In this blog post, we will explore the principles behind earthquake occurrence, the differences between magnitude and intensity, and various prediction methods such as precursor phenomena, propagation changes, and smartphone sensor-based detection. We will examine both the potential and limitations of earthquake prediction.
Before explaining earthquake prediction methods, it is essential to first understand precisely what an earthquake is. An earthquake refers to the phenomenon where the earth’s surface shakes due to the sudden fracturing of underground rock caused by immense forces acting within the Earth. In other words, a sudden change occurs at some point within the Earth, generating seismic waves that travel to the surface, causing the ground to vibrate. Causes of earthquakes include volcanic activity, fault movement, and crustal subsidence. The Gyeongju and Pohang earthquakes, which caused significant shock to the people of South Korea, are also understood to have been triggered by the release of energy accumulated along the Yangsan Fault.
Among the concepts of earthquakes, magnitude and intensity are both the most fundamental and the most important. Reviewing earthquake-related articles reveals that many journalists easily confuse the precise meanings of these two terms. This phenomenon is equally prevalent among the general public. Magnitude is a measure of an earthquake’s absolute intensity, calculated by measuring the amount of energy released. Expressions like ‘an M5.8 earthquake’ commonly used refer precisely to this magnitude. Magnitude values are assigned from the perspective of seismic energy; each increase of 1 in magnitude corresponds to approximately a 32-fold increase in seismic energy and a 10-fold increase in amplitude. Conversely, intensity is a measure of the relative strength actually felt by an observer at a specific location. Because it is observer-based, even a large magnitude earthquake will register as low intensity if the epicenter is distant.
An earthquake does not simply vibrate once and end. It releases stress in the surrounding strata, accompanied by a series of smaller earthquakes. Viewed from a future perspective, the strongest earthquake occurring at the same time and place is called the mainshock. The initial earthquake occurring before the mainshock is called the foreshock, and the small earthquakes occurring sporadically after the mainshock are called aftershocks. Generally, the number of aftershocks tends to be proportional to the magnitude of the mainshock.
The underground point where the earthquake originates is called the hypocenter, and the point on the ground surface directly above the hypocenter is called the epicenter. Therefore, when an earthquake occurs, the epicenter is affected first, followed by seismic waves propagating spherically outward from the hypocenter and reaching the surrounding ground surface.
The waves generated during an earthquake are called seismic waves, which are classified into P-waves (Primary), S-waves (Secondary), L-waves (Love waves), and R-waves (Rayleigh waves). These seismic waves arrive in the order P-wave, S-wave, L-wave, R-wave. Significant damage typically occurs after the S-wave arrives. The time from the arrival of the P-wave to the arrival of the S-wave is called the PS time. By measuring this time, the location of the hypocenter can be estimated.
As evident from the fact that large-scale earthquake damage continues to occur worldwide, no reliable method for accurately predicting earthquakes has been discovered to date. However, while imperfect, several active earthquake prediction methods exist and are being vigorously researched. These methods may advance further in the future, potentially leading to more accurate prediction systems.
The first prediction method to introduce is precursory phenomena. This method generates the most controversy and is difficult to consider scientifically validated. Nevertheless, among precursory phenomena, animal abnormal behavior is particularly intriguing. Since animals are known to possess more sensitive senses than humans, many people suspect unusual animal movements they witness as precursors to earthquakes. Cases have been reported worldwide of various animals, including birds and amphibians, migrating in large groups or exhibiting completely different behavior than usual before major earthquakes. In South Korea, during the Gyeongju earthquake, tens of thousands of mullet were observed moving in a straight line in the Taehwa River in Ulsan, and ants were seen moving in swarms in Gwangalli, Busan. However, the causal relationship between such animal behavior and earthquake occurrence has not yet been scientifically established, making it difficult to consider this a reliable prediction method.
The second precursor phenomenon is earthquake lights, or luminous phenomena. There are frequent reports of large, sudden flashes of blue light, similar to lightning, appearing in the sky just before an earthquake occurs, followed by the actual strong tremor. This is explained by the piezoelectric effect: when the tectonic plates forming the crust undergo intense pressure just before an earthquake, the quartz rock layers within the bedrock are exposed to high piezoelectric stress, generating a strong electric field. This electric field then causes the luminous phenomenon in the sky.
Earthquake clouds, appearing as thick band-shaped cirrus clouds, scaly cirrocumulus clouds, whirlwind-like formations, or fan-shaped clouds, are also known as precursors to earthquakes. Earthquake clouds form immediately before an earthquake occurs and are known to possess relatively strong predictive capabilities among precursor phenomena. This is because gases and water vapor erupting from surface fractures caused by the earthquake rise into the air, forming band-like or striped clouds.
The second prediction method involves detecting changes in radio waves. In December 2015, Professor GuoZe Zhao’s team at the China Earthquake Administration published research findings suggesting that detecting minute changes in radio waves generated when the crust shakes can predict earthquakes. According to this study, the movement of the inner crust before an earthquake affects surrounding radio waves, and detecting these changes can predict earthquakes. The team proposed installing antennas around earthquake-prone areas to continuously transmit and receive signals via satellite, observing how these signals fluctuate, as the changes are extremely subtle.
The final prediction method introduced utilizes smartphone sensors. As explained earlier, P-waves and S-waves arrive at different times. This system was developed based on this principle. As mentioned previously, major damage occurs after the S-wave arrives. Therefore, the method detects the P-wave upon arrival and evacuates residents before the S-wave reaches them. While not strictly ‘prediction’ in the strictest sense, it functions more as an early warning after P-wave arrival. However, securing even a few seconds before the S-wave arrives can significantly reduce damage. Though a very short time, people can use those few seconds to take cover or prepare for the earthquake.
Smartphone sensors are used to detect precisely those P-waves. The principle is simple. Most smartphones are equipped with GPS devices. If the phenomenon of GPS receivers suddenly shaking in one direction occurs only on a small number of smartphones, it is unlikely to be an earthquake. However, if the same shaking is observed simultaneously on thousands of smartphones, the probability of an earthquake becomes very high. In other words, it detects earthquakes occurring in specific regions by collecting shaking data from a large number of GPS devices. Because most people today use smartphones, this system is expected to become even more valuable in the future. If many people, including citizens of the Republic of Korea, install earthquake early warning applications on their smartphones, the amount of collected data would increase exponentially, enabling this system to operate at a near-perfect level.
If accurate earthquake prediction methods are established, it would significantly reduce the damage caused by earthquakes currently occurring worldwide. Even at this very moment, many people are losing their lives, losing family members, and losing their homes due to earthquakes. If humanity acquires the technological capability to effectively respond to natural disasters, such innocent sacrifices could be prevented. While research in IT, artificial intelligence, and computer science is important, I hope this field—directly connected to human life and capable of saving countless lives—receives even more attention and is actively researched.
