ASM-SS: The First Quasi-Global High Spatial Resolution Coastal Storm Surge Dataset Reconstructed from Tide Gauge Records

Abstract. Storm surges (SSs) cause massive loss of life and property in coastal areas each year. High spatial resolution and long-term SS records are the basis for deepening our understanding of this disaster. However, such global or quasi-global scale information could only be simulated by global numerical models until now due to the sparse and uneven distribution of tide gauge stations. In this paper, the all-site modeling framework for the data-driven model was implemented on a quasi-global scale within areas severely affected by SSs caused by tropical and extratropical cyclones. Compared to single-site modeling data-driven models, it can provide SS information for ungauged points. Compared to numerical models, it can reconstruct long-term SSs faster with fewer computational resources. We generated the first high spatial resolution (every 10 km per station along the coastline) hourly SS dataset ASM-SS (all-site modeling storm surge) within 45° S to 45° N, whose record length is over 80 years from 1940 to 2020. Assessments indicate that for 95th extreme SSs, the precision of this model (medians of correlation coefficients, root mean square errors, and mean biases are 0.66, 9 cm, and -4.4 cm, respectively) is slightly better than that of the state-of-the-art global hydrodynamic model (medians are 0.58, 10.8 cm, and -4.3 cm); for annual maximum SSs, our model is more stable than the numerical model with overall root mean square error and coefficient of determination optimizing by around 23.1 % and 14.8 %, respectively. This dataset could provide possible alternative support for coastal communities to estimate return levels of extremes, analyze variations (intensity, frequency, and trend) of SSs, and other relevant applications. The ASM-SS dataset is available at https://doi.org/10.5281/zenodo.13293595 (Yang et al., 2024a).