Tsunamis can be extremely dangerous and can cause widespread destruction and loss of life. Tsunamis are large waves that are caused by sudden movements of the Earth’s crust, such as earthquakes, landslides, or volcanic eruptions. These waves can travel across oceans at high speeds, and when they reach the shore, they can grow to be several meters in height.
The danger of a tsunami depends on a number of factors, including the size of the wave, the distance it has traveled, and the topography of the coastline. In general, tsunamis that originate from closer to the shore are more dangerous, as they have less time to dissipate before they reach the coast.
RIKEN Prediction Science Laboratory makes it possible to predict tsunamis
A new press release reveals that the RIKEN Prediction Science Laboratory has predicted tsunami impacts in about a second and by exploiting the powers of machine learning. Therefore, we can now have high hopes that people who live in areas where tsunamis are about to occur will benefit from in-time warnings from the authorities.
Iyan Mulia from RIKEN explained in the aforementioned press release:
The main advantage of our method is the speed of predictions, which is crucial for early warning,
Conventional tsunami modeling provides predictions after 30 minutes, which is too late. But our model can make predictions within seconds.
The coast boasts the world’s most extensive system of sensors for monitoring the movement that occurs on the ocean floor. This network, which consists of around 150 offshore stations, works together to provide early warnings of tsunamis. In order to function optimally, the data generated by these sensors must be transformed into estimates of the size and extent of tsunamis along the coastline. These estimates are crucial for providing accurate and timely warnings to communities at risk of being affected by tsunamis. By utilizing this sophisticated system of sensors, authorities are able to monitor and predict the likelihood of tsunamis, allowing them to take necessary precautions to protect lives and property.