- National Oceanography Centre, Liverpool, United Kingdom of Great Britain – England, Scotland, Wales (cwi@noc.ac.uk)
In some places and over some time horizons, coastal sea-level is highly predictable. For example, there are locations where the seasonal cycle dominates and the monthly-mean sea- level is predictable for many years ahead. However, in other places, we know that there are frequent storm surges, that AMOC changes are linked to coastal sea-level, that mass anomalies propagate around the continental shelf slope boundary and can affect remote changes in coastal sea level, but also that there is a manifestation of internal or intrinsic, nonlinear processes which have a chaotic signature. From place to place, globally, there is a need to optimally predict coastal sea-level for societal planning and adaptation, to mitigate the effects of climate change and sea-level rise. However, on the regional and local scales, there are still many gaps, both in terms of observation and modelling of coastal sea-level on timescales relevant to people’s lives and wellbeing.
Using an ensemble modelling approach, one can use the ensemble mean and ensemble variance to estimate a potentially predictable,”forced” component of the system and a potentially unpredictable, ”unforced” component. In terms of sea-level, the unforced, chaotic intrinsic variability (CIV) component can, in some locations, dominate the forced component, even out to decadal timescales. This is known to be a major source of uncertainty in sea-level trends, relevant to IPCC projections, but analogously so for other temporal components on seasonal to decadal timescales too.
This study:
- a) verifies where and over which timescales of variability the OCCIPUT, eORCA025, 50- member initial condition ensemble simulation captures coastal sea-level from the GESLA3 tide gauge dataset.
- b) generates maps of the potential predictability of coastal sea-level.
- c) explores predictive suitability of statistical models versus GCMs.
- d) suggests relevant processes behind potential predictability characteristics.
How to cite: Wilson, C. and Williams, S. D. P.: Where, why, and over which timescales is coastal sea-level potentially predictable?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19468, https://doi.org/10.5194/egusphere-egu25-19468, 2025.
