Eos: Quit Worrying About Uncertainty in Sea Level Projections
A new article in Eos provides an excellent discuss on how to understand uncertainty in the context of modeling earth systems. While the C1W project won’t directly incorporate sea-level projections and ice-sheet modelling (the focus of this article), the underlying concepts of uncertainty, confidence and model skill are certainly relevant to the integrated hydrologic forecasting central to C1W.
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“Large discrepancies among model projections of long-term sea level rise have spawned calls among the scientific community for scientists to work on reducing uncertainty. However, focusing on uncertainty is a trap we must avoid. Instead, we should focus on the adaptation decisions we can already make on the basis of current models and communicating and building confidence in models for longer-term decisions.
A common method for estimating uncertainty used by climate and ice sheet modelers is to examine the spread in sea level rise projections associated with a suite of different ice sheet models driven by the same input climate forcing. [...] Another way to estimate uncertainty is to explore the range of simulated model outcomes associated with different parameters or parameterizations. The challenge here is that parameterizations are often tuned to represent physical processes as they have been observed in modern times.
So how do we know when a model is complex enough in the physics it includes that we can rely on its projections of the future under conditions very different from today’s? Answering this question comes down to two related concepts: model confidence and model skill.
Confidence reflects an assessment (qualitative or quantitative) of whether we believe that the physics and hypotheses underpinning models are fundamentally correct. Beyond being correct, model hypotheses must be complete enough that the models still produce accurate outcomes even when pushed outside the set of conditions, or regime, for which they have been calibrated. For example, we must be able to predict reliably when and how quickly ice breaks and crumbles before we can confidently predict the role of marine ice cliff instability in future sea level rise. Building confidence in models thus requires using them to make—and then test—predictions. Model skill is a measure of how accurately models have predicted past changes. Higher model skill results in greater confidence, but boosting model skill is no easy feat.”