Searching for Abrupt Climate Change Precursors Using Ultra High Resolution Ice Core Analysis

The project will undertake an ultra high resolution, multi-parameter investigation of past climate to develop predictors for future abrupt climate change through identification of the "tipping points" which occur prior to an abrupt climate change events. Ultra-high resolution (up to 4 micron) ice core records will be produced -- well beyond the ~1cm resolution currently available -- using continuous flow injection into both a Thermo Element 2 ICP-MS and a Picarro Inc. L-2130-I H2O isotope analyzer sampled using a newly developed state-of-the-art cryocell chamber integrated with digital image recording and annotating software. The PI will look for precursors that reveal evidence of changes in, for example, the timing and magnitude of temperature, precipitation and atmospheric circulation from multi-decadal down to hundreds of sampling levels per year. The project will train students to be well versed in advanced laboratory and numerical modeling methods. Students will learn data reduction and visualization algorithms while also helping to provide a data stream that has broad applicability to climate. Cyberinfrastructure developed under NSF funding to the Climate Change Institute will be used to store, process, and visualize this high volume of ice core data while also making the information available to the public with high transparency for climate change use and attribution.本项目将开展超高分辨率多参数的古气候研究，通过识别气候突变事件发生前的“临界点（tipping points）”，构建未来气候突变的预测模型。研究将获取分辨率高达4微米的冰芯记录——这一指标远超当前约1厘米的主流采样分辨率——具体实现方式为：采用连续流进样技术，结合Thermo Element 2 ICP-MS与Picarro公司L-2130-I型水同位素分析仪，并借助全新研发的集成数字图像记录与注释软件的尖端低温样品舱完成采样。项目负责人（Principal Investigator，PI）将搜寻能够反映温度、降水与大气环流的时序与强度变化的前兆信号，时间尺度涵盖数十年至每年数百个采样层级。本项目将培养学生熟练掌握先进实验室技术与数值模拟方法，学生将学习数据简化与可视化算法，同时参与构建具备广泛气候研究应用价值的数据集。依托美国国家科学基金会（National Science Foundation, NSF）资助气候变化研究所搭建的网络基础设施，本项目将对这批海量冰芯数据进行存储、处理与可视化，并以高透明度向公众开放相关信息，以供气候变化研究与归因分析使用。