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

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式模拟档案，在过去调查年代际和多年代际气候振荡的研究基础上建立。所提出的补充分析可以提供对内部气候变率性质的更全面的理解，从而可以评估在年代际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，而不仅仅是红噪声谱连续体的一部分，(b)基于长期古气候数据的证据在时间上持续存在，以及(c)在时间尺度和空间格局上都是一致的。在长时间的、最先进的模型控制仿真中识别出可变性模式。这种分析可以为十年和较长期气候可预测性的潜力评估提供信息。该方法将主要侧重于应用多锥度方法奇异值分解（MTM-SVD）来检测和表征时空仪器、代理和模式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19世纪中期以来最新的全球地表温度数据，以重新评估年代际至多年代际气候变率振荡时空模式的观测证据，并重建相关信号的时间演变模式。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），以获得有关海洋-大气动力学的更全面的看法。下一步将是分析过去一千年的古气候代理记录，以建立信号的长期稳健性和持久性，并解决在向人类活动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，利用现在可获得的跨越过去千年的更广泛的古气候数据档案。通过对耦合模式比对项目第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未来预估实验的平行分析，将寻求进一步的机制理解。这些比较将评估在具有与观测和古气候数据中分离出来的时间尺度和空间特征相似的时空振荡气候信号的不同选择模式中是否存在一致的证据。对比控制、上一千年、历史和预估的未来模拟，可以评估强迫的变化是否以及如何影响或相互作用于内部变率的特征。提出的补充分析应提供对内部气候变率性质的更全面的理解，从而能够评估在年代际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，而不仅仅是红噪声谱连续体的一部分，(b)基于长期古气候数据的证据在时间上持续存在，以及(c)在时间尺度和空间格局上都是一致的。在长时间的、最先进的模型控制仿真中识别出可变性模式。此外，这种分析将为十年和较长期气候可预测性的潜力评估提供信息。潜在的更广泛的影响包括对窄带年代际和多年代际气候信号的证据进行更明确的评估，以改进年代际时间尺度的预测。在十年代际和长期气候预报方面更强大的预测技能，以及对潜在机制或该技能的来源有更好的物理理解，可以帮助包括广大公众在内的一系列利益攸关方从改进的气候预报中受益。该项目还将支持一名早期职业科学家和研究生。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。

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.