Collaborative Research: P2C2--Fingerprinting Forced and Unforced Variability in Holocene Paleoclimate Record

合作研究：P2C2——全新世古气候记录中受迫和非受迫变异的指纹识别

• 批准号: 2102936
• 负责人: Cristian Proistosescu
• 金额: $ 30.45万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2102936&HistoricalAwards=false
• 关键词: Collaborative; Research; P2C2; Fingerprinting; Forced

Distinguishing between natural and forced climate variability has large implications for both interpreting past variations and for making accurate predictions of the future. Climate models and paleoclimate observations disagree about the magnitude of variability at interdecadal-and-longer time scales. This creates uncertainty in estimates of equilibrium climate sensitivity (temperature increase that result from a doubling of atmospheric carbon dioxide concentration) and in model projections of long-term climate variability. The key to reconciling this contradiction lies in understanding the relative importance of forced and unforced variability in the paleoclimate records. If the paleoclimate reconstructions are correct, then the missing physics must be identified, whether it be a lack of sensitivity to external forcing (e.g. volcanic eruption, solar variability, changing concentrations of greenhouse gases and aerosols), or an underrepresentation of internal variability (internal mechanisms within the climate system). This project proposes a framework for fingerprinting forced and unforced climate variability in Holocene paleoclimate records, based on their different spatial and temporal statistics. Specifically, the researchers will develop spatio-temporal fingerprints for forced and unforced climate variability, using a combination of Global Circulation Models (GCMs) simulations and fundamental physical principles, and apply them to the multiproxy paleoclimate record of Holocene climate variability. The researchers will build the fingerprints starting from GCMs, which provide a complete representation of the climate system and have the ability to disaggregate forced and unforced variability. The proxy-system models (forward modelling of mechanistic processes either biological or chemical, by which climate variability is recorded in a climate archive such as corals or ice cores) will be used to evaluate how these fingerprints are expressed in proxy records that are sparse, noisy, and can alter the statistics of climate signals. Given well-documented deficiencies in the ability of GCMs to simulate low-frequency variability in both observations and proxies, the GCM-based fingerprints will be complemented with physical-statistical stochastic models.The potential Broader Impacts include a greater understanding of Holocene climate variability and modeled projections by (1) building a single coherent picture of the factors controlling the response of temperature, hydrology, and hydroclimate proxies in the climate system; and (2) improving the physical interpretation of the low-frequency climate variability recorded in paleoclimate records. This research will potentially illuminate both the nature and sources of climate variability over the Holocene, and the physical mechanisms responsible. This has large implications for interpreting the recent observational record, and for inferences of climate projections. The statistical frameworks, model simulations, and simple dynamical models developed in this project will serve as a conceptual framework for climate-related research across the Earth Sciences and over all geologic timescales.The project will provide scientific training and professional development for two undergraduate and two graduate students. The undergraduate students will be involved in the research and its publication as demonstrated by the track record of the researchers. Output from the model simulations, Code for setting up the simulations with the publicly available Community Earth System Model (CESM), and Code for reproducing the diagnostics using the publicly available data and model output will be all made publicly available.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.

区分自然气候变化和强迫气候变化对解释过去的变化和对未来的准确预测都具有很大的影响。气候模型和古气候观察结果不同意跨时间和时间尺度上变异性的幅度。这会导致气候灵敏度估计的不确定性（由于大气二氧化碳浓度的增加而导致的温度升高）和长期气候变化的模型投影。核对这一矛盾的关键在于了解古气候记录中强制性变异性的相对重要性。如果古气候重建是正确的，则必须确定缺失的物理学，无论是对外部强迫缺乏敏感性（例如火山喷发，太阳可变性，温室气体和气溶胶的变化浓度），还是内部变异性不足的内部变异性（气候系统内部机械机制）。该项目提出了一个基于其不同的空间和时间统计数据，用于全新世古气候记录中强迫和非强制性气候变化的框架。具体而言，研究人员将使用全球循环模型（GCMS）模拟和基本物理原理的组合为强制和非强制性气候变异性开发时空指纹，并将其应用于全新世气候变异性的多X型古气候记录。研究人员将建立从GCM开始的指纹，该指纹提供了气候系统的完整表示，并有能力分解强制和无力的可变性。将使用代理系统模型（机械工艺的正向建模，无论是生物学还是化学过程，在气候档案中记录了气候变异性，例如珊瑚或冰芯），以评估这些指纹在稀疏，嘈杂的代理记录中如何表达这些指纹，并且可以改变气候信号的统计数据。 Given well-documented deficiencies in the ability of GCMs to simulate low-frequency variability in both observations and proxies, the GCM-based fingerprints will be complemented with physical-statistical stochastic models.The potential Broader Impacts include a greater understanding of Holocene climate variability and modeled projections by (1) building a single coherent picture of the factors controlling the response of temperature, hydrology, and hydroclimate proxies在气候系统中； （2）改善古气候记录中记录的低频气候变异性的物理解释。这项研究可能会阐明全新世气候变异性的性质和来源，以及负责的物理机制。这对解释最近的观察记录和气候预测的推断具有很大的影响。该项目中开发的统计框架，模型模拟和简单的动态模型将成为整个地球科学和所有地质时间范围内与气候有关的研究的概念框架。该项目将为两名本科和两名研究生提供科学培训和专业发展。本科生将参与研究及其出版物，如研究人员的往绩记录所证明。来自模型模拟的输出，使用公开可用的社区地球系统模型（CESM）设置模拟的代码，以及使用公开可用数据和模型输出来重现诊断的代码，将全部公开可用。该奖项反映了NSF的法定任务，并通过使用该基金会的知识优点和广泛影响来通过评估来评估NSF的法定任务。