Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-7055-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-7055-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
11 Dec 2025
Data description paper |
| 11 Dec 2025
| 11 Dec 2025
Sea level reconstruction reveals improved separation of regional climate and trend patterns over the last seven decades
Shengdao Wang
CORRESPONDING AUTHOR
Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, OH, 43210, USA
Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, OH, 43210, USA
Michael Bevis
Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, OH, 43210, USA
Xiaoxing He
School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
Yu Zhang
Space Systems Analysis Inc., Columbus, OH 43220, USA
Yihang Ding
Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Chaoyang Zhang
Center for Space Research, The University of Texas at Austin, Austin, TX 78712, USA
Jean-Philippe Montillet
Institute Dom Luiz, University of Beira Interior, 6201-001 Covilhã, Portugal
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The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, a frequency-dependent noise processing strategy, and parameterization-integrating natural boundaries, aiming to enhance accuracy for monitoring mass transportation on Earth.
Fan Gao, Qiang Shen, Hansheng Wang, Tong Zhang, Liming Jiang, Yan Liu, C. K. Shum, Yan An, and Xu Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3264, https://doi.org/10.5194/egusphere-2025-3264, 2025
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Basal ice-shelf melting critically impacts Antarctic ice sheet evolution. Our testing of two melt schemes showed starkly diverging projections despite near-identical ice sheet initial states, especially for West Antarctica. By 2100, the predicted sea-level contribution differed by 57 %. Because initial setup changes hidden sub-ice properties (e.g., friction, temperature), changing ice flow. Accurately representing melt and refining setup are thus essential to reduce vital projection uncertainty.
Jean-Philippe Montillet, Xiaoxing He, Kegen Yu, and Changliang Xiong
Nonlin. Processes Geophys., 28, 121–134, https://doi.org/10.5194/npg-28-121-2021, https://doi.org/10.5194/npg-28-121-2021, 2021
Short summary
Short summary
Recently, various models have been developed, including the
fractional Brownian motion (fBm), to analyse the stochastic properties of
geodetic time series, together with the estimated geophysical signals.
The noise spectrum of these time series is generally modelled as a mixed
spectrum, with a sum of white and coloured noise. Here, we are interested
in modelling the residual time series after deterministically subtracting geophysical signals from the observations with the Lévy processes.
Cited articles
Abessolo, G. O., Birol, F., Almar, R., Léger, F., Bergsma, E., Brodie, K., and Holman, R.: Wave influence on altimetry sea level at the coast, Coastal Engineering, 180, 104275, https://doi.org/10.1016/j.coastaleng.2022.104275, 2023.
Akaike, H.: Fitting autoregressive models for prediction, Ann. Inst. Stat. Math., 21, 243–247, https://doi.org/10.1007/BF02532251, 1969.
Bâki Iz, H.: Sub and superharmonics of the lunar nodal tides and the solar radiative forcing in global sea level changes, Journal of Geodetic Science, 4, 20140016, https://doi.org/10.2478/jogs-2014-0016, 2014.
Beckley, B., Yang, X., Zelensky, N. P., Holmes, S. A., Lemoine, F. G., Ray, R. D., Mitchum, G. T., Desai, S., and Brown, S. T.: Global mean sea level trend from integrated multi-mission ocean altimeters TOPEX/Poseidon, Jason- 1, OSTM/Jason-2, Jason-3, and Sentinel-6, version 5.2, PO.DAAC, CA, USA [data set], https://doi.org/10.5067/GMSLM-TJ152, 2024.
Berge-Nguyen, M., Cazenave, A., Lombard, A., Llovel, W., Viarre, J., and Cretaux, J. F.: Reconstruction of past decades sea level using thermosteric sea level, tide gauge, satellite altimetry and ocean reanalysis data, Global and Planetary Change, 62, 1–13, https://doi.org/10.1016/j.gloplacha.2007.11.007, 2008.
Bevis, M. and Brown, A.: Trajectory models and reference frames for crustal motion geodesy, J. Geod., 88, 283–311, https://doi.org/10.1007/s00190-013-0685-5, 2014.
Bevis, M., Scherer, W., and Merrifield, M.: Technical Issues and Recommendations Related to the Installation of Continuous GPS Stations at Tide Gauges, Marine Geodesy, 25, 87–99, https://doi.org/10.1080/014904102753516750, 2002.
