Using over 4,500 GNSS receivers across Japan, the team mapped electron density changes in the ionosphere following the 7.5 magnitude earthquake that struck Ishikawa Prefecture on January 1, 2024. Led by Dr. Weizheng Fu and Professor Yuichi Otsuka from the Institute for Space-Earth Environmental Research (ISEE), the researchers revealed the intricate 3D structure of these disturbances, demonstrating the power of GNSS technology to monitor atmospheric effects.
GNSS signals slow as they pass through the ionosphere due to interactions with electrically charged particles. By measuring the delay, scientists can estimate the total electron content along the signal path, effectively mapping the ionosphere's state. About 10 minutes after the earthquake, the sound waves generated by the quake reached the ionosphere (60-1000 km above Earth), creating ripple-like disturbances similar to those seen when a stone splashes into a pond.
To reconstruct the 3D patterns, the team employed a tomographic technique akin to a CT scan. By analyzing data from thousands of GNSS receivers at different angles, they produced time series showing how electron density evolved after the earthquake.
South of the epicenter, the researchers observed that the sound wave pattern initially tilted and then straightened over time. This occurs because upper parts of the waves move faster than lower parts, causing a leaning wave front that becomes more vertical as it propagates. The researchers achieved the first detailed 3D visualization of this dynamic, capturing the progressive straightening in unprecedented detail.
Previous models assumed all sound waves originated from a single point at the earthquake's center. However, the observed patterns were more complex than those models predicted. By incorporating multiple sources along the fault line and factoring in time delays between different fault segments, the researchers' new model better matched real-world data. This approach revealed that earthquakes generate atmospheric waves from multiple fault segments, not just a single epicenter.
"By including multiple distributed sources and time delays, our improved modeling provides a more accurate representation of how these waves propagate through the upper atmosphere," Professor Otsuka explained.
Dr. Weizheng Fu, lead author of the study, added, "Disturbances in the ionosphere can interfere with satellite communications and location accuracy. If we understand these patterns better, we could improve our ability to protect sensitive technologies during and after earthquakes and enhance early warning systems for similar natural events."
The team now plans to apply this modeling approach to other natural phenomena, including volcanic eruptions, tsunamis, and severe weather events.
Research Report:Unveiling the vertical ionospheric responses following the 2024 Noto Peninsula Earthquake with an ultra-dense GNSS network
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