Sea-level projections representing the deeply uncertain contribution of the West Antarctic ice sheet

Abstract

There is a growing awareness that uncertainties surrounding future sea-level projections may be much larger than typically perceived. Recently published projections appear widely divergent and highly sensitive to non-trivial model choices. Moreover, the West Antarctic ice sheet (WAIS) may be much less stable than previous believed, enabling a rapid disintegration. Here, we present a set of probabilistic sea-level projections that approximates the deeply uncertain WAIS contributions. The projections aim to inform robust decisions by clarifying the sensitivity to non-trivial or controversial assumptions. We show that the deeply uncertain WAIS contribution can dominate other uncertainties within decades. These deep uncertainties call for the development of robust adaptive strategies. These decision-making needs, in turn, require mission-oriented basic science, for example about potential signposts and the maximum rate of WAIS-induced sea-level changes.

BRICK v0.2, a simple, accessible, and transparent model framework for climate and regional sea-level projections

“…Semi-empirical modeling (SEM) approaches trade detailed physics for a model that can efficiently project sea level using statistical, but mechanistically motivated, relationships between sea-level changes and climate conditions such as temperature and radiative forcing Jevrejeva et al, 2010;Kopp et al, 2016;Rahmstorf, 2007). Recent work has expanded upon the SEM approach to use simple models to resolve individual contributions to global sea level (Bakker et al, 2017;Mengel et al, 2016;Nauels et al, 2017).…”

“…As compared to Bakker et al (2017), BRICK v0.2 accounts for land water storage with the other components kept unchanged. There is a wide range of potential applications for such a model.…”

“…Here we describe in detail BRICK (Building blocks for Relevant Ice and Climate Knowledge, Bakker et al, 2017) v0.2, a model framework that focuses on accessibility, transparency, and flexibility while maintaining, as much as possible, the computational efficiency that makes simple models so appealing. As compared to Bakker et al (2017), BRICK v0.2 accounts for land water storage with the other components kept unchanged.…”

“…In robust decision-making approaches, it can be favorable to be underconfident as opposed to overconfident, e.g., by applying conservative estimates in the sense of being risk-averse (Herman et al, 2015). We hence include in our Bayesian approach wide, mechanistically motivated prior parameter probability distributions (Bakker et al, 2017). Yet, the flexibility of the BRICK model framework also enables the implementation of other calibration schemes.…”

“…For example, they are used for uncertainty quantification (Bakker et al, 2017;Grinsted et al, 2010;Urban et al, 2014;Urban and Keller, 2010) and complex model emulation (Applegate et al, 2012;Bakker et al, 2016;Hartin et al, 2015;Meinshausen et al, 2011a), and are incorporated into integrated assessment models (Hartin et al, 2015;Meinshausen et al, 2011a).…”