CMG: Reconstructing Climate from Tree Ring Data

CMG：从树木年轮数据重建气候

• 批准号: 0934516
• 负责人: Andrew Gelman
• 金额: $ 59.81万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0934516&HistoricalAwards=false
• 关键词: CMG; Reconstructing; Climate; Tree; Ring

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).This project seeks better ways to use tree ring data to infer changes in climate. Annual growth rings in trees have long been used as a primary means of reconstructing climatic conditions over the past two millennia, extending our knowledge of climate beyond the period of the instrumented record. However, tree ring growth depends on factors other than climate, and non-climatic influences must be removed when tree ring data is used for climate reconstruction. Traditional methods for filtering out non-climatic influences can be too extreme, removing some of the climate signal as well as the non-climate noise. The research in this project will improve upon traditional filtering methods using Bayesian hierarchical modeling, a technique in which statistical models will be constructed to specify how tree rings growth is expected to vary in response to both climatic and non-climatic (e.g. tree age) factors. The models will then be combined with tree ring data to produce both climate reconstructions and estimates of the level of uncertainty present in the reconstructions. Additional research will consider the extent to which tree ring-based reconstructions might benefit from changes in the way tree ring data is collected. In particular, the potential benefit from taking additional cores from each tree will be evaluated.Tree ring-based climate reconstructions are an important source of information on the range of natural climate fluctuations, and thus they play an important role in assessing the extent to which recent climate changes are outside the envelope of pre-industrial climate variability. The improvements in tree ring analysis resulting from this research will thus have a broad impact on our understanding of both natural and human-induced climate variation and change. In addition, tree rings are an important source of information regarding the range of past variability in water resources, which is of interest to water managers in the semi-arid southwestern states. Beyond these benefits, the research will develop statistical techniques which will be applicable to a range of scientific problems in which the behavior of a complex system must be inferred from proxy data.

该奖项是根据2009年的《美国回收与再投资法》（公法111-5）资助的。本项目寻求更好的方法来使用树环数据来推断气候变化。 在过去的两千年中，长期以来，树木中的年度生长环一直用作重建气候条件的主要手段，从而将我们对气候的知识扩展到了仪器记录的时期。 但是，树环的生长取决于气候以外的其他因素，当将树环数据用于气候重建时，必须消除非气候影响。 过滤非气候影响的传统方法可能太极端了，消除了某些气候信号以及非气候噪声。 该项目中的研究将改善使用贝叶斯分层建模的传统过滤方法，该技术将构建统计模型，以指定树环的增长如何因气候和非气候和非气候和非气候（例如树时代）因素而变化。 然后，模型将与树环数据结合使用，以产生气候重建和重建中存在的不确定性水平的估计。 其他研究将考虑基于树环的重建可能受益于收集树环数据的变化的程度。 特别是，将评估从每棵树上取其他核心的潜在益处。基于树环的气候重建是自然气候波动范围的重要信息来源，因此它们在评估最近气候变化的程度中起着重要作用，在多大程度上超出了工业前工业气候变化的范围。 因此，这项研究产生的树环分析的改进将对我们对自然和人类引起的气候变化和变化的理解产生广泛的影响。 此外，树环是有关水资源过去变异范围的重要信息来源，这对于半干旱西南州的水管理者感兴趣。 除这些好处外，研究还将开发统计技术，这些技术将适用于一系列科学问题，其中必须从代理数据中推断出复杂系统的行为。