This is the previous GESLA website for Version 2. Data can be downloaded below.

GESLA Background 

The GESLA (Global Extreme Sea Level Analysis) project grew out of the interests of several people in learning more about the changes in the frequency and magnitude of extreme sea levels. The first formal GESLA data set (denoted GESLA-1) was assembled by Philip Woodworth (National Oceanography Centre Liverpool), Melisa Menendez (University of Cantabria) and John Hunter (University of Tasmania) around 2009 and contained a quasi-global set of ‘high frequency’ (i.e. hourly or more frequent) measurements of sea level from tide gauges around the world.

GESLA-1 was used first in a study of sea level extremes by Woodworth and Menendez (Journal of Geophysical Research, 2010). It has since been used in a number of other published studies of extremes including the Intergovernmental Panel on Climate Change Fifth Assessment Report.

After some years it became apparent that GESLA-1 needed updating, which has resulted in the present GESLA-2 that contains 1355 records and 39151 station-years. The three people above have been joined in GESLA by Marta Marcos (University of the Balearic Islands) and Ivan Haigh (University of Southampton).

A list of some of the published papers that have made use of either GESLA-1 or GESLA-2 is given below. It can be seen that, while the study of extreme sea levels has been the main interest, the availability of as large a quasi-global sea level data set as possible enables many other types of study, such as changes in the ocean tides. We believe that the oceanographic community needs a global data set such as GESLA, that is regularly updated and extended to include new historical data as it becomes available, and we are taking steps to see how that might be accomplished in the future.

The GESLA-2 data set was described by Woodworth et al. (2017).

GESLA Data Sets 

How is GESLA constructed? 

We have benefited from the fact that suitable data are now readily accessible from many national web sites, requiring only reformatting to make them available for scientific research (see the link below for the format description). In addition, we have traded on the excellent personal links that we have established though the years to ask for data that is not otherwise publicly available. These data files have also been reformatted and added to the combined set. Thirdly we have made use of the data held by the international data centres, in particular the University of Hawaii Sea Level Center. UH have done an excellent job for many years in collecting and quality controlling (QCing) sea level records, and UH information comprises over a quarter of GESLA.

At the present time we do not normally perform our own separate QC of the data we receive, we assume that some form of QC has already been undertaken by the national and other authorities. We realise that this is not a perfect situation and we intend that a subset of GESLA (perhaps the longest records) will be subject to a separate QC by us in a subsequent step.

How is GESLA data made available? 

Data from the various sources mentioned above have been provided to us on the understanding that it can be copied readily to other interested users, or can be copied subject to a firm acknowledgement to the original data owner, or cannot be copied at all.

This means that we cannot at the present time make the entire data set available to everyone as we would like. Any bona fide researcher should contact with an explanation of why they would like access to the entire GESLA-2 data (i.e. both the ‘public’ and ‘private’ parts). We will then decide if we can accede to the request and we will specify the terms and conditions. In practice, this will depend strongly on whether we know the researcher or know of their previous research, so speculative enquiries will almost certainly be declined.

To download that part of the data set which is public and for which there is no problem with general access, follow this link. This file is essentially the same as that described by the Identifier: doi:10.5285/3b602f74-8374-1e90-e053-6c86abc08d39 in Woodworth et al. (2017), but with a small number of corrections to station locations and other minor changes.

To download that part of the data set which is private, follow this link (use “gesla_private” as user name, and password which will be provided if access is granted).

We intend that all the data will eventually be made available via one or more of the international sea level centres.

GESLA Data Sources 

There are 30 sources of data in GESLA-2. We consider 27 of them to be ‘public’, subject in some cases to the sources being explicitly recognised, while 3 of them are ‘private’. There is one file per station and the end of the station filename indicates the source as shown below. The number of records and the number of station-years are indicated. In total there are 1355 records and 39151 station-years.

There will some duplication between sea level records provided by the different sources. In general we advise to use the longest and most recently complete record at a site with more than one. The sets of records shown as ‘copied from GESLA-1’ will be older records without recent data.

