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A coupled ice sheet - ocean model for calibrated prediction of the future contribution to sea level change from the Pine Island Glacier, Antarctica (CRAG)
Start date: Jul 1, 2013, End date: Jun 30, 2016 PROJECT  FINISHED 

The potential of marine ice sheets to undergo rapid irreversible retreat has been considered in the glaciological community since the 1970s. One of the world’s major marine ice sheets, the West Antarctic Ice Sheet (WAIS), contains enough ice to raise global mean sea level by approximately 5m. However, of immediate relevance to policy makers, the likely rate of WAIS contribution to sea level change on century timescales is not known.This project will couple a state of the art ice sheet model and ocean circulation model. Ice sheet models are only now reaching sufficient maturity to be applied to predictive studies of marine ice sheet behaviour, partly due to the candidate’s recent advances in modelling the grounding line (the line dividing ice grounded on bedrock from the floating part of the ice sheet). Ocean models incorporating ice shelf cavity processes are also emerging, and the candidate’s collaborators at the outgoing host are leading development in this area. Ice sheet – ocean model coupling is essential in predictive studies due to the feedback between evolving ice shelf cavity geometry/grounding line location and ice shelf cavity circulation via sub ice shelf melt rates.The model will be applied to the Pine Island Glacier (PIG), an important outlet glacier draining a portion of the WAIS, which has been studied extensively and is currently thinning at an increasing rate. The project will use new coupled model and Bayesian calibration techniques to ascertain whether the PIG has crossed a threshold for irreversible retreat and provide a probabilistic quantification of the PIG contribution to sea level change over the next two centuries.The project is novel in the ice sheet - ocean coupling (this will be the first 3D ocean circulation model fully coupled to an evolving ice sheet model) and in the use of Bayesian calibration to provide a probabilistic prediction, an approach rarely used in glaciology.
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