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.

极光表明，高层大气和磁层之间最动态的电磁能量和动量交换过程发生在极地区域。由于这些过程而沉积到高层大气中的能量引起了巨大的全球扰动，包括全球温度和中性质量密度的增加以及等离子体密度的变化。这些近地空间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。为了满足研究界对综合地面和天基仪器的不同数据以更好地确定磁层电磁能量和动量沉积的工具的需求，该项目将开发和部署一个开放源码的PYTHON软件，以便以最佳方式融合这些数据集。该项目将通过提供对强大的数据分析工具和再分析数据产品的轻松访问，增强个人调查人员的能力。拟议的传播活动旨在促进开放源码和开放数据协作队列的基层发展，以催化地球空间界内部必要的文化变革，使其充分受益于大数据时代的机遇。该项目将使研究机构的一名博士后、两名研究生和几名本科生参与一个多方面的项目，从而扩大他们的教育和培训经验。拟议的软件和基础设施将用于编写研究生课程材料。受地球空间观测能力的最新进展和大数据机遇的启发，该提案旨在(1)开发和部署开放源代码的Python软件和相关的网络应用程序，用于与现有的地球空间社区数据资源和标准互操作的地球空间观测同化地图，以及(2)创建完全可复制的、经过验证的再分析数据产品，这些产品可以从现有的数据存储库中访问，以最大限度地实现国家科学基金会和其他联邦机构的计划投资的科学回报。现有数据同化和数据分析工具是作为研究人员早些时候的EarthCube试点项目的一部分开发的，其能力将得到扩展，以利用地球空间科学的最新发展和发现。拟议的网络应用服务和软件将使数据收集、前处理和质量控制步骤自动化，以减轻非专家的障碍。地球空间观测同化测绘软件将以符合第一原则并严格考虑与每一次观测相关的不确定性的方式，以最佳方式合并各种地球空间观测数据，从而提供磁层-电离层耦合的连贯、同时和半球间的图景。通过与社区科学工作组合作组织的研讨会，研究人员将使地球航天社区参与协作的地球空间系统科学活动，以及使用通用的、可访问的、可扩展的数据分析工具的科学驱动的数据产品验证过程。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。