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| Collaborative Research: Improved Characterization of Internal Decadal-Multidecadal Climate Variability Using Paleoclimate Archives, Observational Climate Data and Model Simulations | |
| 项目编号 | 1748097 |
| Michael Mann | |
| 项目主持机构 | Pennsylvania State Univ University Park |
| 开始日期 | 2018-07-01 |
| 结束日期 | 06/30/2022 |
| 英文摘要 | 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. |
| 资助机构 | US-NSF |
| 项目经费 | $474,083.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/213019 |
| 推荐引用方式 GB/T 7714 | Michael Mann.Collaborative Research: Improved Characterization of Internal Decadal-Multidecadal Climate Variability Using Paleoclimate Archives, Observational Climate Data and Model Simulations.2018. |
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