Abstract
<p>At the Last Glacial Maximum, the Eurasian Ice Sheet (EIS) was one of the largest ice masses, reaching an area of 5.5 Mkm<sup>2</sup> at its maximum. Recent advances in numerical ice sheet modelling hold significant promise for improving our understanding of ice sheet dynamics, but remain limited by the significant uncertainty as to the appropriate values for the various model input parameters. The EIS left behind a rich library of observational evidence, in the form of glacial landforms and sediments. Integrating this evidence with numerical ice sheet models allows inference on these key model parameters, leading to a better understanding of the behaviour of the EIS and a framework for advancing numerical ice sheet models. To quantify how successfully a particular model run matches the available data, model-data comparison tools are required. Here, we model the EIS using the Parallel Ice Sheet Model (PISM), a hybrid shallow-ice shallow shelf ice sheet model. We perform sensitivity analyses to reveal the most important parameters controlling the evolution of our modelled EIS. Results from this analysis allow us to reduce the parameter space required for a future ensemble experiment. This ensemble experiment will utilise novel model-data comparison tools which compare ice-free timings to geochronological evidence and modelled flow directions with drumlins. Unlike previous model-data comparison routines, our tools provide a more nuanced, and probabilistic, assessment of fit than a simple pass-fail. This offers significant benefits for future parameter selection.</p>
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