Bevis, M., Bedford, J., and Caccamise II, D. J.: The art and science of trajectory modelling, in: Geodetic Time Series Analysis in Earth Sciences, edited by: Montillet, J.-P. and Bos, M. S., Springer, Cham, 27 pp., https://doi.org/10.1007/978-3-030-21718-1_1, 2019.
Caccamise II, D. J.: Geodetic and Oceanographic Aspects of Absolute versus Relative Sea-Level Change, PhD thesis, Ohio State University, Columbus, OH, USA, http://rave.ohiolink.edu/etdc/view?acc_num=osu1543357751520828 (last access: 5 December 2024), 2019.
Calafat, F. M. and Gomis, D.: Reconstruction of Mediterranean sea level fields for the period 1945–2000, Global and Planetary Change, 66, 225–234, https://doi.org/10.1016/j.gloplacha.2008.12.015, 2009.
Calafat, F. M., Chambers, D. P., and Tsimplis, M. N.: On the ability of global sea level reconstructions to determine trends and variability, J. Geophys. Res. Oceans, 119, 1572–1592, https://doi.org/10.1002/2013JC009298, 2014.
Cazenave, A., Gouzenes, Y., Birol, F., Leger, F., Passaro, M., Calafat, F. M., Shaw, A., Nino, F., Legeais, J. F., Oelsmann, J., Restano, M., and Benveniste, J.: Sea level along the world's coastlines can be measured by a network of virtual altimetry stations, Commun. Earth Environ., 3, 117, https://doi.org/10.1038/s43247-022-00448-z, 2022.
Chambers, D. P., Merrifield, M. A., and Nerem, R. S.: Is there a 60-year oscillation in global mean sea level?, Geophysical Research Letters, 39, 2012GL052885, https://doi.org/10.1029/2012GL052885, 2012.
Church, J. A. and White, N. J.: A 20th century acceleration in global sea-level rise, Geophysical Research Letters, 33, 2005GL024826, https://doi.org/10.1029/2005GL024826, 2006.
Church, J. A. and White, N. J.: Sea-Level Rise from the Late 19th to the Early 21st Century, Surv. Geophys., 32, 585–602, https://doi.org/10.1007/s10712-011-9119-1, 2011.
Church, J. A., White, N. J., Coleman, R., Lambeck, K., and Mitrovica, J. X.: Estimates of the Regional Distribution of Sea Level Rise over the 1950–2000 Period, J. Climate, 17, 2609–2625, https://doi.org/10.1175/1520-0442(2004)017<2609:EOTRDO>2.0.CO;2, 2004.
Dangendorf, S., Hay, C., Calafat, F. M., Marcos, M., Piecuch, C. G., Berk, K., and Jensen, J.: Persistent acceleration in global sea-level rise since the 1960s, Nat. Clim. Chang., 9, 705–710, https://doi.org/10.1038/s41558-019-0531-8, 2019.
Dangendorf, S., Sun, Q., Wahl, T., Thompson, P., Mitrovica, J. X., and Hamlington, B.: Probabilistic reconstruction of sea-level changes and their causes since 1900, Earth Syst. Sci. Data, 16, 3471–3494, https://doi.org/10.5194/essd-16-3471-2024, 2024.
Ding, H. and Chao, B. F.: A 6-year westward rotary motion in the Earth: Detection and possible MICG coupling mechanism, Earth and Planetary Science Letters, 495, 50–55, https://doi.org/10.1016/j.epsl.2018.05.009, 2018.
Ding, H. and Jiang, W.: A newly unraveled 13.6-year oscillation from GPS displacements and its potential implications for the dynamic reference frame, Sci. China Earth Sci., 67, 3204–3212, https://doi.org/10.1007/s11430-024-1415-1, 2024.
Ding, H., Jin, T., Li, J., and Jiang, W.: The Contribution of a Newly Unraveled 64 Years Common Oscillation on the Estimate of Present-Day Global Mean Sea Level Rise, J. Geophys. Res. Solid Earth, 126, e2021JB022147, https://doi.org/10.1029/2021JB022147, 2021.
