In the context of future climate change, understanding the nature and behaviour of ice sheets during warm intervals in Earth history is of fundamental importance. The late Pliocene warm period (also known as the PRISM interval: 3.264 to 3.025 million years before present) can serve as a potential analogue for projected future climates. Although Pliocene ice locations and extents are still poorly constrained, a significant contribution to sea-level rise should be expected from both the Greenland ice sheet and the West and East Antarctic ice sheets based on palaeo sea-level reconstructions. Here, we present results from simulations of the Antarctic ice sheet by means of an international Pliocene Ice Sheet Modeling Intercomparison Project (PLISMIP-ANT). For the experiments, ice-sheet models including the shallow ice and shelf approximations have been used to simulate the complete Antarctic domain (including grounded and floating ice). We compare the performance of six existing numerical ice-sheet models in simulating modern control and Pliocene ice sheets by a suite of five sensitivity experiments. We include an overview of the different ice-sheet models used and how specific model configurations influence the resulting Pliocene Antarctic ice sheet. The six ice-sheet models simulate a comparable present-day ice sheet, considering the models are set up with their own parameter settings. For the Pliocene, the results demonstrate the difficulty of all six models used here to simulate a significant retreat or re-advance of the East Antarctic ice grounding line, which is thought to have happened during the Pliocene for the Wilkes and Aurora basins. The specific sea-level contribution of the Antarctic ice sheet at this point cannot be conclusively determined, whereas improved grounding line physics could be essential for a correct representation of the migration of the grounding-line of the Antarctic ice sheet during the Pliocene.
Helmholtz Research Programs > PACES II (2014-2018) > TOPIC 3: The earth system from a polar perspective > WP 3.3: From process understanding to enabling climate prediction