About this project
Description from the program archive
Developing a subsetting tool to access ocean forecast data is critical and addresses an immediate need for maximizing the utilization of STOFS model output. STOFS-2D global stands out as one of the most refined and high-resolution global ocean forecast datasets available. The STOFS Data Subsetting Tool project enhances the xarray-subset-grid library to efficiently subset STOFS and oceanographic data. Through Python libraries like Xarray, Zarr and Dask, it benchmarks performance, integrates with ocean modeling packages, and develops a service for on-demand subsetting via email or API. The project spans 12-16 weeks, focusing on method benchmarking, performance evaluation, optimization, service development, and the creation of a portal for subsetting datasets.