Fundamental research on building a storm surge prediction model using neural networks for actual operation

Abstract

In this study, storm surge prediction in the Ariake Sea using a hierarchical neural network was conducted. The network was trained with only typhoon information (position, central pressure, and maximum wind speed radius) as input, using a dataset generated from storm surge calculations performed by FVCOM and d4PDF. As a result, we confirmed that storm surge could be predicted with high accuracy even with only typhoon information. Furthermore, we found that inputting the typhoon location as a distance angle from the prediction point, instead of latitude and longitude, improved the prediction accuracy even when using the same typhoon information because of improving the interpretability of the feature values. We evaluated the prediction accuracy using actual typhoon data as input and presented issues for the future operation of storm surge prediction.