P2C2: Bayesian Detection of Holocene Abrupt Transitions in Proxy Records and Climate Model Simulations

人们缺乏对过去何时何地发生突如其来的气候事件的了解，以及气候变化如此迅速的驱动因素是什么。该项目试图确定全新世，即当前间冰期(约10.000年)期间气候突变的空间和时间成分。研究人员将结合古气候数据和模型来评估模拟快速气候变化和预测未来变化的能力。该项目将利用最近的几项发展，包括在过去十年中高分辨率全新世古气候记录的数量急剧增加，开发新的统计技术来检测古气候记录(例如，温度或降雨)的变化点并处理古气候数据的不确定性，以及利用越来越现实的驱动因素和过程进行气候模拟。工作旨在解决三个问题：(1)全新世期间突变的空间和时间模式是什么？它们是在时间和空间上有组织的，还是以更随机的方式发生？(2)产生全新世突变事件的作用力(如轨道强迫、太阳变异性、火山喷发)和气候系统非线性(如反馈、阈值)是什么？(3)耦合气候模型模拟的是全新世古气候记录中观察到的那种突变气候变化，还是模型更稳定？为了回答这些问题，研究人员建议(1)使用贝叶斯变点检测来客观地识别全新世代理记录的大量数据集中的快速变化，同时考虑到年龄、代理和方法上的不确定性，(2)将这些结果综合成一个系统和完整的时空转换观点；(3)将相同的算法应用于几个全新世气候的瞬时模拟，以检验关于外部强迫和随机内部变率在过去突发事件发生中的相对作用的假设。潜在的更广泛的影响包括更好地描述过去的突发气候事件，以及用气候模式评估它们的可预测性。该项目将生成精选的古气候数据，以支持可发现性、可访问性、互操作性和可重用性(公平)数据管理原则和联邦数据战略。该项目还将为一名博士后研究人员和一名本科生提供培训和支持。此外，本科生将通过在博尔德的实习计划参与进来，包括NOAA霍林斯计划、NOAA与少数族裔服务机构的教育伙伴计划以及UCAR大气科学重大机会计划。研究人员将为WDS-Paleo和NOAA国家环境信息中心(NCEI)主办的“旧大陆对突然气候变化的视角”网页创建新的内容，突出该项目的发现。本《古气候展望》面向普通读者，解释了古气候学数据如何提供了了解地球气候在各种时间尺度上的自然变异性所需的过去变化的长基线。这些观点还提供了到科学研究结果和数据集的各种链接。这一奖项反映了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。

There is a lack of understanding of when and where abrupt climate events occurred in the past, and what are the drivers of such rapid climate shifts. This project seeks to identify the spatial and temporal components of abrupt climate transitions during the Holocene, the current interglacial period (~10.000 years). The researchers will combine paleoclimate data and models to assess the ability to simulate rapid climate shifts and predict future changes. This project will leverage several recent developments, including a dramatic increase in the number of high-resolution Holocene paleoclimate records over the past decade, the development of new statistical techniques to detect changepoints in paleoclimate records (e.g., temperature or rainfall) and handle uncertainties of the paleoclimate data, and the availability of climate simulations with increasingly realistic drivers and processes.The work aims to address three questions: (1) What is the spatial and temporal pattern of abrupt changes during the Holocene? Are they organized in time and space, or do they occur more stochastically? (2) What are the forcings (e.g., orbital forcing, solar variability, volcanic eruptions) and climate system nonlinearities (e.g., feedbacks, thresholds) that produce Holocene abrupt events? (3) Do coupled climate models simulate abrupt climate changes of the types observed in the Holocene paleoclimate record, or are models more stable?To answer these question, researchers suggest to (1) use Bayesian changepoint detection to objectively identify rapid shifts in a large data set of Holocene proxy records while accounting for age, proxy, and methodological uncertainties, (2) aggregate these results into a systematic and integrated view of transitions in time and in space, (3) apply the same algorithm to several transient simulations of Holocene climate in order to test hypotheses about the relative roles of external forcing and stochastic internal variability in generating past abrupt events.The potential Broader Impacts include a better characterization of abrupt climate events in the past, and an evaluation of their predictability with climate models. This project will generate curated paleoclimate data that will support the Findability, Accessibility, Interoperability, and Reusability (Fair) data management principles and federal data strategy. The project will also provide training and support for one post-doctoral research and an undergraduate student. Additionally, undergraduate students will be involved through internship programs in Boulder, including the NOAA Hollings Program, the NOAA Educational Partnership Program with Minority Serving Institutions, and the UCAR Significant Opportunities in Atmospheric Science program. The researchers will create new content for the “Paleo Perspective on Abrupt Climate Change” webpage hosted by the WDS-Paleo and NOAA’s National Centers for Environmental Information (NCEI), highlighting the findings from the project. This Paleo Perspectives are aimed at a general audience and explain how paleoclimatology data provide a long baseline of past change needed to understand the natural variability of the Earth’s climate over a variety of timescales. The perspectives also provide a variety of links to scientific research results and datasets.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.