MCA Pilot PUI: Proxy-model comparison using carbon isotopes from annually banded marine calcifiers and ocean circulation inverse models to evaluate coastal carbon cycle processes

海洋是大气中人为碳汇的一大部分。因此，计算碳进入海洋的移动对于了解未来大气中二氧化碳的浓度是很重要的。海洋气候模型是理解控制碳循环的过程的有力工具。然而，数据估计和模拟海洋中碳同位素的海洋环流逆模型(OCIM)之间存在很大差异。该项目将使用从代理档案中获得的数据进行模型-代理数据比较，作为对模型模拟碳同位素的独立测试。这项研究将提供海洋碳酸盐碳同位素记录的第一个替代数据模型输出比较和来自OCIMs的模拟，以更好地了解北大西洋和北太平洋沿海地区的碳循环。这种比较将解决由于与季节性、气-海气体交换、代理档案年代不确定性以及不受模式限制的更广泛的环境/气候过程有关的代理档案和模式偏差而产生的偏移和时间差异。该项目将分析模型输出和代理数据之间的差异，以更好地限制碳循环过程，这对了解人为二氧化碳从大气和海洋中的去除至关重要。因此，这项工作将有助于从社会角度理解减缓正在进行的气候变化的过程。该项目将支持一名初等本科院校的职业生涯中期研究人员。在与社会相关的气候科学和数值模拟的交汇点上，该项目将通过研究经验培养本科生，并将内容纳入新的科学系的课程，从而提供对劳动力能力的投资，这些投资将延伸到项目持续时间之外。该奖项反映了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 ocean is a large sink of anthropogenic carbon from the atmosphere. Thus, calculating the movement of carbon into the oceans is important to understand future atmospheric carbon dioxide concentrations. Ocean climate models are a powerful tool to understand the processes that control carbon cycling. However, large discrepancies exist among data estimates and an ocean circulation inverse model (OCIM) that models carbon isotopes in the ocean. This project will use data obtained from proxy archives to perform a model-proxy data comparison as an independent test of the model-simulated carbon isotopes. The research would provide the first proxy data – model output comparison of carbon isotope records from marine carbonates and simulations from OCIMs to better understand carbon cycling in the coastal regions of the North Atlantic and North Pacific Oceans. The comparison would address offsets and timing differences due to proxy archive and model biases related to seasonality, air-sea gas exchange, proxy archive chronological uncertainty, and broader environmental/climatic processes not constrained in the model. This project will analyze discrepancies between model output and proxy data to better constrain the carbon cycling processes critical to understanding the removal of anthropogenic carbon dioxide from the atmosphere and into the oceans. Thus, this work will contribute to societally relevant understanding of the processes that mitigate ongoing climate change. The project will support a mid-career researcher at a primary undergraduate institution. At the interface of societally relevant climate science and numerical modeling, this project will train undergraduate students through research experiences and will incorporate content into the curriculum of the new science department, thus providing an investment in workforce capabilities that will extend beyond the project duration.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.