Publication: Modeling the Greenland englacial stratigraphy
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2021-09-28
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Copernicus Gesellschaft MBH
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Abstract
Radar reflections from the interior of the Greenland ice sheet contain a comprehensive archive of past accumulation rates, ice dynamics, and basal melting. Combining these data with dynamic ice sheet models may greatly aid model calibration, improve past and future sea level estimates, and enable insights into past ice sheet dynamics that neither models nor data could achieve alone. Unfortunately, simulating the continental-scale ice sheet stratigraphy represents a major challenge for current ice sheet models. In this study, we present the first three-dimensional ice sheet model that explicitly simulates the Greenland englacial stratigraphy. Individual layers of accumulation are represented on a grid whose vertical axis is time so that they do not exchange mass with each other as the flow of ice deforms them. This isochronal advection scheme does not influence the ice dynamics and only requires modest input data from a host thermomechanical ice sheet model, making it easy to transfer to a range of models. Using an ensemble of simulations, we show that direct comparison with the dated radiostratigraphy data yields notably more accurate results than calibrating simulations based on total ice thickness. We show that the isochronal scheme produces a more reliable simulation of the englacial age profile than traditional age tracers. The interpretation of ice dynamics at different times is possible but limited by uncertainties in the upper and lower boundary conditions, namely temporal variations in surface mass balance and basal friction.
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© Author(s) 2021. Andreas Born acknowledges support from the Trond Mohn Foundation. We thank Nicholas Holschuh and an anonymous reviewer for their constructive suggestions. This research has been supported by the Trond Mohn Foundation (Modeling Englacial Layers and Tracers in Ice Sheets), the Ramón y Cajal Programme of the Spanish Ministry for Science, Innovation and Universities (grant no. RYC-2016- 20587), and the Spanish Ministry of Science and Innovation project ICEAGE (grant no. PID2019-110714RA-I00).