Estimating and reducing the uncertainty in the future behaviour of the Greenland Ice Sheet

Lead Research Organisation: University of Bristol
Department Name: Geographical Sciences

Abstract

Sea level rise (SLR) is considered to be one of the most economically and socially important consequences of global warming. The potential contribution of the ice sheets dominates uncertainties in projections of future SLR and the fourth assessment report of the IPCC (AR4) was unable to place an upper bound on the contribution of the ice sheets because of an inadequate understanding of processes controlling their future behaviour. Uncertainties in how the climate will evolve are also important. Depending on the climate model and Greenhouse Gas (GHG) scenario the contribution from changes in the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) could range between ~0 to 4 mm/yr of SLR by 2150. For reference, the AR4 estimates that the GrIS has been contributing 0.21 mm/yr between 1993-2003. Thus, the increase in mass loss (excluding any change in ice dynamics) from Greenland over the next 150 years could go up by a factor of 20 and potentially be the largest single source of SLR but, as mentioned, the uncertainty in predicting the value is large. Further, it has been suggested that the GrIS could be eliminated by a regional temperature rise of > 4.5 degs C, with a final contribution to global SLR of some 7 m. Most simulations from the AR4 exceed this temperature threshold over Greenland by 2100. What impact climate change will have on the net mass balance of the ice sheet (i.e. on both ice dynamic and surface melt effects) and what the likely contribution will be to SLR and freshwater production remain poorly constrained. The aim of this project is to tackle several key components responsible for this uncertainty relating to how the ice sheet will respond to changing climate and what the uncertainties in the future climate are due to parameter uncertainty in the models used. In addition we will incorporate our results and the SMB model into the next generation of Hadley Centre AOGCMs.

Publications

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