Eichstädt, S., Arendacké, B., Link, A., and Elster, C.: Evaluation of measurement uncertainty for time-dependent quantities, EPJ Web of Conferences, 77, 00003, https://doi.org/10.1051/epjconf/20147700003, 2014.
Ebisuzaki, W.: A Method to Estimate the Statistical Significance of a Correlation When the Data Are Serially Correlated, J. Climate, 10, 2147–2153, https://doi.org/10.1175/1520-0442(1997)010<2147:AMTETS>2.0.CO;2, 1997.
Feng, J., Chen, Q., Li, D., Yang, X., and Zhao, L.: The dominant modes of recent sea level variability from 1993 to 2020 in the China Seas, Global and Planetary Change, https://doi.org/10.1016/j.gloplacha.2024.104451, 2024.
Feng, W. and Zhong, M.: Global sea level variations from altimetry, GRACE and Argo data over 2005–2014, Geodesy and Geodynamics, 6, 274–279, https://doi.org/10.1016/j.geog.2015.07.001, 2015.
Foreman, M. G. G.: Manual for tidal heights analysis and prediction (Pacific Marine Science Report 77-10), Institute of Ocean Sciences, Patricia Bay, Victoria, BC, Canada, https://waves-vagues.dfo-mpo.gc.ca/library/54866.pdf (last access: 25 March 2025), 1977.
Frankcombe, L. M., McGregor, S., and England, M. H.: Robustness of the modes of Indo-Pacific sea level variability, Clim. Dynam., 45, 1281–1298, https://doi.org/10.1007/s00382-014-2377-0, 2015.
Frederikse, T., Jevrejeva, S., Riva, R. E. M., and Dangendorf, S.: A Consistent Sea-Level Reconstruction and Its Budget on Basin and Global Scales over 1958–2014, Journal of Climate, 31, 1267–1280, https://doi.org/10.1175/JCLI-D-17-0502.1, 2018.
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V. W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L., and Wu, Y.-H.: The causes of sea-level rise since 1900, Nature, 584, 393–397, https://doi.org/10.1038/s41586-020-2591-3, 2020.
Hamlington, B. D., Bellas-Manley, A., Willis, J. K., Fournier, S., Vinogradova, N., Nerem, R. S., Piecuch, C. G., Thompson, P. R., and Kopp, R.: The rate of global sea level rise doubled during the past three decades, Commun. Earth Environ., 5, 601, https://doi.org/10.1038/s43247-024-01761-5, 2024.
Hamlington, B. D., Cheon, S. H., Piecuch, C. G., Karnauskas, K. B., Thompson, P. R., Kim, K. -Y., Reager, J. T., Landerer, F. W., and Frederikse, T.: The Dominant Global Modes of Recent Internal Sea Level Variability, J. Geophys. Res. Oceans, 124, 2750–2768, https://doi.org/10.1029/2018JC014635, 2019.
Hamlington, B. D., Leben, R. R., Nerem, R. S., Han, W., and Kim, K.-Y.: Reconstructing sea level using cyclostationary empirical orthogonal functions, J. Geophys. Res., 116, C12015, https://doi.org/10.1029/2011JC007529, 2011.
Hamlington, B. D., Leben, R. R., Strassburg, M. W., Nerem, R. S., and Kim, K.-Y.: Contribution of the Pacific Decadal Oscillation to global mean sea level trends, Geophys. Res. Lett., 40, 5171–5175, https://doi.org/10.1002/grl.50950, 2013.
Hamlington, B. D., Leben, R. R., Strassburg, M. W., and Kim, K. -Y.: Cyclostationary empirical orthogonal function sea-level reconstruction, Geosci. Data J., 1, 13–19, https://doi.org/10.1002/gdj3.6, 2014.
Hamlington, B. D., Cheon, S. H., Thompson, P. R., Merrifield, M. A., Nerem, R. S., Leben, R. R., and Kim, K. -Y.: An ongoing shift in Pacific Ocean sea level, J. Geophys. Res. Oceans, 121, 5084–5097, https://doi.org/10.1002/2016JC011815, 2016.