Right-hand part of filename <country>-<contributor> No. records No. station-years Source 
glossdm-bodc 191 3380 GLOSS Delayed Mode data copied from GESLA-1 
*-uhslc 679 15992 from 
japan-jma 80 3072 from Japan Meteorological Agency 
uk-bodc 46 1627 from;
usa-noaa 73 3398 from 
france_med-refmar 14 216 from – acknowledgement needed 
spain-pde 31 460 from Puertos del Estado, Spain 
canada-meds 26 2017 from Marine Environmental Data Service, Canada 
egypt-noc 20 Alexandria data processed by NOC, UK 
10 spain-ieo 10 609 from Instituto Espanol de Oceanografica, Spain 
11 italy-idromare 25 557 from idromare, Italy 
12 turkey-eseas 14 copied from GESLA-1 
13 france-refmar 29 1081 from – acknowledgement needed 
14 uk-noc 75 from;
15 sweden-smhi+30 1185 from SMHI, Sweden – acknowledgement needed. 
16 spain_atlantic-ieo 204 from Instituto Espanol de Oceanografica, Spain 
17 germany-bsh 99 from Federal Maritime and Hydrographic Agency, Germany 
18 finland-fmi 13 598 from Finnish Meteorological Institute – acknowledgement needed 
19 nl-rws 135 from Rijkswaterstaat Netherlands 
20 croatia-eseas copied from GESLA-1 
21 denmark-dmi 310 from;
22 norway-statkart 280 from Norwegian Hydrographic Service 
23 iceland-coastguard 45 from Icelandic Coastguard Service 
24 italy-itt 43 from Istituto Talassographico di Trieste 
25 italy-comune_venezia 32 from Venice Commune 
26 uk+ukraine-noc 31 data from the Uraine Vernadsky base processed by NOC, UK 
27 poland-eseas 42 copied from GESLA-1 

+ These data were replaced in June 2021 on advice from SMHI. The new files have a greater total span and there are now 30 stations and 2220 station-years from this source.


Right-hand part of filename <country>-<contributor> No. records No. station-years Source 
28 australia-johnhunter 29 1310 copied from GESLA-1, original data from National Tidal Centre 
29 australia-national_tidal_centre 47 2271 from National Tidal Centre Australia 
30 croatia-university_zagreb 41 from University of Zagreb 

“Problems” File 

A text file describing current known problems with GESLA-1 and GESLA-2 is here


Any reports or papers that make use of GESLA data should include an acknowledgement to this web site and refer to the paper by Woodworth et al. (2017). We would be grateful to be notified of such papers and, if possible, sent copies of them.


