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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Miami |
| Country | United States |
| Start Date | Sep 01, 2021 |
| End Date | Aug 31, 2025 |
| Duration | 1,460 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2126413 |
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.
University of Miami
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