Climate Change Data Portal
| NSF Summer 2019 workshop: Computing Arctic Data: Orono, ME - Spring 2019 | |
| 项目编号 | 1848747 |
| Andrei Kurbatov | |
| 项目主持机构 | University of Maine |
| 开始日期 | 2018-09-01 |
| 结束日期 | 08/31/2022 |
| 英文摘要 | 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. |
| 资助机构 | US-NSF |
| 项目经费 | $49,999.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/213324 |
| 推荐引用方式 GB/T 7714 | Andrei Kurbatov.NSF Summer 2019 workshop: Computing Arctic Data: Orono, ME - Spring 2019.2018. |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| [Andrei Kurbatov]的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| [Andrei Kurbatov]的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| [Andrei Kurbatov]的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
