Investigating uncertainty in the simulation of the Antarctic ice sheet during the mid‐Piacenzian

Abstract

The mid‐Piacenzian (~3 Ma) represents the most recent warm period in Earth's history on a geological time scale; it is characterized by a significant rise of global sea level. The simulation of the size and location of the ice sheets and the investigation of the uncertainty in the simulations are potentially helpful for constraining reconstructed sea level changes. In this study, we focus on the behavior of the Antarctic ice sheet (AIS) in the mid‐Piacenzian. We investigate the influence of topography correction, model parameters, climate forcings, and model resolution on the modeled AIS and explore the isolated role of atmospheric and oceanic forcings. Forced by the simulated climate changes with the Norwegian Earth System Model, the Parallel Ice Sheet Model (15 km × 15 km) produces a nearly collapsed West AIS (WAIS) in the mid‐Piacenzian, with no significant retreat of the East AIS (EAIS). The role of increased air temperature plays a key role in the mass loss of the mid‐Piacenzian AIS, while its role is comparable to the role of ocean warming on the melting of the WAIS. In terms of the range of sea level changes, the largest source of uncertainty in the modeled AIS is derived from ice sheet model parameters and climate forcings. Although the employed model parameters, topography correction factors, and model resolution affect the simulated AIS in the mid‐Piacenzian, large‐scale deglaciation of the EAIS in our sensitivity experiments may only be possible with additional warming.

Antarctic climate and ice-sheet configuration during the early Pliocene interglacial at 4.23 Ma

“…Because there are considerable uncertainties in both the modelled and proxy-inferred temperatures, we defined an envelope of air and ocean temperatures and ran a small ensemble of ice-sheet simulations to capture the range of possible responses. We find that, under the applied climate conditions, the Antarctic ice sheet contributed 8.6 ± 2.8 m to global mean sea level in the early Pliocene, consistent with some recent studies of the midPliocene Yan et al, 2016) but higher than DeConto (2009), de Boer et al (2015) and lower than Dolan et al (2011), DeConto and.…”

“…Through carefully guided parameter iteration our procedure results in a spun-up, thermally and dynamically equilibrated ice-sheet simulation that is the best fit to observational constraints that is possible by tuning available model parameters Aitken et al, 2016). Thus although parameter uncertainty can be a large source of error under certain circumstances (see Yan et al, 2016), we argue that our approach significantly reduces this uncertainty prior to our undertaking the prognostic experimentation. All experiments start from the same spun-up present-day ice-sheet simulation.…”

Transient Variability of the Miocene Antarctic Ice Sheet Smaller Than Equilibrium Differences

“…Second, earlier modeling studies have used different ways to correct precipitation for surface height changes (e.g., Charbit et al, 2002;Gasson et al, 2014;Kirchner et al, 2011;Quiquet et al, 2012;Yamagishi et al, 2005;Yan et al, 2016). We refrain from using a precipitation lapse rate correction in our reference experiments.…”

Instability of Northeast Siberian ice sheet during glacials

“…PDD_ice, PDD_snow and SAT_stdand two important parameters for ice dynamics -ENF_SIA (the SIA enhancement factor) and ENF_SSA (the SSA enhancement factor). These selected parameters are prevalent in other modelling studies to test the sensitivity of ice sheets (e.g., Stone et al, 2010;Yan et al, 2016). Larger values of these five parameters lead to smaller ice sheet extents (due to enhanced surface melting and ice discharge), and vice versa.…”

“…PISM is a three-dimensional, thermodynamically coupled continental-scale ice sheet model (Martin et al, 2011;Winkelmann et al, 2011), widely used in ice sheet modelling (e.g., Yan et al, 2016;Bakker et al, 2017). It is based on the shallow ice approximation (SIA) and the shallow shelf approximation (SSA).…”