Extension of a high temporal resolution sea level time series at Socoa (Saint-Jean-de-Luz, France) back to 1875

• Published in: Earth System Science Data
• Main Authors: M. J. U. Khan, I. Van Den Beld, G. Wöppelmann, L. Testut, A. Latapy, N. Pouvreau
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2023
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; North Atlantic
• Online Access: https://doi.org/10.5194/essd-15-5739-2023; https://doaj.org/article/1d1691d2cd2c43218ab444f4132ec795

In this data paper, the sea level time series at Socoa (Saint-Jean-de-Luz, southwestern France) is extended through a data archaeology exercise. We conducted a comprehensive study of national and local archives to catalogue water level records stored in ledgers (handwritten record books) and charts (marigrams from mechanical float gauges), along with other associated documents (metadata). A dedicated effort was undertaken to preserve more than 2000 documents by archiving them in digital formats. Using this large set of rescued documents, the Socoa time series has been extended back to 1875, with more than 58 station-years of additional data. The final time series has hourly sampling, while the raw dataset has a finer sampling frequency of up to 5 min. By analysing precise levelling information, we assessed the continuity of the vertical datum. We also compared the new century-long time series to nearby tide gauge data to ensure its datum consistency. While the overall quality of the time series is generally good, siltation of the stilling well has occasionally affected certain parts of the record. We have successfully identified these impacted periods and flagged the corresponding data as doubtful. This extended high-resolution sea level time series at Socoa, spanning more than 100 years, will be valuable for advancing climate research, particularly when studying the decadal-scale variations in the North Atlantic and investigating the storminess and extreme events along the French Basque coast. The raw digitized water level, the processed dataset, metadata, and the python notebooks used for processing are available at https://doi.org/10.5281/zenodo.7438469 (Khan et al., 2022).