ASM-SS: the first quasi-global high-spatial-resolution coastal storm surge dataset reconstructed from tide gauge records
<p>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-glob...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-06-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/2793/2025/essd-17-2793-2025.pdf |
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| Summary: | <p>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 <span class="inline-formula">−0.050 m</span>, respectively) is better than that of the state-of-the-art global hydrodynamic model (the medians are 0.55, 0.106, and <span class="inline-formula">−0.045 m</span>). 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 <a href="https://doi.org/10.5281/zenodo.14034726">https://doi.org/10.5281/zenodo.14034726</a> (Yang et al., 2024a).</p> |
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| ISSN: | 1866-3508 1866-3516 |