Automated Method to Extract Oceanographic and Atmospheric Data from Online Sources
Abstract
The US Navy relies on accurate forecasts of the battlespace environment including ocean waves, currents, and water levels near the coast. The forecast models are dependent on the fidelity of their forcing, boundary, and initial conditions. Model developers need automated and efficient methods to obtain data to drive and validate coastal models. This Memorandum Report describes three publicly available online web servers to obtain modeled and observed meteorologic and oceanographic data. A suite of algorithms was developed to extract, reformat, and visualize the data. There is a significant capability gap in the useful dissemination of big data from operational model output. Access to the most recent and reliable data, as well as efficient and automated algorithms, improves the accuracy and fidelity of the Navy's environmental forecasts to the fleet, and advance visualization of the forecasts would provide enhanced information for mission planning.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 20, 2022
- Accession Number
- AD1184125
Entities
People
- A. Penko
- Kendal Hall
- Sunni Schoenauer
Organizations
- Howard University
- United States Naval Research Laboratory