  • Menendez, M. and Woodworth, P.L. 2010. Changes in extreme high water levels based on a quasi-global tide-gauge dataset. Journal of Geophysical Research, 115, C10011, doi:10.1029/2009JC005997.
  • Woodworth, P.L. 2010. A survey of recent changes in the main components of the ocean tide. Continental Shelf Research, 30, 1680-1691, doi:10.1016/j.csr.2010.07.002.
  • Woodworth, P.L., Menendez, M. and Gehrels, W.R. 2011. Evidence for century-timescale acceleration in mean sea levels and for recent changes in extreme sea levels. Surveys in Geophysics, 32(4-5), 603-618 (erratum page 619), doi:10.1007/s10712-011-9112-8. [This is a review that includes mention of GESLA.]
  • Hunter, J. 2012. A simple technique for estimating an allowance for uncertain sea-level rise. Climatic Change, 113, 239-252, doi:10.1007/s10584-011-0332-1.
  • Hunter, J.R., Church, J.A., White, N.J. and Zhang, X. 2013. Towards a global regionally varying allowance for sea-level rise. Ocean Engineering, 71, 17-27, doi:10.1016/j.oceaneng.2012.12.041.
  • Chapters 3 and 13 of Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Stocker, T.F. et al.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
  • Nicholls, R.J., Hanson, S.E., Lowe, J.A., Warrick, R.A., Lu, X. and Long, A.J., 2014. Sea-level scenarios for evaluating coastal impacts. WIREs Clim Change, 5:129-150, doi: 10.1002/wcc.253.
  • Mawdsley, R.J., Haigh, I.D. and Wells, N.C. 2015. Global secular changes in different tidal high water, low water and range levels. Earth’s Future, 3, doi:10.1002/2014EF000282.
  • Marcos, M., Calafat, F.M., Berihuete, A. and Dangendorf, S. 2015. Long-term variations in global sea level extremes. Journal of Geophysical Research Oceans, 120, doi:10.1002/2015JC011173.
  • Mawdsley, R.J. and Haigh, I.D., 2016. Spatial and temporal variability and long-term trends in skew surges globally. Frontiers in Marine Science, 3:29, doi:10.3389/fmars.2016.00029.
  • Woodworth, P.L. 2017. Differences between Mean Tide Level and Mean Sea Level. Journal of Geodesy, 91, 69-90, doi:10.1007/s00190-016-0938-1.
  • Woodworth, P.L., Hunter, J.R. Marcos, M., Caldwell, P., Menendez, M. and Haigh, I. 2017. Towards a global higher-frequency sea level data set. Geoscience Data Journal, 3, 50-59, doi:10.1002/gdj3.42.
  • Slangen, A.B.A., van de Wal, R.S.W., Reerink, T.J., de Winter, R.C., Hunter, J.R., Woodworth, P.L. and Edwards, T. 2017. The impact of uncertainties in ice sheet dynamics on sea-level allowances at tide gauge locations. Journal of Marine Science and Engineering, 5, 21, doi:10.3390/jmse5020021.
  • Hunter, J.R., Woodworth, P.L., Wahl, T. and Nicolls, R.J. 2017. Using global tide gauge data to validate and improve the representation of extreme sea levels in flood impact studies. Global and Planetary Change, 156, 34-45, doi:10.1016/j.gloplacha.2017.06.007.
  • Marcos, M. and Woodworth, P.L. 2017. Spatio-temporal changes in extreme sea levels along the coasts of the North Atlantic and the Gulf of Mexico. Journal of Geophysical Research Oceans, 122, doi:10.1002/2017JC013065. Supplementary data is here.
  • Wahl, T., Haigh, I.D., Nicholls, R.J., Arns, A., Dangendorf, S., Hinkel, J., Slangen, A.B.A. 2017. Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis. Nature Communications, 16075.
  • Goodwin, P., Haigh, I.D., Rohling, E.J. and Slangen, A. 2017. A new approach to projecting 21st century sea-level changes and extremes. Earth’s Future 5 (2), 240-253, doi:10.1002/2016EF000508.
  • Ward, P.J. Couasnon, A., Eilander, D., Haigh, I.D., Hendry, A., Muis, S., Veldkamp T.I.E, Winsemius, H.C. and Wahl, T., 2018. Dependence between high sea-level and high river discharge increases flood hazard in global deltas and estuaries, Environmental Research Letters, 13, 084012, doi:10.1088/1748-9326/aad400.
  • Wolff, C. et al. 2018. A Mediterranean coastal database for assessing the impacts of sea-level rise and associated hazards. Scientific Data, 5, 180044, doi:10.1038/sdata.2018.44.
  • Tsitsikas, C. 2018. Regional sea level allowances along the world coast-line. Master’s Thesis, Utrecht University.
