4:30 PM - 4:45 PM
[S22-18] Real-Time Monitoring of the 2024 Note M7.6 Earthquake Genesis Process using Physical Wavelets
The Earth’s outer layer, the lithosphere, consists of three parts: the brittle upper crust, the ductile lower crust, and the ductile uppermost mantle. Movements in the Earth’s plates cause steady creep in the ductile layers, building stress in the brittle upper crust [1]. The stress has vertical and horizontal directions to the Earth’s surface. This stress leads to earthquakes (EQs) of different sizes.
The process of how the EQs form in the brittle upper crust is complex. Some scientists have tried to explain the complexity using models that see the EQ system as self-organizing or critically self-organized. However, these models over-simplify the EQ frequency and magnitude relationship by ignoring the detailed variations in the transition between the brittle and ductile layers [2].
The details are important because they challenge the patterns expected by the simplified relation and provide new insights into how significant EQs form. We address these challenges and use a novel tool, Physical Wavelets (PWs), to advance EQ and tsunami prediction methods. This innovative tool has been instrumental in analyzing complex seismic and GNSS data, offering a fresh perspective on the megathrust and significant EQ formations.
By challenging conventional understanding, we can significantly mitigate the impact of these natural disasters. It is important to note that our findings are built upon a solid foundation of previous studies and patents [3]. We used seismic data from Japan within the latitude and longitude range of 16°–52° and 116°–156°, respectively. By analyzing consecutive EQs with magnitudes above a certain level of Mc ≈ 4, we discovered a correlation between the moving sum of time intervals between the successive EQs and the region’s strain energy density. This finding has practical implications, as it allows us to predict when an impending significant EQ will occur by monitoring this energy’s accumulation and release cycles. The rapid release of this energy after its peak accumulation, known as Accelerated Moment Release, increases before the impending significant earthquake, providing a potential early warning system. The same method can be used to track the moving sum of EQ depths. If the energy is high, the EQs are deep. After reaching the peak, energy release shifts to shallower depths if the expected significant EQ is shallow. The energy keeps increasing for deeper significant events, like those in the Wadati-Benioff zone. We can predict the location of the impending EQ using smaller grid sizes and a lower magnitude threshold (Mc ≈ 3). These smaller-size analyses, combined with the entire region’s analysis, help predict the approximate epicenter, depth (deep or shallow), and exact date of the significant EQ occurrence.
We also identified two key processes to the significant EQ formation: CQK and CQT. CQK is after the 1995 Kobe M7.3 EQ, and CQT is after the 2000 Tottori M7.3 EQ. The CQK or CQT occurs in two spatially different segments shown by Japan’s Coda Q map [4], reflecting two distinct geological structures. Understanding the distinctive processes is crucial for improving our ability to predict and prepare for future significant EQs.
Japan’s GNSS network provides noisy daily data on crustal movement. By applying PWs to this data, we found out how the 2011 Tohoku M9 EQ formed over 15 months and identified the tsunami formation process over the last three months.
Similarly, by applying PWs to seismic and GNSS data, we can show how the Noto Peninsula M7.6 EQ on January 1, 2024, with a tsunami occurrence formed over three months. Thus, PWs could have provided real-time monitoring and early warnings for the 2024 Noto Peninsula EQ, potentially reducing the impact of the EQ and tsunami, and saving lives.
References
1. Zoback & Zoback (2002) State of stress in the Earth’s lithosphere, IHEES. 2. Takeda (2022) ArXiv. 2201.02815. 3. Takeda (2022) ArXiv. 2107.02799. 4. Jin & Aki (2005) High–resolution maps of Coda Q in Japan, EPS.
The process of how the EQs form in the brittle upper crust is complex. Some scientists have tried to explain the complexity using models that see the EQ system as self-organizing or critically self-organized. However, these models over-simplify the EQ frequency and magnitude relationship by ignoring the detailed variations in the transition between the brittle and ductile layers [2].
The details are important because they challenge the patterns expected by the simplified relation and provide new insights into how significant EQs form. We address these challenges and use a novel tool, Physical Wavelets (PWs), to advance EQ and tsunami prediction methods. This innovative tool has been instrumental in analyzing complex seismic and GNSS data, offering a fresh perspective on the megathrust and significant EQ formations.
By challenging conventional understanding, we can significantly mitigate the impact of these natural disasters. It is important to note that our findings are built upon a solid foundation of previous studies and patents [3]. We used seismic data from Japan within the latitude and longitude range of 16°–52° and 116°–156°, respectively. By analyzing consecutive EQs with magnitudes above a certain level of Mc ≈ 4, we discovered a correlation between the moving sum of time intervals between the successive EQs and the region’s strain energy density. This finding has practical implications, as it allows us to predict when an impending significant EQ will occur by monitoring this energy’s accumulation and release cycles. The rapid release of this energy after its peak accumulation, known as Accelerated Moment Release, increases before the impending significant earthquake, providing a potential early warning system. The same method can be used to track the moving sum of EQ depths. If the energy is high, the EQs are deep. After reaching the peak, energy release shifts to shallower depths if the expected significant EQ is shallow. The energy keeps increasing for deeper significant events, like those in the Wadati-Benioff zone. We can predict the location of the impending EQ using smaller grid sizes and a lower magnitude threshold (Mc ≈ 3). These smaller-size analyses, combined with the entire region’s analysis, help predict the approximate epicenter, depth (deep or shallow), and exact date of the significant EQ occurrence.
We also identified two key processes to the significant EQ formation: CQK and CQT. CQK is after the 1995 Kobe M7.3 EQ, and CQT is after the 2000 Tottori M7.3 EQ. The CQK or CQT occurs in two spatially different segments shown by Japan’s Coda Q map [4], reflecting two distinct geological structures. Understanding the distinctive processes is crucial for improving our ability to predict and prepare for future significant EQs.
Japan’s GNSS network provides noisy daily data on crustal movement. By applying PWs to this data, we found out how the 2011 Tohoku M9 EQ formed over 15 months and identified the tsunami formation process over the last three months.
Similarly, by applying PWs to seismic and GNSS data, we can show how the Noto Peninsula M7.6 EQ on January 1, 2024, with a tsunami occurrence formed over three months. Thus, PWs could have provided real-time monitoring and early warnings for the 2024 Noto Peninsula EQ, potentially reducing the impact of the EQ and tsunami, and saving lives.
References
1. Zoback & Zoback (2002) State of stress in the Earth’s lithosphere, IHEES. 2. Takeda (2022) ArXiv. 2201.02815. 3. Takeda (2022) ArXiv. 2107.02799. 4. Jin & Aki (2005) High–resolution maps of Coda Q in Japan, EPS.