Abstract. Understanding future impacts of sea-level rise at the local level is important
for mitigating its effects. In
particular, quantifying the range of sea-level rise outcomes in a probabilistic way enables coastal planners to
better adapt strategies, depending on cost, timing and risk tolerance. For a time horizon of 100 years,
frameworks have been developed that provide such projections by relying on sea-level fingerprints where
contributions from different processes are sampled at each individual time step and summed up to create
probability distributions of sea-level rise for each desired location. While advantageous, this method does not
readily allow for including new physics developed in forward models of each component. For example, couplings
and feedbacks between ice sheets, ocean circulation and solid-Earth uplift cannot easily be represented in
such frameworks. Indeed, the main impediment to inclusion of more forward model physics in probabilistic
sea-level frameworks is the availability of dynamically computed sea-level fingerprints that can be directly
linked to local mass changes. Here, we demonstrate such an approach within the Ice-sheet and Sea-level
System Model (ISSM), where we develop a probabilistic framework that can readily be coupled to forward process models
such as those for ice sheets, glacial isostatic adjustment, hydrology and ocean circulation, among others.
Through large-scale uncertainty quantification, we demonstrate how this approach enables inclusion of
incremental improvements in all forward models and provides fidelity to time-correlated processes. The
projection system may readily process input and output quantities that are geodetically consistent with space
and terrestrial measurement systems. The approach can also account for numerous improvements in our
understanding of sea-level processes.
Ice Sheets and Sea-Level Rise in Earth System Models
