P2C2: Paleo Perspectives on Temperature Extremes

为了提高我们对历史和现代极端温度的理解，哈佛大学的研究人员将使用新的统计方法分析过去气候的仪器和温度敏感代理。 具体而言，研究人员将探索极端事件的仪器和代理指标之间的关系，重建空间和时间上的极端温度，并更好地了解平均气候变化与极端事件发生的关系。 分析战略是扩展现有的贝叶斯方法，以更直接地针对极端情况推断过去的气候。“极端”的定义将符合国家研究理事会在2006年提出的标准，即精确量化诸如最大值、最小值或变化率之类的量是真正例外的概率。根据定义，极端是罕见的，这使得记录的时间比单独使用仪器所能提供的时间更长，也许比评估平均气候更为迫切。 该项目的成功完成将提供对背景气候和极端气候在足够长的时间内的共变性的洞察，以建立基线条件。这项工作还将为解释和评估现代变化提供重要背景。 鉴于不同的机制是过去600年来变暖和变冷的原因，这项研究还将表明过去平均气候和极端气候之间的关系在多大程度上可以用作未来变化的类比。除了更好地理解极端事件的社会意义外，其他更广泛的影响包括研究生的培训和早期职业研究人员的支持，没有事先国家科学基金会的支持。在这项研究期间开发的所有软件工具将免费公开提供给古气候界，任何公开数据集的汇编也是如此。

To improve our understanding of historical and modern extreme temperatures, researchers at Harvard University will analyze instrumental and temperature-sensitive proxies of past climate using new statistical approaches. Specifically, the researchers will explore the relationships between instrumental and proxy indicators of extremes, reconstruct temperature extremes in space and time, and provide a better understanding of how changes in mean climate relate to the occurrences of extreme events. The analysis strategy is to extend an existing Bayesian methodology for inferring past climate to more directly target extremes. Definition of "extremes" will meet the standards set forth by the National Research Council in 2006 for accurate quantification of the probability that quantities such as maxima, minima, or rates-of-change are truly exceptional.Extremes are by definition rare, making the need for records longer than are afforded by instruments alone perhaps even more acute than for evaluation of mean climate. Successful completion of this project will provide insight into the co-variability between background climate and extremes over a time period long enough to establish baseline conditions. The work will also provide important context in which to interpret and assess modern changes. Given that disparate mechanisms are responsible for warming and cooling over the last 600 hundred years, this research will also indicate the extent to which past relationships between mean climate and extremes can be used as analogues for future changes.In addition to the societal relevance of better understanding extreme events, other broader impacts include training of a graduate student and support of an early career researcher with no prior NSF support. All software tools developed during this research will be made freely and publicly available to the paleoclimate community, as will any compilations of publicly available data sets.