NSF Summer 2019 workshop: Computing Arctic Data: Orono, ME - Spring 2019

NSF 2019 年夏季研讨会：计算北极数据：缅因州奥罗诺 - 2019 年春季

• 批准号: 1848747
• 负责人: Andrei Kurbatov
• 金额: $ 5万
• 依托单位: University of Maine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1848747&HistoricalAwards=false
• 关键词: NSF; Summer; 2019; workshop; Computing

To better understand causes, trends and thresholds of a changing Arctic and to develop robust societal adaptation strategies new research tools are needed. There is a wealth of past climate data sets stored in the NSF-funded Arctic Data Center (ADC) that are unresolved yet have the potential to expand and deepen the current state of understanding about how the Arctic is responding to environmental changes. This award supports an integrative workshop that will bring together a diverse group of early career scientists and experts from the fields of ice core, computer and climate sciences to transform the existing research data computation platform. The goal is to pave the way for the development of a future generation of computer tools necessary to better understand complex interactions of multiple driving forces that are changing Earth's environment. Objectives are to evaluate the latest computational advances, break existing interdisciplinary barriers that limit the use of ice core data sets in climate research, and, by openly sharing results, promote the development of future products that will benefit the Arctic research community and the global population. Evaluating present and forecasting future trends in the "New Arctic" system is closely connected to understanding multidimensional paleoclimate data archives. Using open source tools to ease the reproduction of computational and data-intensive portions of paleoclimate research, transparency in data processing steps will increase. In addition, (1) the range of usability of existing climate and ice core based paleoclimate data archives will be extended; (2) open access data and software libraries, utilizing open source based software tools will be developed; (3) paleoclimate and computer infrastructure specific white papers will be developed that will summarize the state of the problem, map future pathways for systematic improvements, and finally converge this rapidly evolving research domain with a novel computational and easy to use data processing framework.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.

为了更好地了解北极变化的原因、趋势和阈值，并制定强有力的社会适应策略，需要新的研究工具。 NSF 资助的北极数据中心 (ADC) 中存储了大量过去的气候数据集，这些数据集尚未解决，但有可能扩大和加深对北极如何应对环境变化的当前了解。该奖项支持举办一个综合研讨会，该研讨会将汇集来自冰芯、计算机和气候科学领域的不同早期职业科学家和专家，以改造现有的研究数据计算平台。其目标是为开发下一代计算机工具铺平道路，以更好地理解正在改变地球环境的多种驱动力的复杂相互作用。目标是评估最新的计算进展，打破限制冰芯数据集在气候研究中使用的现有跨学科障碍，并通过公开分享结果，促进未来产品的开发，造福北极研究界和全球人口。 评估“新北极”系统当前和预测未来趋势与了解多维古气候数据档案密切相关。使用开源工具来简化古气候研究的计算和​​数据密集部分的复制，数据处理步骤的透明度将会增加。此外，（1）现有气候和冰芯古气候数据档案的可用范围将得到扩展； (2) 将开发开放获取数据和软件库，利用基于开源的软件工具； (3) 将制定针对古气候和计算机基础设施的白皮书，总结问题的状况，绘制系统改进的未来路径，并最终将这一快速发展的研究领域与新颖的计算和易于使用的数据处理框架融合起来。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。