Articles | Volume 18, issue 4
https://doi.org/10.5194/os-18-1093-2022
https://doi.org/10.5194/os-18-1093-2022
Research article
 | 
27 Jul 2022
Research article |  | 27 Jul 2022

Attributing decadal climate variability in coastal sea-level trends

Sam Royston, Rory J. Bingham, and Jonathan L. Bamber

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Cited articles

Adloff, F., Jordà, G., Somot, S., Sevault, F., Arsouze, T., Meyssignac, B., Li, L., and Serge, P.: Improving sea level simulation in Mediterranean regional climate models, Clim. Dynam., 51, 1167–1178, https://doi.org/10.1007/s00382-017-3842-3, 2018. a
Becker, M., Karpytchev, M., Marcos, M., Jevrejeva, S., and Lennartz-Sassinek, S.: Do climate models reproduce complexity of observed sea level changes?, Geophys. Res. Lett., 43, 5176–5184, https://doi.org/10.1002/2016GL068971, 2016. a
Bingham, R. J. and Hughes, C. W.: Local diagnostics to estimate density-induced sea level variations over topography and along coastlines, J. Geophys. Res.-Ocean., 117, C01013, https://doi.org/10.1029/2011JC007276, 2012. a
Bos, M. S., Fernandes, R. M. S., Williams, S. D. P., and Bastos, L.: Fast error analysis of continuous GNSS observations with missing data, J. Geodesy, 87, 351–360, https://doi.org/10.1007/s00190-012-0605-0, 2013. a
Carson, M., Köhl, A., and Stammer, D.: The Impact of Regional Multidecadal and Century-Scale Internal Climate Variability on Sea Level Trends in CMIP5 Models, J. Clim., 28, 853–861, https://doi.org/10.1175/JCLI-D-14-00359.1, 2015. a, b
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Short summary
Decadal sea-level variability masks longer-term changes and increases uncertainty in observed trend and acceleration estimates. We use numerical ocean models to determine the magnitude of decadal variability we might expect in sea-level trends at coastal locations around the world, resulting from natural, internal variability. A proportion of that variability can be replicated from known climate modes, giving a range to add to short- to mid-term projections of regional sea-level trends.