Relative sea level projections constrained by tide gauge trends

Projections of relative sea level rise are central to assess the future impacts of sea level rise, but available projections do not emerge as a continuation of the historical data. This complicates local adaptation planning, coastal impact assessments and communication to policy makers. Here, we present a spatial Bayesian model to provide local projections  emerging from past records. The model integrates tide gauges, GPS and satellite altimetry with past and future constraints on mountain glaciers, polar ice sheets, thermal expansion, ocean circulation, land water storage and glacial history. We separate natural, unforced ocean variability from the long-term signal to provide posterior estimates of sea level change and vertical land motion. The model reduces the uncertainty for local projections within this century through the inclusion of local constraints while producing global median projections and uncertainty ranges similar to the IPCC AR6. The model allows to project local relative sea level rise for any given global-mean temperature pathway and we illustrate this with projections for three IPCC AR6 WG3 pathways.