An improved radiostratigraphy of the Greenland Ice Sheet and its value for ice-sheet model initialization

Radar sounding across a wide range of frequencies regularly generates rich datasets for local-to-regional-scale investigation of the properties and processes that govern ice flow. However, beyond measurements of ice thickness, little of this richness is directly incorporated into continental-scale models that project the future of Earth’s ice sheets amid anthropogenic climate change. Ice sheets have long memories, and their isochronal radiostratigraphy memorializes and integrates an ice sheet’s response to past centennial-to-millennial-scale climatic and dynamic events. These memories are often cast aside in modeling studies to focus on reproducing recent observations of dramatic change, but at the expense of a more reliable initial state. Isochronal radiostratigraphy is thus an obvious target for next-generation continental-scale validation of the initial state of ice-sheet models and evaluation of their sensitivity to past climate changes. Here we describe the second version of a VHF radiostratigraphy of the Greenland Ice Sheet from 26 NASA and NSF airborne campaigns between 1993 and 2019 and its value for identifying well-tuned modern instances of the Parallel Ice Sheet Model (PISM). We incorporated several lessons learned from the generation of the first version (1993–2013), improved quality control, reviewed and augmented the entire 1993–2013 radiostratigraphy, and applied an independently developed method for predicting radiostratigraphy (ARESELP) to the previously untraced campaigns (2014–2019) to accelerate their semi-automatic tracing. The result is a substantially more robust and accessible radiostratigraphy of the Greenland Ice Sheet that highlights the tradeoff between speed and sophistication for generating continental-scale observational constraints from radar sounding. We upgraded PISM to generate and record ice age non-diffusively, and then generated an ensemble of PISM simulations initialized during the Last Glacial Period through to the present. This ensemble is compared against our new radiostratigraphy to evaluate its basin-level sensitivity to deglaciation and to identify a best-fit simulation to use as an initial state for future projections.