A novel approach to constraining ice sheet models with glacial geomorphology

The ice sheets in Greenland and Antarctica hold enough water to raise global sea level by ~65 m, and are currently losing mass at an accelerating rate. Predictions of future mass loss are difficult to make, meaning that the contribution of ice sheets is a large source of uncertainty for estimates of future sea level rise. The numerical models which make these predictions need observations of ice sheet behaviour for validation and improvement, but the record of extant ice sheets is short.

A longer record of ice sheet behaviour can be obtained by studying the regions occupied by ice sheets during the last glacial period (~120,000 to ~10,000 years ago). The ice sheets which existed during this time left behind abundant evidence for their dynamic behaviour in the form of glacial landforms. In fields such as weather forecasting, model improvement has been achieved by hindcasting – the act of simulating past conditions and comparing them to historical data. However, simulations of palaeo-ice sheets rarely utilise the glacial landform record to its full extent. This project is a deliberate attempt to bring together the rather disparate disciplines of ice sheet modelling and glacial geomorphology to improve hindcasting procedures. With this motivation, my aim is to develop and apply tools for validating ice sheet models with glacial geomorphology. During the last glacial, the Greenland and Antarctic ice sheets were larger and much of North America, Northwest Europe and Patagonia was glaciated. Information regarding the behaviour of these major ice sheets is currently disparately stored. I will collate information regarding the ice sheets that covered these five regions into a single standardised database. From this, I will produce the first global scale empirical reconstruction of ice sheet extent and behaviour during the last glacial. I will also use a state of the art ice sheet model to simulate the behaviour of these ice sheets. The ice sheets will be simulated hundreds of times, each simulation with a separate set of input values, to capture the full range of likely ice configurations given the current limitations of our knowledge regarding how ice sheets flow and past climate conditions. To evaluate my model simulations, I will develop a new set of tools which will quantify how well the model predicts the properties of palaeo-ice sheets inferred from the dataset of glacial geomorphology. To filter out extremely unrealistic model simulations, I will first compare model output to my reconstructed ice sheet extent. An overall score of model performance will then be calculated from the ability to reproduce the timing, flow direction, changes in flow pattern, margin position, erosive capabilities and basal pressure gradients that are recorded by glacial geomorphology. I will then combine the simulations which best conform to the geomorphological data to produce a high resolution simulation of the behaviour of the major ice sheets which existed during the last glacial cycle. The simulated ice sheets will serve as important analogues for existing ice sheets, demonstrating how controls on ice sheet behaviour such as topography, sea level and climate conditioned these ice sheets to retreat, and how their changing geometries contributed to past rapid sea level rise, such as meltwater pulses and major iceberg discharge events. My model-data comparison procedure will also identify regions where the model struggles to replicate the palaeo-ice sheet behaviour. This will highlight deficiencies in the model, providing targets for model development. Furthermore, models of the future Antarctic and Greenland ice sheets rely upon accurately simulating their past extent and behaviour. The procedures and model experiments I conduct will improve how ice sheet models adhere to this history. Therefore, my project will bring about a step-change in how ice sheet models are tested and calibrated and offer a new framework for other researchers to utilise.

Grant reference
Natural Environment Research Council
Total awarded
£483,315 GBP
Start date
30 Sep 2018
4 years 11 months 29 days
End date
29 Sep 2023