A suite of tutorials on data collection, analysis methods, and visualization techniques used in physical oceanography and biogeochemistry created by retracing the steps needed to reproduce results from two published articles(1,2) on:
- combining field data with satellite data to understand the sea surface temperature conditions associated with a hurricane undergoing rapid intensification over the continental shelf
- using locally calibrated satellite products to improve the satellite estimation of the partial pressure of carbon dioxide in coastal waters
From NASA'S Open-Source Science Initiative (OSSI):
Open-source science requires a culture shift to a more inclusive, transparent, and collaborative scientific process, which will increase the pace and quality of scientific progress.
As part of the OSSI, course materials are being developed for Open Science 101, also called OpenCore. Beyond the basics, it is often difficult to find the time or motivation to study something not specifically applicable to our current workloads. Enter ScienceCore:
ScienceCore is a curriculum of discipline-specific materials that showcase open-science workflows.
We hope to make data collection and computational tasks accessible to any student or researcher regardless of computing background. As we build this tutorial, please comment and post questions on any of the included computational science topics - we're here to help!
Scientific conclusions are made by domain scientists, often with decades of experience. Specific domain science questions are out of our scope, but perhaps we can point you to your nearest expert.
- B. Dzwonkowski, S. Fournier, G. Lockridge, J. Coogan, Z. Liu, and K. Park. Hurricane Sally (2020) Shifts the Ocean Thermal Structure across the Inner Core during Rapid Intensification over the Shelf. Journal of Physical Oceanography, 52(11), 2841-2852.
- Le, C., Y. Gao, W-J. Cai, J. Lehrter, Y. Bai, and Z-P. Jiang. Estimating summer sea surface pCO2 on a river-dominated continental shelf using a satellite-based semi-mechanistic model. Remote Sensing of Environment, 225, 115-126.
This effort is funded by NASA's Transform to Open Science Training (TOPST) program under award 80NSSC23K0863 to North Carolina State University with University of South Alabama.
See the Proposal Summary for more details. The full proposal submitted for the award is on Zenodo:
