Paleochronometry as a control problem for recovering holocene climate variations over the Greenland Ice Sheet

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The Greenland ice sheet (GrIS) has emerged as a significant contributor to present-day, and possibly future global sea level rise. Predictions of mass loss over the coming century have been hampered by large discord between current-generation ice sheet models. Major challenges are the lack of suitable observational constraints for model calibration and accurate histories of past surface climates that may serve as surface forcing boundary conditions in ice sheet model simulations. This project addresses these challenges through the use of observational data in the form of stratigraphic horizons of constant age that have been imaged by numerous ice-penetrating radar surveys, which serve as a data-constraints on the past flow and boundary conditions of an ice sheet model. The method developed will provide a novel approach for rigorous ice sheet calibration and initialization. Beyond the scientific application that is targeted at past climate reconstruction from ice sheet internal data, the infrastructure to enable this will be publicly available to the community, being based on the open-source ice sheet model. The project will support the transition of a female early-career scientist into an independent research career.Solving the state and parameter estimation problem as a terminal constraint control problem enables us to make several key scientific advances: (i) develop a time-evolving GrIS state that is consistent with the time history encapsulated in the age layer data; (ii) jointly invert for a set of optimal model parameters (i.e., model calibration) and time-varying optimal surface forcings that are consistent with the underlying ice sheet evolution (i.e., reconstruction of a consistent climate forcing history); and (iii) develop a realistic transient simulation of the ice sheet over the Holocene period, leading into a present state that may serve as well-balanced initial condition for prediction, and for which initialization shocks or artificial model drift are expected to be minimal, by construction. A key computational ingredient that enables the proposed work is the development of a time-dependent adjoint model of an ice sheet model that is able to evolve internal ice age structures. We propose to accomplish this by means of algorithmic differentiation (AD) with the open-source tool OpenAD, applied to the SImulation COde for POLythermal Ice Sheets (SICOPOLIS) model. This reconstruction of past ice flow and the boundary conditions of the Greenland Ice Sheet is necessary to reproduce the observed ages (from ice cores) and also enables us to test with finer spatio-temporal detail the onset of important past climatic events, including the Holocene Climatic Optimum and the Little Ice Age. Exactly how, when, and where these events may be recovered by this state estimate will shed light on how the GrIS responds to rapid changes in climate, both in its entirety and regionally.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.