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.

该奖项由探索性研究小额赠款(SGER)计划赞助，将帮助开发一套新的非线性工具，并将其应用于分析著名的气候事件--北大西洋涛动(NAO)。该项目的成功可以展示非线性技术在古气候研究中的价值，揭示线性和非线性技术的优缺点，并有助于更好地理解气候在社会利益时间尺度上的变异性。进行这一探索性项目的关键是，许多古气候研究依赖于一种强有力的统一性假设：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，当时三个独立的、不太统一的古温度计表明，平均年温度和冰中水的稳定同位素比率之间的短期校准将格陵兰过去的温度变化低估了三倍。这位研究人员和他的同事建议，提高此类分析信心的一种方法是遵循完全独立的统一分析路径，并比较结果。均匀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经在不同的领域得到了发展，研究人员已经组装了适当的非线性工具，并将它们应用于重建南极西部的古气候条件。其策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。他将评估在验证期间，非线性技术是否在重建这一重要气候特征方面做得更好，以及是否提供了新的见解。如果像他和他的同事怀疑的那样，新技术在验证区间内更好，那么它们产生的更长的NAO历史将在更广泛的研究中使用，它与以前重建的差异将为古气候研究的不确定性提供一个估计。拟议的研究的更广泛的重要性是深远的，因为如果研究人员成功，他们将为提高古气候重建的信心提供一个新的工具。