Synoptic Evaluation of Long-Term Antarctic Ice Sheet Model Simulations using a Continent-Wide Database of Cosmogentic-Nuclide Measurements

该项目的目的是利用记录南极冰盖过去变化的地质数据来测试冰盖变化的计算机模型。地质数据主要包括保存在现今冰盖水平之上的年代久远的冰川沉积物，其年龄从数千年到数百万年不等。这些提供了有关过去冰盖比现在大的时候冰盖的大小，厚度和变化率的信息。此外，其中一些数据来自现在的冰面以下，因此也提供了一些关于过去温暖时期的信息，当时冰盖很可能比现在小。计算机模型的主要目的是预测未来冰盖的变化，但由于冰盖大小的显著变化是缓慢的，可能会发生数百年或更长时间，确定这些模型是否准确的唯一方法是测试它们再现过去冰盖变化的能力。本项目的主要目的是进行这样的测试。研究小组将汇编相关的地质数据，在某些情况下通过确定额外矿床的年代来生成新数据，并开发方法和软件来比较数据与模型模拟。此外，该项目将（i）通过地质年代学，冰盖建模和数据科学的博士后培训，为建设和维持美国科学能力做出贡献，以及（ii）通过在线数据库和网站开发，改善公众对与冰盖变化相关的地质数据和模型模拟的访问。该项目的技术方面主要侧重于宇宙成因核素同位素测年领域，这是一种依靠宇宙射线与暴露在地球表面的岩石和矿物相互作用产生稀有稳定放射性核素的方法。由于冰盖的前进和后退导致交替的宇宙射线暴露和屏蔽底层基岩和表层沉积物，这种技术通常用于日期和重建过去的冰盖变化。首先，该项目将有助于汇编和系统整理过去三十年在南极洲收集的大量宇宙成因核素照射年龄数据。其次，它将产生额外的地球化学数据，以提高稳定的宇宙成因核素，特别是宇宙成因氖-21的测量范围和有用性，这对限制百万年时间尺度上的冰盖行为是有用的。第三，它将制定一个计算框架，将地质数据集与现有的数值模型模拟的过去几百万年南极冰盖变化进行比较，特别强调过去温暖时期的模型模拟，例如上新世中期。据推测，在此期间，南极冰盖比现在小得多。第四，在比较结果的指导下，它将生成新的模型模拟，旨在提高模型模拟与地质数据之间的一致性，并诊断模型中哪些过程或参数化受到或不受数据的良好约束。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The purpose of this project is to use geological data that record past changes in the Antarctic ice sheets to test computer models for ice sheet change. The geologic data mainly consist of dated glacial deposits that are preserved above the level of the present ice sheet, and range in age from thousands to millions of years old. These provide information about the size, thickness, and rate of change of the ice sheets during past times when the ice sheets were larger than present. In addition, some of these data are from below the present ice surface and therefore also provide some information about past warm periods when ice sheets were most likely smaller than present. The primary purpose of the computer model is to predict future ice sheet changes, but because significant changes in the size of ice sheets are slow and likely occur over hundreds of years or longer, the only way to determine whether these models are accurate is to test their ability to reproduce past ice sheet changes. The primary purpose of this project is to carry out such a test. The research team will compile relevant geologic data, in some cases generate new data by dating additional deposits, and develop methods and software to compare data to model simulations. In addition, this project will (i) contribute to building and sustaining U.S. science capacity through postdoctoral training in geochronology, ice sheet modeling, and data science, and (ii) improve public access to geologic data and model simulations relevant to ice sheet change through online database and website development. Technical aspects of this project are primarily focused on the field of cosmogenic-nuclide exposure-dating, which is a method that relies on the production of rare stable and radio-nuclides by cosmic-ray interactions with rocks and minerals exposed at the Earth's surface. Because the advance and retreat of ice sheets results in alternating cosmic-ray exposure and shielding of underlying bedrock and surficial deposits, this technique is commonly used to date and reconstruct past ice sheet changes. First, this project will contribute to compiling and systematizing a large amount of cosmogenic-nuclide exposure age data collected in Antarctica during the past three decades. Second, it will generate additional geochemical data needed to improve the extent and usefulness of measurements of stable cosmogenic nuclides, cosmogenic neon-21 in particular, that are useful for constraining ice-sheet behavior on million-year timescales. Third, it will develop a computational framework for comparison of the geologic data set with existing numerical model simulations of Antarctic ice sheet change during the past several million years, with particular emphasis on model simulations of past warm periods, for example the middle Pliocene ca. 3-3.3 million years ago, during which the Antarctic ice sheets are hypothesized to have been substantially smaller than present. Fourth, guided by the results of this comparison, it will generate new model simulations aimed at improving agreement between model simulations and geologic data, as well as diagnosing which processes or parameterizations in the models are or are not well constrained by the data.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.