GESLA Version 3: A major update to the global higher-frequency sea-level dataset
- 1School of Ocean and Earth Science, University of Southampton, National Oceanography Centre, European Way, Southampton, SO14 3ZH, UK
- 2University of the Balearic Islands, IMEDEA, Physics, Esporles, Spain
- 3Department of Civil and Environmental Engineering, California Polytechnic State University, San Luis Obispo, California, USA
- 4National Oceanography Centre, Liverpool L3 5DA, UK
- 5Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia
- 6Australian Bureau of Meteorology, GPO Box 1289, Melbourne, Victoria, Australia
- 7Faculty of Agricultural and Environmental Sciences, University of Rostock, Justus-von-Liebig-Weg 6, 18059, Rostock, Germany
- 8British Oceanographic Data Centre, National Oceanography Centre, Liverpool L3 5DA, UK
- 9Department of Oceanography, University of Hawaiʻi at Mānoa, Honolulu, Hawaiʻi, USA
This paper describes a major update to the quasi-global, higher-frequency sea-level dataset known as GESLA (Global Extreme Sea Level Analysis). Versions 1 (released 2009) and 2 (released 2016) of the dataset have been used in many published studies, across a wide range of oceanographic and coastal engineering-related investigations concerned with evaluating tides, storm surges, extreme sea levels and other related processes. The third version of the dataset (released 2021), presented here, contains twice the number of years of data (91,021), and nearly four times the number of records (5,119), compared to version 2. The dataset consists of records obtained from multiple sources around the world. This paper describes the assembly of the dataset, its processing and its format, and outlines potential future improvements. The dataset is available from https://www.gesla.org.
How to cite: Haigh, I. D., Marcos, M., Talke, S. A., Woodworth, P. L., Hunter, J. R., Hague, B. S., Arns, A., Bradshaw, E., and Thompson, P.: GESLA Version 3: A major update to the global higher-frequency sea-level dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9778, https://doi.org/10.5194/egusphere-egu22-9778, 2022.