(Pre-) calibration of a Reduced Complexity Model of the Antarctic Contribution to Sea-level Changes

Abstract:

(Pre-) calibration of a Reduced Complexity Model of the Antarctic Contribution to Sea-level Changes

Kelsey L. Ruckert¹*, Yawen Guan², Chris E. Forest^1,3,7, Gary Shaffer ^4,5,6, and Klaus Keller^1,7,8

¹ Department of Geosciences, The Pennsylvania State University, University Park, Pennsylvania, USA

² Department of Statistics, The Pennsylvania State University, University Park, Pennsylvania, USA

³ Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania, USA

⁴ GAIA_Antarctica, University of Magallanes, Punta Arenas, Chile

⁵ Center for Advanced Studies in Arid Zones, La Serena, Chile

⁶ Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

⁷ Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, Pennsylvania, USA

⁸ Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

* Corresponding author. E-mail klr324@psu.edu

Understanding and projecting future sea-level changes poses nontrivial challenges. Sea-level changes are driven primarily by changes in the density of seawater as well as changes in the size of glaciers and ice sheets. Previous studies have demonstrated that a key source of uncertainties surrounding sea-level projections is the response of the Antarctic ice sheet to warming temperatures. Here we calibrate a previously published and relatively simple model of the Antarctic ice sheet over a hindcast period from the last interglacial period to the present. We apply and compare a range of (pre-) calibration methods, including a Bayesian approach that accounts for heteroskedasticity. We compare the model hindcasts and projections for different levels of model complexity and calibration methods. We compare the projections with the upper bounds from previous studies and find our projections have a narrower range in 2100. Furthermore we discuss the implications for the design of climate risk management strategies.