EarthCube Capabilities: CloudDrift: a platform for accelerating research with Lagrangian climate data

DriftCloud项目旨在推动发现和使用主要由自由漂流浮标收集的独特海洋拉格朗日观测数据。开发的工具将利用现有的网络基础设施和已建立的开源和开放访问协议，以便将海洋观测和数值异构分布地理空间数据的分析提供给从高中学生到统计专家等熟练程度用户的指尖。这可能有助于更公平地获取数据和计算资源，用于广泛的具体和跨学科应用，从海洋塑料运输到表面重力波对卫星海面温度校准的影响。由于与EarthCube和其他认知社区的合作，广泛而多样化的用户将能够访问这些笔记本，这些笔记本将绑定到部署在现有基础设施上的开放访问的基于云的可执行环境。这个项目将支持一位职业生涯早期的科学家。DriftCloud项目将利用美国国家海洋和大气管理局全球漂流计划的漂流浮标提供的与气候相关的海面洋流、海面温度和海平面压力的拉格朗日数据作为工作框架，促进和加速拉格朗日数据集的生成和分析。该项目将生成新的附加数据集和一套模块化和开源转换工具，为分析和优化云计算环境提供拉格朗日数据集。将开发一套额外的开源工具，用于快速有效地可视化和分析任何拉格朗日数据。这两套软件工具的使用将通过使用开源python语言创建教学示范Jupyter notebook来促进。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The DriftCloud project aims at propelling forward the discovery and use of unique oceanic Lagrangian observational data principally gathered by freely drifting buoys. The tools developed will utilize existing cyberinfrastructures and established open source and open access protocols in order to bring analyses of ocean observational and numerical heterogeneously distributed geospatial data at the fingertips of users with level of proficiency ranging from high school students to statistical experts. This will potentially contribute to more equitable access to data and computing resources for a broad spectrum of specific and interdisciplinary applications ranging from marine plastics transport to the impact of surface gravity waves on satellite sea surface temperature calibrations. A wide and diverse set of users will be able to access these notebooks which will be bound to openly-accessible cloud-based executable environments deployed on existing infrastructures thanks to collaborations with the EarthCube and other cognizant communities. This project will support an early-career scientist.The DriftCloud project will facilitate and accelerate the production and analysis of Lagrangian datasets by using the climate relevant Lagrangian data of sea surface current, sea surface temperature, and sea level pressure from the drifting buoys of the National Oceanic and Atmospheric Administration’s Global Drifter Program as a working framework. The project will generate new add-on datasets and a suite of modular and open source conversion tools to render Lagrangian datasets ready for analyses and optimized for cloud computing environments. An additional suite of open source tools will be developed for rapid and efficient visualizations and analyses of any Lagrangian data. The utilization of both suites of software tools will be fostered by creating pedagogical demonstration Jupyter Notebooks using the open source python language.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.