Hammond, W. C., Blewitt, G., Kreemer, C., and Nerem, R. S.: GPS Imaging of Global Vertical Land Motion for Studies of Sea Level Rise, J. Geophys. Res. Solid Earth, 126, e2021JB022355, https://doi.org/10.1029/2021JB022355, 2021.
Han, W., Meehl, G. A., Stammer, D., Hu, A., Hamlington, B., Kenigson, J., Palanisamy, H., and Thompson, P.: Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes, Surv. Geophys., 38, 217–250, https://doi.org/10.1007/s10712-016-9386-y, 2017.
Hay, C. C., Morrow, E., Kopp, R. E., and Mitrovica, J. X.: Estimating the sources of global sea level rise with data assimilation techniques, P. Natl. Acad. Sci. USA, 110, 3692–3699, https://doi.org/10.1073/pnas.1117683109, 2013.
Hay, C. C., Morrow, E., Kopp, R. E., and Mitrovica, J. X.: Probabilistic reanalysis of twentieth-century sea-level rise, Nature, 517, 481–484, https://doi.org/10.1038/nature14093, 2015.
Holgate, S. J., Matthews, A., Woodworth, P. L., Rickards, L. J., Tamisiea, M. E., Bradshaw, E., Foden, P. R., Gordon, K. M., Jevrejeva, S., and Pugh, J.: New data systems and products at the permanent service for mean sea level, J. Coastal Res., 29, 493–504, https://doi.org/10.2112/JCOASTRES-D-12-00175.1, 2013.
Ilin, A. and Raiko, T.: Practical approaches to principal component analysis in the presence of missing values, J. Mach. Learn. Res., 11, 1957–2000, 2010.
Iz, H. B. and Shum, C. K.: Minimum record length for detecting a prospective uniform sea level acceleration at a tide gauge station, All Earth, 34, 8–15, https://doi.org/10.1080/27669645.2022.2045697, 2022.
İz, H. B. and Shum, C. K.: The ambiguous sea level rise at Brest's 212 yearlong record elucidated, Journal of Geodetic Science, 11, 95–101, https://doi.org/10.1515/jogs-2020-0124, 2021.
Iz, H. B., Shum, C. K., and Kuo, C. Y.: Sea level accelerations at globally distributed tide gauge stations during the satellite altimetry era, Journal of Geodetic Science, 8, 130–135, https://doi.org/10.1515/jogs-2018-0013, 2018.
Japan Meteorological Agency: ENSO/PDO monitoring indices, https://ds.data.jma.go.jp/tcc/tcc/products/elnino/, last access: 20 May 2024.
Jevrejeva, S., Moore, J. C., Grinsted, A., Matthews, A. P., and Spada, G.: Trends and acceleration in global and regional sea levels since 1807, Global and Planetary Change, 113, 11–22, https://doi.org/10.1016/j.gloplacha.2013.12.004, 2014.
Jwo, D.-J., Chang, W.-Y., and Wu, I.-H.: Windowing Techniques, the Welch Method for Improvement of Power Spectrum Estimation, Computers, Materials & Continua, 67, 3983–4003, https://doi.org/10.32604/cmc.2021.014752, 2021.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Kaplan, A., Kushnir, Y., and Cane, M. A.: Reduced Space Optimal Interpolation of Historical Marine Sea Level Pressure: 1854–1992, J. Climate, 13, 2987–3002, https://doi.org/10.1175/1520-0442(2000)013<2987:RSOIOH>2.0.CO;2, 2000.
Kay, S. M.: Modern spectral estimation: Theory and application, Prentice Hall, Englewood Cliffs, NJ, ISBN 013598582X, 1988.
Kim, K.-Y. and North, G. R.: EOFs of Harmonizable Cyclostationary Processes, J. Atmos. Sci., 54, 2416–2427, https://doi.org/10.1175/1520-0469(1997)054<2416:EOHCP>2.0.CO;2, 1997.
Kim, K.-Y., Hamlington, B., and Na, H.: Theoretical foundation of cyclostationary EOF analysis for geophysical and climatic variables: Concepts and examples, Earth-Science Reviews, 150, 201–218, https://doi.org/10.1016/j.earscirev.2015.06.003, 2015.
