Real-Time Prediction of Typhoon-Induced Storm Surge in the Greater Bay Area: A Model Setup and Validation Study

Typhoon-induced storm surges pose the most severe marine disaster threat to the densely populated and economically vital Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Accurate and timely forecasting of these events remains a significant operational challenge. To address this, we developed and validated an advanced, real-time storm surge prediction system for the GBA—the Greater Bay Area Storm Surge Prediction System (GBASSP). This operational system features a tightly coupled framework, integrating the Global/Regional Assimilation and Prediction System (GRAPES) atmospheric model with the Finite-Volume Coastal Ocean Model (FVCOM). The GBASSP achieves an exceptionally high horizontal resolution of up to 80 meters in critical coastal zones, enabling detailed simulation of complex coastlines and estuary dynamics. The performance of GBASSP was rigorously verified against observational data. Key findings demonstrate its robust forecasting capability: (i) The system provides reliable early warning and surge forecasts with a lead time of at least two days prior to typhoon landfall. (ii) For 24-hour forecasts during typhoon events, the model exhibits high accuracy, with a maximum storm surge error as low as 5 cm for specific cases and a mean absolute error for maximum surge heights of 19.7 cm across evaluated events. Furthermore, the timing error for the predicted peak surge is consistently within one hour of observations. (iii) In a comprehensive comparative analysis with other established storm surge prediction models, GBASSP shows superior skill. It achieves the smallest relative error (5.9%) and root mean square error (21 cm) among all models compared. Its average absolute error also falls within the range of the best-performing benchmarks. In conclusion, the GBASSP establishes itself as a high-precision, operational tool for real-time storm surge forecasting in the GBA. Its coupled atmosphere-ocean design, very high resolution, and demonstrated accuracy in predicting both surge magnitude and timing make it a valuable asset for disaster prevention, mitigation, and emergency response, ultimately contributing to enhanced coastal resilience against typhoon threats.