A real-time storm surge prediction system for the Guangdong–Hong Kong–Macao Greater Bay Area under the background of typhoons: model setup and validation

Storm surges are the most severe type of marine disaster affecting the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), and storm surge forecasting under the background of typhoons remains challenging. In this paper, we propose an operational coupling model (including the global–regional assimilation and prediction system [GRAPES] atmospheric model and the finite volume coastal ocean model [FVCOM]) to predict typhoon-induced storm surges in the GBA, namely, the Greater Bay Area Storm Surge Prediction System (GBASSP), and verified its performance. The highest horizontal resolution of the GBASSP is 80 m, and the time from the start of the system to the end of the the post-processing is about 100 min. The model is fast enough to meet operational requirements. It has the following advantages. (i) It can provide early warning and forecasting for storm surge at least 2 days before typhoon landfall. (ii) For the next 24-hour forecast of a single typhoon, the maximum storm surge error is only 5 cm, while the mean absolute error of the maximum storm surge of the GBASSP is 19.7 cm. The difference in the occurrence time of the maximum storm surge between observations and the GBASSP is within 1 h. (iii) Comprehensively compared to other storm surge prediction models, the GBASSP performs well and has the best forecasting skills. The relative and root mean square errors of the GBASSP are 5.9% and 21 cm, respectively, the smallest of all the comparative models used in this study. In addition, the average absolute error is between those of the other models.