan within the past few years.

The team's findings clearly show a relationship between climate models and earthquake activity, says William Frank, an assistant professor in MIT's Department of Earth, Atmospheric and Planetary Sciences (EAPS) and co-author of the study.


“We see that snowfall and other environmental loading at the surface affects the stress state underground, and the timing of heavy rainfall events is closely linked to the onset of this earthquake swarm,” Frank said in a statement.

“So, climate clearly has an impact on the response of solid Earth, and part of that response is earthquakes.”

The study's authors point out that well-documented tectonic forces remain the main driver of seismic events. However, incorporating new findings linking earthquake swarms with heavy rainfall could help researchers broaden their knowledge overall in the coming years and perhaps help predict when earthquakes are likely to occur based on careful observation of weather data.

Micah Hanks is editor-in-chief and co-founder of The Debrief. He can be reached via email at [email protected]. Follow his work at micahhanks.com and on X:MicahHanks.

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