King, M. A., Keshin, M., Whitehouse, P. L., Thomas, I. D., Milne, G., and Riva, R. E. M.: Regional biases in absolute sea-level estimates from tide gauge data due to residual unmodeled vertical land movement, Geophysical Research Letters, 39, 2012GL052348, https://doi.org/10.1029/2012GL052348, 2012.
Kulp, S. A. and Strauss, B. H.: New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding, Nat. Commun., 10, 4844, https://doi.org/10.1038/s41467-019-12808-z, 2019.
Kumar, P., Hamlington, B., Cheon, S., Han, W., and Thompson, P.: 20th Century Multivariate Indian Ocean Regional Sea Level Reconstruction, J. Geophys. Res. Oceans, 125, https://doi.org/10.1029/2020JC016270, 2020.
Kuo, C. Y., Shum, C. K., Braun, A., and Mitrovica, J. X.: Vertical crustal motion determined by satellite altimetry and tide gauge data in Fennoscandia, Geophys. Res. Lett., 31, L01608, https://doi.org/10.1029/2003GL019106, 2004.
Kuo, C.-Y., Shum, C. K., Braun, A., Cheng, K.-C., and Yi, Y.: Vertical Motion Determined Using Satellite Altimetry and Tide Gauges, Terr. Atmos. Ocean. Sci., 19, 21, https://doi.org/10.3319/TAO.2008.19.1-2.21(SA), 2008.
Mantua, N. J., Hare, S. R., Zhang, Y., Wallace, J. M., and Francis, R. C.: A Pacific interdecadal climate oscillation with impacts on salmon production, B. Am. Meteorol. Soc., 78, 1069–1080, https://doi.org/10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2, 1997.
Meng, L., Zhuang, W., Zhang, W., Ditri, A., and Yan, X.-H.: Decadal Sea Level Variability in the Pacific Ocean: Origins and Climate Mode Contributions, Journal of Atmospheric and Oceanic Technology, 36, 689–698, https://doi.org/10.1175/JTECH-D-18-0159.1, 2019.
Meyssignac, B., Becker, M., Llovel, W., and Cazenave, A.: An Assessment of Two-Dimensional Past Sea Level Reconstructions Over 1950–2009 Based on Tide-Gauge Data and Different Input Sea Level Grids, Surv. Geophys., 33, 945–972, https://doi.org/10.1007/s10712-011-9171-x, 2012.
Mu, D., Yan, H., and Feng, W.: Assessment of sea level variability derived by EOF reconstruction, Geophysical Journal International, 214, 79–87, https://doi.org/10.1093/gji/ggy126, 2018.
National Research Council: Sea-level rise for the coasts of California, Oregon, and Washington: Past, present, and future, National Academies Press, Washington, D.C., 250 pp., ISBN 978-0-309-25594-3, 2012.
Nerem, R. S. and Mitchum, G. T.: Estimates of vertical crustal motion derived from differences of TOPEX/POSEIDON and tide gauge sea level measurements, Geophysical Research Letters, 29, https://doi.org/10.1029/2002GL015037, 2002.
Newman, M., Alexander, M. A., Ault, T. R., Cobb, K. M., Deser, C., Di Lorenzo, E., Mantua, N. J., Miller, A. J., Minobe, S., Nakamura, H., Schneider, N., Vimont, D. J., Phillips, A. S., Scott, J. D., and Smith, C. A.: The Pacific Decadal Oscillation, Revisited, Journal of Climate, 29, 4399–4427, https://doi.org/10.1175/JCLI-D-15-0508.1, 2016.
Nicholls, R. J., Wong, P. P., Burkett, V. R., Codignotto, J. O., Hay, J. E., McLean, R. F., Ragoonaden, S., and Woodroffe, C. D.: Coastal systems and low-lying areas, in: Climate Change 2007: Impacts, Adaptation and Vulnerability, Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J., and Hanson, C. E., Cambridge University Press, Cambridge, UK, 315–356, ISBN 9780521880107, 2007.
NOAA Physical Sciences Laboratory: Niño 3.4 SST index, https://psl.noaa.gov/data/timeseries/month/, last access: 20 May 2024.
Oelsmann, J., Passaro, M., Dettmering, D., Schwatke, C., Sánchez, L., and Seitz, F.: The zone of influence: matching sea level variability from coastal altimetry and tide gauges for vertical land motion estimation, Ocean Sci., 17, 35–57, https://doi.org/10.5194/os-17-35-2021, 2021.
