10:45 AM - 12:15 PM
[SSS11-P04] Further Evidence that Moon Tidal Forces Affect Seismicity on Earth
Keywords:earthquake forecasting, coupled dynamical systems, forecasting point processes, lunar tidal force
Introduction
Despite the vast literature on earthquake forecasting, we are still largely unable to forecast large events. In spite of that, it is clear that advances have been achieved in each subfield of earthquake forecasting. In this communication, we concentrate on the particular problem of next-day forecasting, which is generally seen as more difficult than long-term forecasting.
In [5] we presented our prediction framework for performing next-day forecasting, which basically consists of comparing, using edit distances, patterns of earthquakes within windows of 7 days, and subsequently feeding these distances to train a radial basis function predictor. There, we had also investigated the influence of the Sun on seismic activity on Earth, and found pieces of evidence that such an influence indeed exists. In the field, identifying and evaluating precursor phenomena is a common way to improve the accuracy of earthquake forecasting [2].
Giving sequence to [5], here we focus on the effects exerted by the Moon, in particular those related to the tidal force it subjects the Earth to. The tidal force is hypothesized to influence earthquakes because it deforms not only the ocean levels, but also the solid crust as well, which could be responsible for promoting the accumulation of more strain energy in the faults, as well as being responsible for the occurrence of nucleations that can evolve into an earthquake. The effects of tidal forces in seismic activity has been analyzed in the literature already [3], and here we contribute to the discussion by focusing on next-day forecasting and using other mathematical tools to demonstrate such effects.
Results
Initially, we found that the method of Andrzejak and Kreuz [1] indicates that the Moon drives earthquakes (from a dynamical systems perspective) to some extent, since L(Y→X) is almost always larger than zero (p < 0.05) and much larger (in absolute value) than L(X→Y), where X represents the earthquake system and Y, the Moon one. The only case where that does not happen is for the Touhoku subregion in Japan, where we obtained a negative value for L(Y→X), which does not have much significance according to the method. We also identify unidirectional coupling when using the method of Hirata et al. [4]. Here, the p-values for the Y→X case are most often significantly smaller than for X→Y. Overall, with both methods, we see that in the large majority of cases they indicate a coupling Y→X, so there is evidence to believe that such a coupling indeed exists.
We also analyzed the correlation between the differential pull and the magnitude of each earthquake. In Figure 1, we show what happens to the average differential pull if we take only earthquakes that exceed a certain magnitude threshold m, represented by the x-axis. The figure shows a clear tendency of the average differential pull to grow together with the magnitude threshold chosen, which we can interpret as a tendency of larger magnitude earthquakes to happen when there is a higher tide.
The above pieces of evidence should serve to strengthen the hypothesis that the Moon has an influence on earthquake occurrence, and future work should focus on how to take advantage of this to improve accuracy of forecasting.
[1] Ralph Andrzejak and Thomas Kreuz. Characterizing unidirectional couplings between point processes and flows. Europhysics Letters, 2011.
[2] Robert Cicerone, John Ebel, and James Britton. A systematic compilation of earthquake precursors. Tectonophysics, 2009.
[3] Jinlai Hao, Jinhai Zhang, and Zhenxing Yao. Evidence for diurnal periodicity of earthquakes from midnight to daybreak. National science review, 2019.
[4] Yoshito Hirata, José Amigó, Yoshiya Matsuzaka, et al. Detecting causality by combined use of multiple methods: Climate and brain examples. PLOS ONE, 2016.
[5] Matheus Saldanha and Yoshito Hirata. Solar activity facilitates daily forecasts of large earthquakes. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022.
Despite the vast literature on earthquake forecasting, we are still largely unable to forecast large events. In spite of that, it is clear that advances have been achieved in each subfield of earthquake forecasting. In this communication, we concentrate on the particular problem of next-day forecasting, which is generally seen as more difficult than long-term forecasting.
In [5] we presented our prediction framework for performing next-day forecasting, which basically consists of comparing, using edit distances, patterns of earthquakes within windows of 7 days, and subsequently feeding these distances to train a radial basis function predictor. There, we had also investigated the influence of the Sun on seismic activity on Earth, and found pieces of evidence that such an influence indeed exists. In the field, identifying and evaluating precursor phenomena is a common way to improve the accuracy of earthquake forecasting [2].
Giving sequence to [5], here we focus on the effects exerted by the Moon, in particular those related to the tidal force it subjects the Earth to. The tidal force is hypothesized to influence earthquakes because it deforms not only the ocean levels, but also the solid crust as well, which could be responsible for promoting the accumulation of more strain energy in the faults, as well as being responsible for the occurrence of nucleations that can evolve into an earthquake. The effects of tidal forces in seismic activity has been analyzed in the literature already [3], and here we contribute to the discussion by focusing on next-day forecasting and using other mathematical tools to demonstrate such effects.
Results
Initially, we found that the method of Andrzejak and Kreuz [1] indicates that the Moon drives earthquakes (from a dynamical systems perspective) to some extent, since L(Y→X) is almost always larger than zero (p < 0.05) and much larger (in absolute value) than L(X→Y), where X represents the earthquake system and Y, the Moon one. The only case where that does not happen is for the Touhoku subregion in Japan, where we obtained a negative value for L(Y→X), which does not have much significance according to the method. We also identify unidirectional coupling when using the method of Hirata et al. [4]. Here, the p-values for the Y→X case are most often significantly smaller than for X→Y. Overall, with both methods, we see that in the large majority of cases they indicate a coupling Y→X, so there is evidence to believe that such a coupling indeed exists.
We also analyzed the correlation between the differential pull and the magnitude of each earthquake. In Figure 1, we show what happens to the average differential pull if we take only earthquakes that exceed a certain magnitude threshold m, represented by the x-axis. The figure shows a clear tendency of the average differential pull to grow together with the magnitude threshold chosen, which we can interpret as a tendency of larger magnitude earthquakes to happen when there is a higher tide.
The above pieces of evidence should serve to strengthen the hypothesis that the Moon has an influence on earthquake occurrence, and future work should focus on how to take advantage of this to improve accuracy of forecasting.
[1] Ralph Andrzejak and Thomas Kreuz. Characterizing unidirectional couplings between point processes and flows. Europhysics Letters, 2011.
[2] Robert Cicerone, John Ebel, and James Britton. A systematic compilation of earthquake precursors. Tectonophysics, 2009.
[3] Jinlai Hao, Jinhai Zhang, and Zhenxing Yao. Evidence for diurnal periodicity of earthquakes from midnight to daybreak. National science review, 2019.
[4] Yoshito Hirata, José Amigó, Yoshiya Matsuzaka, et al. Detecting causality by combined use of multiple methods: Climate and brain examples. PLOS ONE, 2016.
[5] Matheus Saldanha and Yoshito Hirata. Solar activity facilitates daily forecasts of large earthquakes. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022.