Tidal characteristics from tide gauge data

DOI

Three datasets of tidal characteristics and datums from GESLA-4 tide gauges, including tidal trends, tidal duration, Highest Astronomical Tide (HAT), and Mean High Water (MHW). Tidal trends (tidal_trends.csv) were calculated solely from the University of Hawaii Sea Level Center (UHSLC) research-quality GESLA-4 dataset of gauges with more than 30 years of observations. The tidal duration (tidal_duration.csv) is created based on the full GESLA-4 dataset and is provided for locations in which spring tides are greater than approximately 0.15m and river influence is minor or negligible (see Talke (2025) for more information). The remaining tidal datums (in tidal_datums.csv) are based on 200-year tidal predictions on all tide gauges within TICON-4 (Hart-Davis et al., 2025). For all files, the ‘name’ variable is included, which is the tide gauge name as provided by GESLA-4 (https://www.gesla.org/). More information about particular tide gauge data can be found at GESLA-4. The methods and descriptions of this dataset are expanded in Hart-Davis et al (submitted to Ocean Science). The available DOI will be made available when submitted and available. For users who are here before this, please contact the contributors to this dataset for more information.    References: Hart-Davis M.G., Sulzbach R., Haigh I., Marcos I., Talke S., Ray R., Woodworth P., Dettmering D., Thomas M., Seitz F. Global characteristics of tides from in-situ gauges. In preparation. EGUSPHERE: EGUSPHERE-2026-346 Talke, S.A., 2025. How tidal properties influence the future duration of coastal flooding. npj Natural Hazards, 2(1), p.36. https://doi.org/10.1038/s44304-025-00086-3

Identifier
DOI https://doi.org/10.17882/111620
Metadata Access http://www.seanoe.org/oai/OAIHandler?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:seanoe.org:111620
Provenance
Creator Michael, Hart-davis; Roman, Sulzbach; Stefan, Talke
Publisher SEANOE
Publication Year 2026
Rights CC-BY
OpenAccess true
Contact SEANOE
Representation
Resource Type Dataset
Discipline Marine Science