Abstract
Abstract. We apply a new parameterisation of the Greenland ice sheet (GrIS) feedback between surface mass balance (SMB: the sum of surface accumulation and surface ablation) and surface elevation in the MAR regional climate model (Edwards et al., 2014) to projections of future climate change using five ice sheet models (ISMs). The MAR (Modèle Atmosphérique Régional: Fettweis, 2007) climate projections are for 2000–2199, forced by the ECHAM5 and HadCM3 global climate models (GCMs) under the SRES A1B emissions scenario. The additional sea level contribution due to the SMB–elevation feedback averaged over five ISM projections for ECHAM5 and three for HadCM3 is 4.3% (best estimate; 95% credibility interval 1.8–6.9%) at 2100, and 9.6% (best estimate; 95% credibility interval 3.6–16.0%) at 2200. In all results the elevation feedback is significantly positive, amplifying the GrIS sea level contribution relative to the MAR projections in which the ice sheet topography is fixed: the lower bounds of our 95% credibility intervals (CIs) for sea level contributions are larger than the "no feedback" case for all ISMs and GCMs. Our method is novel in sea level projections because we propagate three types of modelling uncertainty – GCM and ISM structural uncertainties, and elevation feedback parameterisation uncertainty – along the causal chain, from SRES scenario to sea level, within a coherent experimental design and statistical framework. The relative contributions to uncertainty depend on the timescale of interest. At 2100, the GCM uncertainty is largest, but by 2200 both the ISM and parameterisation uncertainties are larger. We also perform a perturbed parameter ensemble with one ISM to estimate the shape of the projected sea level probability distribution; our results indicate that the probability density is slightly skewed towards higher sea level contributions.
Highlights
The Greenland ice sheet (GrIS) response to climate change has two parts: surface mass balance (SMB), which is the sum of surface accumulation and surface ablation; and dynamic, the changes in ice flow and discharge from the ice sheet
We perform a perturbed parameter ensemble with one ice sheet models (ISMs) to estimate the shape of the projected sea level probability distribution; our results indicate that the probability density is slightly skewed towards higher sea level contributions
The only way, to incorporate physical modelling of ice flow, SMB processes, and the SMB–elevation feedback while exploring model uncertainties is with a parameterisation such as the one we present in a companion paper (Edwards et al, 2014), where we characterise the SMB response to elevation in MAR using a suite of simulations in which the MAR GrIS surface height is altered
Summary
The Greenland ice sheet (GrIS) response to climate change has two parts: surface mass balance (SMB), which is the sum of surface accumulation and surface ablation (broadly speaking, the balance of snowfall versus meltwater runoff); and dynamic, the changes in ice flow and discharge from the ice sheet. The dynamic response is simulated with ice sheet models (ISMs), which solve the Stokes equations in complete or approximate form. SMB can be simulated with sophisticated, physically based energy balance schemes in regional climate models (RCMs) such as MAR (Modèle Atmosphérique Régional: Fettweis, 2007) and RACMO2/GR An alternative to using SMB from an RCM is to simulate it within the ISM, so that the evolving ice sheet topography can dynamically alter the SMB. PDD models incorporate the temperature aspect of the SMB–elevation feedback through a lapse rate correction, but not the precipitation aspect (except, in some cases, through a scaling factor for temperature), and represent SMB much more than RCMs such as MAR and RACMO2/GR (Edwards et al, 2014)
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