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-coverage and long-term SS records are the basis for deepening our understanding of these disasters. Due to the sparse and uneven distribution of tide gauge stations, such global or quasi-global information can only be provided by global numerical models, while their simulation products mainly span the most recent decades. In this paper, for the first time, an all-site modeling framework for a data-driven model was implemented on a quasi-global scale within areas severely affected by SSs caused by tropical cyclones. Using tide gauge records and European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) data, we generated a high-spatial-resolution (10 km along the coastline) hourly SS dataset, ASM-SS (all-site modeling storm surge), within the span 45° S–45° N, whose record length is over 80 years from 1940 to 2020. Assessments indicate that, for 95th extreme SSs, the precision of the ASM-SS model (the medians of the correlation coefficients, root mean square errors, and mean biases are 0.63, 0.093, and − 0.050 m, respectively) is better than that of the state-of-the-art global hydrodynamic model (the medians are 0.55, 0.106, and −0.045 m). For annual maximum SSs, it is more stable than the numerical model, with the overall root mean square error and coefficient of determination optimizing by 22.3 % and 14.8 %, respectively. This dataset could provide possible alternative support for coastal communities through relevant SS analysis applications requiring high spatial resolution and sufficiently long records. The ASM-SS dataset is available at https://doi.org/10.5281/zenodo.14034726 (Yang et al., 2024a).