Oppenheim, A. V. and Schafer, R. W.: Discrete-time signal processing, 3rd edn., Pearson, Harlow, ISBN 9780133002287, 2010.
Orfanidis, S. J.: Optimum signal processing: An introduction, 2nd edn., self-published, 748 pp., ISBN 9780979371301, 2007.
Peltier, W. R.: Global glacial isostasy and the surface of the ice-age earth: The ICE-5G (VM2) Model and GRACE, Annu. Rev. Earth Planet. Sci., 32, 111–149, https://doi.org/10.1146/annurev.earth.32.082503.144359, 2004.
Ponte, R. M.: Low-Frequency Sea Level Variability and the Inverted Barometer Effect, Journal of Atmospheric and Oceanic Technology, 23, 619–629, https://doi.org/10.1175/JTECH1864.1, 2006.
Pfeffer, J., Cazenave, A., Rosat, S., Moreira, L., Mandea, M., Dehant, V., and Coupry, B.: A 6-year cycle in the Earth system, Global and Planetary Change, 229, 104245, https://doi.org/10.1016/j.gloplacha.2023.104245, 2023.
Ray, R. D. and Douglas, B. C.: Experiments in reconstructing twentieth-century sea levels, Progress in Oceanography, 91, 496–515, https://doi.org/10.1016/j.pocean.2011.07.021, 2011.
Ray, R. D., Beckley, B. D., and Lemoine, F. G.: Vertical crustal motion derived from satellite altimetry and tide gauges, and comparisons with DORIS measurements, Advances in Space Research, 45, 1510–1522, https://doi.org/10.1016/j.asr.2010.02.020, 2010.
Ray, R. D., Merrifield, M. A., and Woodworth, P. L.: Wave setup at the Minamitorishima tide gauge, J. Oceanogr., 79, 13–26, https://doi.org/10.1007/s10872-022-00659-0, 2023.
Roweis, S. T.: EM algorithms for PCA and SPCA, in: Advances in Neural Information Processing Systems 10 (NIPS 1997), edited by: Jordan, M. I., Kearns, M. J., and Solla, S. A., MIT Press, Cambridge, MA, 626–632, ISBN 0262100762, 1998.
Santamaría-Gómez, A. and Mémin, A.: Geodetic secular velocity errors due to interannual surface loading deformation, Geophysical Journal International, 202, 763–767, https://doi.org/10.1093/gji/ggv190, 2015.
Santamaría-Gómez, A., Gravelle, M., Dangendorf, S., Marcos, M., Spada, G., and Wöppelmann, G.: Uncertainty of the 20th century sea-level rise due to vertical land motion errors, Earth and Planetary Science Letters, 473, 24–32, https://doi.org/10.1016/j.epsl.2017.05.038, 2017.
Schneider, T.: Analysis of Incomplete Climate Data: Estimation of Mean Values and Covariance Matrices and Imputation of Missing Values, J. Climate, 14, 853–871, https://doi.org/10.1175/1520-0442(2001)014<0853:AOICDE>2.0.CO;2, 2001.
Shum, C. K. and Kuo, C. Y.: Observation and geophysical causes of present-day sea-level rise, in: Climate Change and Food Security in South Asia, edited by: Lal, R., Sivakumar, M., Faiz, S., Mustafizur Rahman, A., and Islam, K., Springer, Dordrecht, https://doi.org/10.1007/978-90-481-9516-9_7, 2010.
Si, Z. and Xu, Y.: Influence of the Pacific Decadal Oscillation on regional sea level rise in the Pacific Ocean from 1993 to 2012, Chin. J. Ocean. Limnol., 32, 1414–1420, https://doi.org/10.1007/s00343-014-3363-4, 2014.
SONEL: https://www.sonel.org/-GPS-.html, last access: 12 December 2024.
SSALTO/DUACS: DT merged all satellites Global Ocean Ocean Gridded Monthly Mean of Sea Level Anomalies L4 product, AVISO+ [data set], https://www.aviso.altimetry.fr, 2022.
