Linking terrestrial and marine carbon cycling across the Paleocene-Eocene Thermal Maximum via intermediate complexity Earth system modeling

古新世-始新世极热期（PETM）是大约5600万年前的一次全球变暖事件。PETM是由温室气体（包括二氧化碳和/或甲烷）释放到大气和海洋引起的。地球系统模型已被用于约束始新世纪碳排放的幅度、时间和影响。然而，碳循环反馈对整个始新世纪环境变化严重程度的贡献尚不清楚。一个关键的空白是陆地碳循环如何响应始新世新世全球变化。这个项目将增加陆地碳循环的表示到一个中等复杂的地球系统模型。该模型将模拟二氧化碳和甲烷在植被、土壤、大气和海洋之间的循环。这项研究将对地球碳循环对碳释放和全球变暖的敏感性提出新的限制。此外，该项目将支持河滨社区学院本科生在加州大学河滨分校的研究经历。这些实习是加州大学河滨分校地球科学发展项目的基石。该项目针对社区大学和四年制课程之间的关键节点，目标是培养地球科学专业的多样化本科生。碳循环反馈是未来气候变化预测中不确定性的一个关键来源。对过去的全球变暖事件的研究，如新千年新世热，有可能为这些反馈在温暖的地球上的运作提供至关重要的见解。通过将陆地碳循环的表示添加到古新世晚期配置的中等复杂性地球系统模型中，所提出的研究将允许评估潜在碳循环反馈对高大气CO2和高全球温度的时间依赖性响应。此外，拟议的研究将用陆地甲烷产生和氧化的模拟表示来更新目前海洋和大气甲烷循环的表示。这个更新的模型，cGENIE-ENTS，将用于评估多个提议的PETM碳排放情景，包括将模型输出与可用的代理数据集进行比较。cGENIE-ENTS模型的计算效率将允许在整个~200 kyr的PETM持续时间内运行实验，从而不仅评估事件开始时陆地碳循环反馈的潜力，而且还评估它们在确定地球系统恢复时间尺度方面的潜在作用。在模型整合过程中，所有模型组件将被耦合，为陆地和海洋碳循环随时间的响应产生一致的输出。新的PETM模拟将提供对PETM碳排放的修正估计，并提供对陆地生物圈反馈行为（正负反馈）的约束。该奖项反映了美国国家科学基金会的法定使命，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 Paleocene-Eocene Thermal Maximum (PETM) was a global warming event approximately 56 million years ago. The PETM was caused by the release of greenhouse gases (including carbon dioxide and/or methane) to the atmosphere and oceans. Earth system models have been employed to constrain the magnitude, timing, and impacts of PETM carbon emissions. However, the contribution of carbon cycle feedbacks to the severity of environmental changes across the PETM remains unclear. One key gap is how the terrestrial carbon cycle responded to PETM global change. This project will add a representation of the terrestrial carbon cycle to an intermediate complexity Earth system model. That model will simulate the cycling of carbon dioxide and methane between vegetation, soils, the atmosphere, and the oceans. This study will place new constraints on the sensitivity of Earth’s carbon cycle to carbon release and global warming. In addition, this project will support research experiences at UC Riverside for undergraduate students from Riverside Community College. These internships are a cornerstone of UC Riverside’s Geoscience Development program. That program targets the critical juncture between community college and 4-year programs with the goal of building a diverse population of undergraduates in the geosciences. Carbon cycle feedbacks are a key source of uncertainty in future climate change projections. Study of past global warming episodes, like the PETM, has the potential to provide crucial insight into the operation of these feedbacks on a warm Earth. By adding a representation of the terrestrial carbon cycle to an intermediate complexity Earth system model configured for the late Paleocene, the proposed research will allow evaluation of the time-dependent response of potential carbon cycle feedbacks in response to higher atmospheric CO2 and higher global temperature. In addition, the proposed research will update a current representation of ocean and atmosphere methane cycling with a modeled representation of the terrestrial production and oxidation of methane. This updated model, cGENIE-ENTS, will be used to evaluate multiple proposed PETM carbon emissions scenarios, including comparison of model output against available proxy datasets. The computational efficiency of the cGENIE-ENTS model will allow experiments to be run for the entire ~200 kyr PETM duration and thus evaluate not only the potential for terrestrial carbon cycle feedbacks during the onset of the event, but also their potential role in determining the timescale of Earth system recovery. All model components will be coupled during model integration, producing consistent output for the response of both the terrestrial and marine carbon cycle through time. New PETM simulations will provide revised estimates for PETM carbon emissions and provide constraints on the feedback behavior (both positive and negative) of the terrestrial biosphere.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.