CMG: Reconstructing Climate from Tree Ring Data

该奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。该项目寻求利用年轮数据推断气候变化的更好方法。在过去的两千年里，树木的年轮一直被用作重建气候条件的主要手段，将我们对气候的了解扩展到了仪器记录的时期之外。然而，年轮生长依赖于气候以外的其他因素，在利用年轮数据进行气候重建时，必须消除非气候影响。滤除非气候影响的传统方法可能过于极端，去除了一些气候信号以及非气候噪声。该项目的研究将改进使用贝叶斯分层建模的传统过滤方法，在该技术中，将构建统计模型，以确定树木年轮生长预期如何随气候和非气候(例如树龄)因素的变化而变化。然后，这些模型将与树木年轮数据相结合，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轮的重建可能在多大程度上受益于收集树轮数据的方式的变化。基于树木年轮的气候重建是关于自然气候波动范围的重要信息来源，因此，它们在评估近期气候变化在多大程度上超出了工业化前气候变化的范围方面发挥了重要作用。因此，这项研究在树木年轮分析方面的改进将对我们理解自然和人类引起的气候变异和变化产生广泛的影响。此外，树木年轮是关于水资源过去可变性范围的重要信息来源，这是半干旱西南部各州的水资源管理者感兴趣的。除了这些好处，这项研究还将开发适用于一系列科学问题的统计技术，在这些问题中，复杂系统的行为必须从代理数据中推断出来。

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.