Weather conditions can cause some earthquakes

Weather conditions can cause some earthquakes
Weather conditions can cause some earthquakes

MIT scientists have discovered that certain weather phenomena can also play a role in triggering some earthquakes.

In a study appearing in Science Advances, researchers report that episodes of heavy snowfall and rain likely contributed to a series of earthquakes in recent years in northern Japan. The study is the first to show that weather conditions could trigger some earthquakes.

“We see that snowfall and other environmental loads on the surface impact the subsurface stress state, and the timing of intense precipitation is well correlated with the onset of this earthquake swarm,” study author William Frank says in a statement. assistant professor in the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at MIT (Massachusetts Institute of Technology). “So climate obviously has an impact on the response of the solid earth, and part of that response is earthquakes.”

The new study focuses on a series of ongoing earthquakes on Japan’s Noto Peninsula. The team found that seismic activity in the region is surprisingly synchronized with certain changes in underground pressure, and that those changes are influenced by seasonal patterns of snowfall and precipitation. Scientists suspect that this new connection between earthquakes and climate may not be unique to Japan and could play a role in shaking other parts of the world.

Looking ahead, they predict that climate’s influence on earthquakes could become more pronounced with global warming.

“If we go into a changing climate, with more extreme precipitation, and we expect a redistribution of water in the atmosphere, oceans and continents, that will change the way the Earth’s crust is charged,” Frank adds. “That will surely have an impact and is a link we could explore further.”

HUNDREDS OF EARTHQUAKES IN JAPAN

Since late 2020, hundreds of small earthquakes have shaken Japan’s Noto Peninsula, a strip of land that curves north from the country’s main island toward the Sea of ​​Japan. Unlike a typical earthquake sequence, which begins as a main shock that gives way to a series of aftershocks before dying out, Noto’s seismic activity is an “earthquake swarm,” a pattern of multiple continuous earthquakes without any main shaking. or obvious seismic trigger. .

The MIT team, along with their colleagues in Japan, set out to detect any patterns in the swarm that would explain the persistent earthquakes. They started by looking at the Japanese Meteorological Agency’s earthquake catalog which provides data on seismic activity across the country over time. They focused on earthquakes that have occurred on the Noto Peninsula over the past 11 years, during which the region has experienced episodic seismic activity, including the most recent swarm.

Using seismic data from the catalog, the team counted the number of seismic events that occurred in the region over time and found that the timing of earthquakes before 2020 appeared sporadic and unrelated, compared to late 2020, when the earthquakes became more intense and clustered. over time, signaling the start of the swarm, with earthquakes being correlated in some way.

The scientists then examined a second set of data from seismic measurements taken by monitoring stations during the same 11-year period. Each station continuously records any local displacement or shaking that occurs. Shaking from one station to another can give scientists an idea of ​​the speed at which a seismic wave travels between stations. This “seismic velocity” is related to the structure of the Earth through which the seismic wave travels. Wang used the station’s measurements to calculate the seismic velocity between each station in and around Noto over the past 11 years.

The researchers generated an evolving picture of seismic velocity beneath the Noto Peninsula and observed a surprising pattern: In 2020, when the earthquake swarm is believed to have begun, changes in seismic velocity appeared to be synchronized with the seasons.

“Then we had to explain why we were seeing this seasonal variation,” says Frank.

The team wondered whether environmental changes from season to season could influence the underlying structure of the Earth in a way that would trigger a swarm of earthquakes. Specifically, they looked at how seasonal precipitation would affect underground “pore fluid pressure”: the amount of pressure that fluids in the Earth’s cracks and fissures exert within the bedrock.

“When it rains or snows, that adds weight, which increases pore pressure, allowing seismic waves to travel more slowly,” Frank explains. “When all that weight is removed, through evaporation or runoff, suddenly the pore pressure drops and the seismic waves become faster.”

Wang and Cui developed a hydromechanical model of the Noto Peninsula to simulate the underlying pore pressure over the past 11 years in response to seasonal changes in precipitation. They fed meteorological data from this same period into the model, including daily measurements of snow, precipitation and changes in sea level.

From their model, they were able to track changes in excess pore pressure beneath the Noto Peninsula, before and during the earthquake swarm. They then compared this timeline of pore pressure evolution with their evolving picture of seismic velocity.

“We had observations of the seismic velocity and the excess pore pressure model, and when we overlaid them, we saw that they fit together extremely well,” says Frank.

In particular, they found that when they included snowfall data and especially extreme snowfall data, the fit between the model and observations was stronger than if they only considered precipitation and other events. In other words, the swarm of earthquakes that Noto residents have been experiencing can be explained in part by seasonal rainfall and, in particular, heavy snowfall.

 
For Latest Updates Follow us on Google News
 

-

PREV a pink color could replace the blue color
NEXT Inspirational’24 presents the Online Jury of the Awards