How much of the decadal, coastal sea level variability can we describe by climate modes?

It is well known that key climatic variability like the El Niño Southern Oscillation and Pacific Decadal Oscillation dominate steric sea-level variability in the Pacific Ocean and that this variability influences global- and regional-mean sea-level time series. Reducing the known internal variability from these time series reduces trend errors and can elucidate other factors including anthropogenic influence and sea-level acceleration, as has been demonstrated for the open ocean. Here we discuss the influence of key climate modes on coastal, decadal sea-level variability. For coastal stakeholders and managers it is important to understand the decadal-scale and local changes in the rate of sea-level rise in the context of internal variability in order to inform management decisions in the short- to medium-term. We use a 53-year run of a high-resolution NEMO ocean model run, forced by the DRAKKAR reanalysis atmospheric data set and with the global-mean sea level at each timestep removed, to investigate modes of decadal sea-level variability at the coast, in different basins and from different sea-level components. At more than 45% of Pacific Ocean coastal locations, greater than 50% of the decadal sea-level change can be explained by a regression of the leading principal component mode with key climate indices; ENSO in the Pacific Ocean. In different ocean basins, 18.5% to 61.0% of coastal locations have more than 33% of decadal sea-level variance explained by our climate index reconstructions. These areas include coastal regions lacking long-duration or good quality tide gauges for long-term observations such as the North-West Africa coastline. Because of the shallow depth of continental shelves, steric sea-level change propagates onto the shelf as a manometric (mass) sea-level signal. We use a set of tide gauge locations to demonstrate the internal, decadal sea-level change observed at many coasts has a substantial contribution from local, manometric signal that is driven by climate variability.