  • Piccioni, G. et al. 2018. Coastal improvements for tide models: the impact of ALES retracker. Remote Sensing, 10, 700, doi:10.3390/rs10050700.
  • Cid, A., Wahl, T., Chambers, D.P. and Muis, S. 2018. Storm surge reconstruction and return water level estimation in Southeast Asia for the 20th century. Journal of Geophysical Research Oceans, 123, 437-451, doi:10.1002/2017JC013143.
  • Schindelegger, M., Green, J.A.M., Wilmes, S.-B. and Haigh, I.D. 2018. Can we model the effect of observed sea level rise on tides? Journal of Geophysical Research Oceans, 123, doi:10.1029/2018JC013959.
  • Woodworth, P.L. and Hibbert, A. 2018. The nodal dependence of long-period ocean tides in the Drake Passage. Ocean Science, 14, 711-730, doi:10.5194/os-14-711-2018.
  • Williams, J., Irazoqui Apecechea, M., Saulter, A. and Horsburgh, K. J. 2018. Radiational tides: their double-counting in storm surge forecasts and contribution to the Highest Astronomical Tide. Ocean Science, 14, 1057-1068, doi:10.5194/os-14-1057-2018.
  • Marcos, M. and Woodworth, P.L. 2018. Changes in extreme sea levels. CLIVAR Exchanges/US CLIVAR Variations, 16(1), 20-24, doi:10.5065/D6445K82.
  • Peng, D., Hill, E.M., Meltzner, A.J. and Switzer, A.D., 2019. Tide gauge records show that the 18.61-year nodal tidal cycle can change high water levels by up to 30 cm. JGR Oceans., 124 (1), 736-749, doi:10.1029/2018JC014695.
  • Rohmer, J. and Le Cozannet, G. 2019, Dominance of the mean sea level in the high percentile sea levels time evolution with respect to large-scale climate variability: a Bayesian statistical approach. Environmental Research Letters, 14, 014008, doi:10.1088/1748-9326/aaf0cd.
  • Witze, A. 2018. Attack of the extreme floods. Nature, 555, 156-158, doi:10.1038/d41586-018-02745-0.
  • Harker, A., Green, J. A. M., Schindelegger, M., and Wilmes, S.-B. 2019. The impact of sea-level rise on tidal characteristics around Australia. Ocean Science, 15, 147-159, doi:10.5194/os-15-147-2019.
  • Marcos, M., Wöppelmann, G., Matthews, A. et al. 2019. Coastal sea level and related fields from existing observing systems. Surveys in Geophysics, doi:10.1007/s10712-019-09513-3.
  • Santamaria-Aguilar, S. and Vafeidis, A.T. 2019. Are extreme skew surges independent of high water levels in a mixed semidiurnal tidal regime? Journal of Geophysical Research, 123, 8877-8886, doi:10.1029/2018JC014282.
  • Muis, S., Haigh, I.D., Nobre, G.G., Aerts, J.C.J.H. and Ward, P.J. 2018. Influence of El Niño-Southern Oscillation on global coastal flooding. Earth’s Future, 6, 1311-1322, doi:10.1029/2018EF000909.
  • Devlin, A.T., Pan, J. and Lin, H. 2019. Extended spectral analysis of tidal variability in the North Atlantic Ocean. Journal of Geophysical Research, 124, 506-526, doi:10.1029/2018JC014694.
  • Woodworth, P.L. 2019. The global distribution of the M1 ocean tide. Ocean Science, 15, 431-442, doi:10.5194/os-15-431-2019.
  • Piccioni, G., Dettmering, D., Bosch, W. and Seitz, F. 2019. TICON: TIdal CONstants based on GESLA sea-level records from globally located tide gauges. Geoscience Data Journal, doi:10.1002/gdj3.72.
  • Wilson, C., Harle, J. and Wakelin, S. 2019. Development of a regional ocean model for the Caribbean, including 3D dynamics, thermodynamics and full surface flux forcing. Southampton, National Oceanography Centre, 40pp. (National Oceanography Centre Research and Consultancy Report, 65).
  • Jevrejeva, S., Matthews, A. and Williams, J. 2019. Development of a coastal data hub for stakeholder access in the Caribbean region. Southampton, National Oceanography Centre, 27pp. (National Oceanography Centre Research and Consultancy Report, 67).
  • Vignudelli, S., Birol, F., Benveniste, J. et al. 2019. Satellite Altimetry Measurements of Sea Level in the Coastal Zone. Surveys in Geophysics, 40, 1319-1349, doi:10.1007/s10712-019-09569-1.
  • Benveniste, J. et al. 2019. Requirements for a coastal hazards observing system. Frontiers in Marine Science, in press, doi:10.3389/fmars.2019.00348.