Strassburg, M. W., Hamlington, B. D., Leben, R. R., and Kim, K.-Y.: A comparative study of sea level reconstruction techniques using 20 years of satellite altimetry data, J. Geophys. Res. Oceans, 119, 4068–4082, https://doi.org/10.1002/2014JC009893, 2014.
Stuhne, G. R. and Peltier, W. R.: Reconciling the ICE-6G_C reconstruction of glacial chronology with ice sheet dynamics: The cases of Greenland and Antarctica, J. Geophys. Res. Earth Surface, 120, 1841–1865, https://doi.org/10.1002/2015JF003580, 2015.
Tamisiea, M. E.: Ongoing glacial isostatic contributions to observations of sea level change: Isostatic contributions to sea level change, Geophysical Journal International, 186, 1036–1044, https://doi.org/10.1111/j.1365-246X.2011.05116.x, 2011.
Trenberth, K. E.: The Definition of El Niño, B. Am. Meteorol. Soc., 78, 2771–2777, https://doi.org/10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2, 1997.
Walker, J. S., Kopp, R. E., Little, C. M., and Horton, B. P.: Timing of emergence of modern rates of sea-level rise by 1863, Nat. Commun., 13, 966, https://doi.org/10.1038/s41467-022-28564-6, 2022.
Wan, J.: Joint estimation of vertical land motion and global sea-level rise over the past six decades using satellite altimetry and tide gauge records, PhD thesis, The Ohio State University, Columbus, OH, USA, http://rave.ohiolink.edu/etdc/view?acc_num=osu1449185593 (last access: 20 March 2023), 2015.
Wang, F., Shen, Y., Chen, Q., and Geng, J.: Revisiting sea-level budget by considering all potential impact factors for global mean sea-level change estimation, Sci. Rep., 12, 10251, https://doi.org/10.1038/s41598-022-14173-2, 2022.
Wang, J., Church, J. A., Zhang, X., and Chen, X.: Improved Sea Level Reconstruction from 1900 to 2019, Journal of Climate, 37, 6453–6474, https://doi.org/10.1175/JCLI-D-23-0410.1, 2024.
Wang, S.: Modified Sea Level Reconstruction Reveals Improved Separation of Climate and Trend Patterns (v1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.15288816, 2025.
Wang, Y.-H., Magnusdottir, G., Stern, H., Tian, X., and Yu, Y.: Uncertainty Estimates of the EOF-Derived North Atlantic Oscillation, Journal of Climate, 27, 1290–1301, https://doi.org/10.1175/JCLI-D-13-00230.1, 2014.
WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present, Earth Syst. Sci. Data, 10, 1551–1590, https://doi.org/10.5194/essd-10-1551-2018, 2018.
Wöppelmann, G. and Marcos, M.: Vertical land motion as a key to understanding sea level change and variability, Reviews of Geophysics, 54, 64–92, https://doi.org/10.1002/2015RG000502, 2016.
Wöppelmann, G., Letetrel, C., Santamaria, A., Bouin, M. -N., Collilieux, X., Altamimi, Z., Williams, S. D. P., and Miguez, B. M.: Rates of sea-level change over the past century in a geocentric reference frame, Geophysical Research Letters, 36, 2009GL038720, https://doi.org/10.1029/2009GL038720, 2009.
Wöppelmann, G., Gravelle, M., Guichard, M., and Prouteau, E.: Progress report on the GNSS at tide gauge data assembly center: SONEL data holdings & tools to access the data, status report, GLOSS-GE Meeting, Busan, Republic of Korea, 11–13 April 2019, https://www.sonel.org (last access: 20 May 2024), 2019.
Yu, J. and Kim, S. T.: Three evolution patterns of Central-Pacific El Niño, Geophysical Research Letters, 37, 2010GL042810, https://doi.org/10.1029/2010GL042810, 2010.
Short summary
Sea level rise is a major consequence of climate change, affecting the well-being of humankind. We combined long-term tide gauge records and satellite data to create a new global sea level record from 1950 to 2022. Our results reveal how natural climate patterns, including El Niño, La Niña, and the Pacific Decadal Oscillation, influence rapid present-day sea level change. The data product enhances understanding of climate–sea level interactions.
Sea level rise is a major consequence of climate change, affecting the well-being of humankind....
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