Tsunami Scenario

Tsunami scenario research focuses on improving the accuracy and efficiency of tsunami prediction and detection models. Current efforts involve developing and refining probabilistic models, often incorporating advanced numerical methods like finite volume methods and machine learning techniques such as deep learning (e.g., convolutional neural networks) and Bayesian approaches to handle uncertainty and large datasets. These advancements aim to enhance early warning systems by improving the accuracy of tsunami forecasts and expanding detection capabilities beyond traditional buoy networks, potentially leveraging data from sources like GNSS signals. Ultimately, this research strives to mitigate the devastating impacts of tsunamis on coastal communities.