  • IPCC, 2019. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. (H.-O. Pörtner et al. eds.).
  • Arns, A., Wahl, T., Wolff, C., Vafeidis, A.T., Haigh, I.D., Woodworth, P., Niehüser, S. and Jensen, J, 2020. Non-linear interaction modulates global extreme sea levels, coastal flood exposure, and impacts. Nature Communications, 11, 1918, doi:10.1038/s41467-020-15752-5.
  • Muis, S., Irazoqui Apecechea, M., Dullaart, J., de Lima Rego, J., Madsen, K.S., Su, J., Yan, K. and Verlaan, M., 2020. A high-resolution global dataset of extreme sea levels, tides, and storm surges, including future projections. Frontiers in Marine Science, 7:263, doi:10.3389/fmars.2020.00263.
  • Tadesse, M., Wahl, T. and Cid, A., 2020. Data-driven modeling of global storm surges. Frontiers in Marine Science, 7:260, doi:10.3389/fmars.2020.00260.
  • Hague, B.S, Murphy, B.F., Jones, D.A. and Taylor, A.J., 2020. Developing impact-based thresholds for coastal inundation from tide gauge observations. Journal of Southern Hemisphere Earth Systems Science, 69(1), 252-272, doi:10.1071/ES19024.
  • Hunter, J.R., 2020. Are tidal predictions a good guide to future extremes? – a critique of the Witness King Tides project. Ocean Science, 16, 703-714, doi:10.5194/os-16-703-2020.
  • Lambert, E., Rohmer, J., Le Cozannet, G. and van de Wal, R.S.W, 2020. Adaptation time to magnified flood hazards underestimated when derived from tide gauge records. Environmental Research Letters, 15(7), 074015, doi:10.1088/1748-9326/ab8336.
  • Ray, R.D., 2020. First global observations of third-degree ocean tides. Science Advances, 6, eabd4744.
  • Woodworth, P.L., Hunter, J.R., Marcos, M. and Hughes, C.W., 2021. Towards reliable global allowances for sea level rise. Global and Planetary Change, Vol. 203, 103522, doi:10.1016/j.gloplacha.2021.103522.
  • Vignudelli, S., Scozzari, A., Abileah, R., Gómez-Enri, J., Benveniste, J. and Cipollini, P., 2019. Water surface elevation in coastal and inland waters using satellite radar altimetry. Chapter 4 (pp. 87-127), in: Extreme Hydroclimatic Events and Multivariate Hazards in a Changing Environment, Elsevier, doi:10.1016/B978-0-12-814899-0.00004-3.
  • Núñez, P., Castanedo, S. and Medina, R., 2020. A global classification of astronomical tide asymmetry and periodicity using statistical and cluster analysis. Journal of Geophysical Research: Oceans, 125, e2020JC016143, doi:10.1029/2020JC016143.
  • Bruneau, N., Polton, J., Williams, J. and Holt, J., 2020. Estimation of global coastal sea level extremes using neural networks. Environmental Research Letters, 15, 074030.
  • Rashid, M.M., Wahl, T. and Chambers, D.P., 2021. Extreme sea level variability dominates coastal flood risk changes at decadal time scales. Environmental Research Letters, 16, 024026.
  • Tadesse, M.G. and Wahl, T., 2021. A database of global storm surge reconstructions. Scientific Data, 8:125, doi:10.1038/s41597-021-00906-x.
  • Lee, M. and Lee, J., 2021. Long-term trend analysis of extreme coastal sea levels with changepoint detection. Journal of the Royal Statistical Society, Series C, Applied Statistics, 70(2), 434-458, doi:10.1111/rssc.12466.
  • Cresswell, G.R., 2021. T. W. Fowler’s measurements of sea temperature and density from merchant ships off southern Australia in 1896. Journal of the Royal Society of Western Australia, 104:33-40.
  • Ray, R.D., Loomis, B.D. and Zlotnicki, V., 2021. The mean seasonal cycle in relative sea level from satellite altimetry and gravimetry. Journal of Geodesy, 95:80, 21pp., doi:10.1007/s00190-021-01529-1.
  • Tebaldi, C., Ranasinghe, R., Vousdoukas, M. et al., 2021. Extreme sea levels at different global warming levels. Nature Climate Change, 11, 746-751, doi:10.1038/s41558-021-01127-1.
  • Tiggeloven, T., Couasnon, A., van Straaten, C., Muis, S. and Ward, P.J., 2021. Exploring deep learning capabilities for surge predictions in coastal areas. Scientific Reports, 11, 17224, doi:10.1038/s41598-021-96674-0.

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