SGER: North Atlantic Climate Variability from a Nonlinear Perspective

SGER：非线性视角下的北大西洋气候变化

• 批准号: 0425592
• 负责人: David Reusch
• 金额: $ 9.03万
• 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: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2005-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0425592&HistoricalAwards=false
• 关键词: SGER; North; Atlantic; Climate; Variability

This award, under the auspices of the Small Grants for Exploratory Research (SGER) program, will help support the development of a novel set of nonlinear tools and their application to the analysis of a well-known climatic event, the North Atlantic Oscillation (NAO). Success of this project could demonstrate the value of nonlinear techniques in paleoclimate studies, reveal strengths and weaknesses of linear versus nonlinear techniques, and contribute to better understanding of variability in climate at time scales of societal interest.The crux of the reason for pursuing this exploratory project is that much paleoclimatic research relies on a strong form of the uniformitarian hypothesis: a short term correlation between a particular sedimentary characteristic and a climatic variable is applied to a longer sedimentary record to reconstruct the climatic variable. The danger in such an approach became apparent the wider science community, when three independent, less-uniformitarian paleothermometers showed that a short-term calibration between mean-annual temperature and stable-isotopic ratios of water in ice underestimated past temperature changes in Greenland by threefold. The researcher and his colleagues suggest that one way to improve confidence in such analyses is to follow a completely independent uniformitarian analysis pathway and compare results. The statistical tools used commonly in uniformitarian paleoclimatic analyses are linear. Robust nonlinear "neural network" techniques have been developed in diverse fields, and the researcher has assembled appropriate nonlinear tools and applied them to reconstruction of paleoclimatic conditions in West Antarctica. The strategy is to apply these tools to one of the classic paleoclimatic problems: reconstruction of the history of the North Atlantic Oscillation (NAO). He will assess whether the nonlinear techniques do a better job in reconstructing this important climatic feature in validation intervals, and whether new insights are provided. If, as he and his colleagues suspect, the new techniques are better in the validation interval, then the longer NAO history they produce will be of use in broader studies, and differences between it and previous reconstructions will provide one estimate of the uncertainty in paleoclimatic research.The broader importance of the proposed research is far reaching because if the researchers are successful, they will provide a new tool for improving the confidence of paleoclimatic reconstructions.

在探索性研究（SGER）计划的小额赠款赞助下，该奖项将有助于支持开发一套新颖的非线性工具，并将其应用于分析一个著名的气候事件，北大西洋涛动（NAO）。该项目的成功可以证明非线性技术在古气候研究中的价值，揭示线性与非线性技术的优势和劣势，并有助于更好地理解社会利益时间尺度上的气候变化。追求这个探索性项目的关键原因是，许多古气候研究依赖于均变论假说的强有力形式：将特定沉积特征与气候变量之间的短期相关性应用于较长的沉积记录，以重建气候变量。这种方法的危险在更广泛的科学界变得显而易见，当三个独立的，不太均匀的古温度计显示，平均年温度和冰中水的稳定同位素比率之间的短期校准低估了格陵兰岛过去的温度变化三倍。 研究人员和他的同事们建议，提高对这种分析的信心的一种方法是遵循一种完全独立的均变论分析途径，并比较结果。均变论古气候分析中常用的统计工具是线性的。稳健的非线性“神经网络”技术已在不同领域得到发展，研究人员已组装了适当的非线性工具，并将其应用于西南极洲古气候条件的重建。该战略是将这些工具应用于经典的古气候问题之一：重建北大西洋涛动（NAO）的历史。他将评估非线性技术是否能在验证间隔内更好地重建这一重要的气候特征，以及是否提供了新的见解。如果像他和他的同事们怀疑的那样，新技术在验证间隔内更好，那么它们产生的更长的NAO历史将用于更广泛的研究，它与以前重建之间的差异将提供对古气候研究不确定性的一种估计。拟议研究的更广泛重要性是深远的，因为如果研究人员成功，它们将为提高古气候重建的可信度提供新的工具。