EarthCube Data Capabilities: Collaborative Proposal: Assimilative Mapping of Geospace Observations

EarthCube 数据能力：协作提案：地理空间观测同化制图

• 批准号: 1928327
• 负责人: J Michael Ruohoniemi
• 金额: $ 15.16万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928327&HistoricalAwards=false
• 关键词: EarthCube; Data; Capabilities; Collaborative; Proposal

The most dynamic electromagnetic energy and momentum exchange processes between the upper atmosphere and the magnetosphere take place in the polar regions as evidenced by the aurora. Energy deposited into the upper atmosphere as a result of these processes causes dramatic global disturbances, including global temperature and neutral mass density enhancement and plasma density changes. These near-Earth space environment disturbances can negatively impact radio communication, navigation, positioning, and satellite tracking. In response to the research community's need for tools to combine heterogeneous data from ground-based and space-based instrumentation to better specify electromagnetic energy and momentum deposition from the magnetosphere, the project will develop and deploy an open-source Python software to optimally fuse these data sets. The project will empower individual investigators by providing easy access to a powerful data analysis tool and reanalysis data products. The proposed dissemination activities are intended to promote grassroots development of an open-source and open-data collaborative cohort, to catalyze a cultural change within the geospace community necessary for it to fully benefit from opportunities of the Big Data era. The project will serve to broaden the education and training experiences of one postdoc, two graduate and several undergraduate students at the researcher's institutions by engaging them in a multi-faceted project. The proposed software and infrastructure will be used to develop graduate course material. Inspired by recent advancements in geospace observing capabilities and the opportunities of Big Data, the proposal aims (1) to develop and deploy an open-source Python software and associated web-applications for Assimilative Mapping of Geospace Observations that are interoperable with established geospace community data resources and standards, and (2) to create fully reproduceable, validated reanalysis data products that can be accessed from established data repositories to maximize the scientific return on the program investment from the National Science Foundation and other federal agencies. The capabilities of existing data assimilation and data analysis tools, developed as part of the researcher's earlier EarthCube pilot project, will be extended to take advantage of the latest development and findings in the geospace sciences. The proposed web application service and software will automate data collection, pre-processing, and quality control steps to mitigate hurdles for non-experts. The Assimilative Mapping of Geospace Observations software will provide a coherent, simultaneous and inter-hemispheric picture of magnetosphere-ionosphere coupling by optimally combining diverse geospace observational data in a manner consistent with first-principles and with rigorous consideration of the uncertainty associated with each observation. Through workshops organized in partnership with community science working groups, the researchers will engage the geospace community in the collaborative geospace system science campaigns and science-driven process of data product validation using the common, accessible, expandable data analysis tools.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.

高层大气和磁层之间最动态的电磁能和动量交换过程发生在极光区域。由于这些过程，沉积到高层大气中的能量会引起急剧的全球干扰，包括全球温度和中性质量密度增强和血浆密度变化。这些近地太空环境干扰会对无线电通信，导航，定位和卫星跟踪产生负面影响。为了响应研究界对工具的需求，将基于地面和太空仪器的异质数据结合起来，以更好地指定磁层的电磁能和动量沉积，该项目将开发和部署开源的Python软件，以最佳地融合这些数据集。 该项目将通过轻松访问强大的数据分析工具和重新分析数据产品来增强个人调查人员的能力。拟议的传播活动旨在促进开源和开放数据协作队列的基层开发，以促进其在Geospace社区内的文化变革所必需的文化变革，以使其完全受益于大数据时代的机会。该项目将通过使他们参与一个多方面的项目来扩大研究人员机构的两名毕业生和几名本科生的教育和培训经验。拟议的软件和基础设施将用于开发研究生课程材料。该提案旨在（1）旨在开发和部署和部署开源的Python软件和相关的Web应用程序，以同化与既定的GeoSpace社区数据资源和标准的既定数据，（2），该提案旨在开发和部署开源Python软件和相关的Web应用程序，从而创造出可行的数据，从而使Reproducty访问有效的数据，从而创造了有效的数据，从而创造了有效的数据，该提案旨在从地球上观察能力和大数据的机会的最新进步启发。存储库最大化国家科学基金会和其他联邦机构的计划投资的科学回报。作为研究人员较早的EarthCube Pilot项目的一部分而开发的现有数据同化和数据分析工具的功能将扩展，以利用Geospace Sciences中的最新发展和发现。提出的Web应用程序服务和软件将自动化数据收集，预处理和质量控制步骤，以减轻非专家的障碍。地球上观测软件的同化映射将通过最佳地组合多种多样的GeoSpace观测数据，以与首发的方式相结合，并与对每种observation相关的不确定性相关的考虑，从而提供磁层 - 离子层耦合耦合的连贯，同时和杂膜间图像。通过与社区科学工作组合作组织的研讨会，研究人员将使用共同的，可访问的，可访问的数据分析工具进行合作地Geospace社区参与地理空间系统科学和以科学为导向的数据产品验证的过程。该奖项反映了NSF的立法任务，并被认为是通过基础智力的评估来评估的，并值得通过评估来进行基金会的评估和广泛的影响。