Collaborative Research: PReSto: A Paleoclimate Reconstruction Storehouse to Broaden Access and Accelerate Scientific Inference

合作研究：PReSto：扩大访问范围并加速科学推理的古气候重建仓库

• 批准号: 1948746
• 负责人: Nicholas McKay
• 金额: $ 45.35万
• 依托单位: Northern Arizona University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1948746&HistoricalAwards=false
• 关键词: Collaborative; Research; PReSto; Paleoclimate; Reconstruction

Records from tree rings, lake sediments, corals, and ice cores can be used as sources of information to understand how climate has changed in the past. Each of these sources can contain local climate information, so to look at continental or global-scale changes in climate these observations must be combined into “paleoclimate reconstructions”. Such reconstructions are broadly used to inform many fields, including archaeology, ecology and climate science, as well as land management and climate policy decisions. At present, there is no integrated solution to produce, update, or distribute these reconstructions. As a result, they are rarely updated, and the lack of a central clearinghouse makes reliable reconstructions difficult to find for non-experts. This project will create a Paleoclimate Reconstruction Storehouse (PReSto), that will use the most up-to-date data and cutting edge methods to provide broad access to paleoclimate reconstructions on the internet. By streamlining and increasing broader access to these important scientific resources, this project can accelerate scientific advances and improve public access to scientific products. PReSto will be an integrated solution that builds on existing and emerging cyberinfrastructure to 1) connect a steadily growing digital collection of paleoclimate data to evolving methodologies, 2) distribute the results, and 3) effectively visualize them through a web-based portal. Although PReSto will be designed for paleoclimate reconstructions of any climate variable or time period, this project will pilot the platform on two complementary time periods: the Common Era (the past 2,000 years) and the Holocene (the past ~12,000 years). Both periods help place modern climate into a much longer context, allowing researchers to probe low-frequency climate variability and its drivers. The Common Era incorporates monthly and annual records and established methodologies, whereas Holocene climate is typically observed at lower temporal resolution and synthesized using methods that are still under development. All code and outputs in PReSto will be publicly available and support knowledge transfer to constituencies at multiple levels of data and science literacy. PReSto will build capacity in the paleoclimate community with workshops that will 1) train data stewards to properly digitize and describe paleoclimate datasets, and 2) train early-career researchers to use this cyberinfrastructure to further their scientific objectives. This project will also develop resources for K-12 and tribal college teachers in Northern Arizona, and design and offer one-day educational workshops for teachers throughout the region.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

来自树木年轮、湖泊沉积物、珊瑚和冰芯的记录可以作为了解过去气候变化的信息来源。这些来源中的每一个都可以包含当地的气候信息，因此，为了观察大陆或全球范围内的气候变化，必须将这些观测结果合并到“古气候重建”中。这种重建被广泛用于为许多领域提供信息，包括考古学、生态学和气候科学，以及土地管理和气候政策决策。目前，还没有一个完整的解决方案来制作、更新或分发这些重建。因此，它们很少更新，而且缺乏中央信息交换中心，使得非专家很难找到可靠的重建。该项目将创建一个古气候重建仓库(PRESTO)，它将使用最新的数据和尖端方法，在互联网上提供广泛的古气候重建信息。通过精简和扩大对这些重要科学资源的获取，该项目可以加速科学进步，改善公众获取科学产品的机会。Presto将是一个综合解决方案，它建立在现有和新兴的网络基础设施上，1)将稳步增长的数字古气候数据收集与不断演变的方法联系起来，2)分发结果，3)通过基于网络的门户有效地将结果可视化。尽管Presto将被设计用于任何气候变量或时间段的古气候重建，但该项目将在两个互补的时间段上进行平台试验：普通时代(过去2000年)和全新世(过去约12,000年)。这两个时期都有助于将现代气候置于更长的背景下，使研究人员能够探索低频气候变异性及其驱动因素。共同时代包括月度和年度记录以及既定的方法，而全新世气候通常是以较低的时间分辨率观测的，并使用仍在开发中的方法进行合成。Presto的所有代码和产出都将向公众开放，并支持向不同层次的数据和科学素养的支持者转让知识。Presto将通过研讨会建设古气候界的能力，这些研讨会将1)培训数据管理员适当地数字化和描述古气候数据集，以及2)培训职业生涯早期的研究人员使用这种网络基础设施来促进他们的科学目标。该项目还将为亚利桑那州北部的K-12和部落大学教师开发资源，并为整个地区的教师设计和提供为期一天的教育研讨会。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

PaleoRec: A sequential recommender system for the annotation of paleoclimate datasets

• DOI: 10.1017/eds.2022.3
• 发表时间: 2022-04
• 期刊: Environmental Data Science
• 作者: Shravya Manety;D. Khider;Christopher Heiser;N. McKay;J. Emile‐Geay;C. Routson