Collaborative Research: Improved Characterization of Internal Decadal-Multidecadal Climate Variability Using Paleoclimate Archives, Observational Climate Data and Model Simulations

合作研究：利用古气候档案、观测气候数据和模型模拟改进内部十年-数十年气候变化的表征

• 批准号: 1748097
• 负责人: Michael Mann
• 金额: $ 47.41万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1748097&HistoricalAwards=false
• 关键词: Collaborative; Research; Improved; Characterization; Internal

This project aims to build upon past research investigating interdecadal and multidecadal climate oscillations through the analysis of expanded paleoclimate proxy data, updated instrumental data, and extensive multi-model simulation archives that have recently become available. The complementary set of proposed analyses may provide a more comprehensive understanding of the nature of internal climate variability, allowing assessment of whether there are distinct modes of internal variability on decadal and longer timescales that (a) are oscillatory in nature, as opposed to being simply part of the red noise spectral continuum, (b) persist back in time based on evidence from long-term paleoclimate data and (c) are consistent, in both timescale and spatial pattern, with modes of variability identified in long, state-of-the-art model control simulations. Such analyses could inform assessments of the potential for decadal and longer-term climate predictability.The methodology will principally focus on application of the multi-taper method singular value decomposition (MTM-SVD) to detect and characterize narrowband spatially-coherent signals in spatiotemporal instrumental, proxy, and model-generated climate datasets. The MTM-SVD methodology will first be applied to up-to-date global surface temperature data dating back through the mid-19th century to reevaluate the observational evidence for oscillatory spatiotemporal modes of decadal-to-multidecadal climate variability and to reconstruct the time-evolving patterns of the associated signals. The signals will be projected onto other fields (sea level pressure, sub-surface ocean heat content and circulation, and upper-atmosphere data) to obtain a more comprehensive view of the associated ocean-atmosphere dynamics. The next step will be to analyze paleoclimate proxy records spanning the past millennium to establish the long-term robustness and persistence of signals and to address potential changes in the character of signals during the transition into the anthropogenic era. These analyses will build upon past frequency-domain analyses of global climate proxy data by employing the considerably more extensive paleoclimate data archives now available spanning the past millennium. A further mechanistic understanding will be sought through parallel analysis of the (a) control, (b) last millennium, (c) historical and (d/e) RCP 4.5/8.5 future projection experiments from the Coupled Model Inter-Comparison Project Phase 5 (CMIP5) and CMIP6 projects. These comparisons will assess whether consistent evidence exists across a diverse selection of models for spatiotemporal oscillatory climate signals with similar timescale and spatial characteristics to those isolated in the observations and paleoclimate data. Comparisons of control, last millennium, historical, and projected future simulations will allow assessment of whether and how changes in forcing impact or interact with the characteristics of the internal variability.The complementary set of proposed analyses should provide a more comprehensive understanding of the nature of internal climate variability, allowing assessment of whether there are distinct modes of internal variability on decadal and longer timescales that (a) are oscillatory in nature, as opposed to being simply part of the red noise spectral continuum, (b) persist back in time based on evidence from long-term paleoclimate data and (c) are consistent, in both timescale and spatial pattern, with modes of variability identified in long, state-of-the-art model control simulations. Such analyses will, furthermore, inform assessments of the potential for decadal and longer-term climate predictability.The potential Broader Impacts include a more definitive assessment of evidence for narrowband interdecadal and multidecadal climate signals to improve decadal timescale forecasting. More robust predictive skill in decadal and longer-term climate forecasting and a better physical understanding of the underlying mechanisms, or origin of that skill, could aid an array of stakeholders, including the public at large, benefit from improved climate forecasts. The project will also support an early career scientist and graduate students.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.

该项目旨在通过分析扩展的古气候代理数据、更新的仪器数据和最近可用的广泛的多模型模拟档案，以过去调查年代际和多年代际气候振荡的研究为基础。所提出的一组补充分析可以提供对内部气候变率性质的更全面的理解，从而可以评估十年和更长时间尺度上是否存在不同的内部变率模式，这些模式（a）本质上是振荡的，而不是简单地作为红噪声频谱连续体的一部分，（b）根据长期古气候数据的证据及时持续存在，以及（c）在时间尺度和空间上都是一致的 模式，并在长期、最先进的模型控制模拟中识别出可变性模式。此类分析可以为评估十年和长期气候可预测性的潜力提供信息。该方法将主要侧重于应用多锥方法奇异值分解（MTM-SVD）来检测和表征时空仪器、代理和模型生成的气候数据集中的窄带空间相干信号。 MTM-SVD方法将首先应用于可追溯到19世纪中叶的最新全球表面温度数据，以重新评估十年至数十年气候变化的振荡时空模式的观测证据，并重建相关信号的时间演化模式。这些信号将被投射到其他领域（海平面压力、地下海洋热含量和环流以及高层大气数据），以获得相关海洋大气动态的更全面的视图。 下一步将是分析过去千年的古气候代理记录，以确定信号的长期稳健性和持久性，并解决向人类时代过渡期间信号特征的潜在变化。这些分析将建立在过去对全球气候代理数据的频域分析的基础上，利用过去千年中现有的更广泛的古气候数据档案。 将通过对耦合模型相互比较项目第 5 阶段 (CMIP5) 和 CMIP6 项目的 (a) 控制、(b) 上个千年、(c) 历史和 (d/e) RCP 4.5/8.5 未来预测实验进行并行分析，寻求进一步的机制理解。这些比较将评估时空振荡气候信号的多种选择模型中是否存在一致的证据，这些信号具有与观测和古气候数据中分离的信号相似的时间尺度和空间特征。对控制、上个千年、历史和预测的未来模拟进行比较，将有助于评估强迫变化是否以及如何影响内部变率的特征或与内部变率的特征相互作用。所提出的一组补充分析应提供对内部气候变率性质的更全面的理解，从而可以评估在十年和更长的时间尺度上是否存在不同的内部变率模式，这些模式（a）本质上是振荡的，而不是简单地作为内部变率的一部分。 红噪声光谱连续体，（b）基于长期古气候数据的证据，在时间上持续存在，（c）在时间尺度和空间模式上都是一致的，与长期、最先进的模型控制模拟中确定的变异模式一致。此外，此类分析将为评估十年和长期气候可预测性的潜力提供信息。潜在的更广泛影响包括对窄带年代际和十年间气候信号的证据进行更明确的评估，以改进十年时间尺度的预测。 十年间和长期气候预测中更强大的预测技能以及对基本机制或该技能起源的更好的物理理解可以帮助包括广大公众在内的一系列利益相关者从改进的气候预测中受益。该项目还将支持早​​期职业科学家和研究生。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

On The Estimation of Internal Climate Variability During the Preindustrial Past Millennium

• DOI: 10.1029/2021gl096596
• 发表时间: 2022-01
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: M. Mann;B. Steinman;D. Brouillette;A. Fernandez;S. Miller

Multidecadal climate oscillations during the past millennium driven by volcanic forcing

• DOI: 10.1126/science.abc5810
• 发表时间: 2021-03-05
• 期刊: SCIENCE
• 影响因子: 56.9
• 作者: Mann, Michael E.;Steinman, Byron A.;Miller, Sonya K.
• 通讯作者: Miller, Sonya K.