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

格陵兰冰盖(Gris)已经成为当今乃至未来全球海平面上升的重要因素。当前几代冰盖模型之间的巨大分歧，阻碍了对未来一个世纪质量损失的预测。主要挑战是缺乏适当的观测约束来进行模型校准，以及过去地表气候的准确历史，这些历史可以作为冰盖模型模拟中的地表强迫边界条件。该项目通过使用恒定年代的地层层形式的观测数据来应对这些挑战，这些地层层由许多穿透冰层的雷达测量成像，作为对冰盖模型过去流动和边界条件的数据约束。所开发的方法将为严格的冰盖校准和初始化提供一种新的方法。除了针对从冰盖内部数据重建过去气候的科学应用之外，实现这一目标的基础设施将基于开放源码冰盖模型向社区公开提供。该项目将支持一位职业生涯早期的女性科学家过渡到独立的研究生涯。将状态和参数估计问题作为终端约束控制问题的解决使我们能够取得几个关键的科学进展：(I)开发与年龄层数据中包含的时间历史一致的时间演变的GRIS状态；(Ii)联合反演一组最优模式参数(即，模型校准)和与基本冰盖演变一致的时变最优地面强迫(即，重建一致的气候强迫历史)；以及(3)对全新世期间的冰盖进行真实的瞬变模拟，从而形成一种目前的状态，这种状态可以作为预测的良好平衡的初始条件，并且通过建造，预计其初始化冲击或人工模型漂移最小。支持这项拟议工作的一个关键计算要素是开发一个能够演变内部冰期结构的冰盖模型的随时间变化的伴随模型。利用开源工具OpenAD来实现这一点，并将其应用于POLY热冰盖(SICOPOLIS)模型的模拟代码中。这种对过去冰流和格陵兰冰盖边界条件的重建对于(从冰芯)再现观测到的年龄是必要的，并使我们能够以更精细的时空细节测试过去重要气候事件的发生，包括全新世气候最佳时期和小冰期。根据这一州的估计，这些事件具体如何、何时和在哪里恢复，将有助于阐明GRIS如何应对整个和区域的气候快速变化。这一裁决反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.