Andy Sayer (616/UMBC) was a co-author on a paper and related presentations given at the GSFC's AI Center of Excellence (AICoE) seminar series. According to Dr. Sayer, "The AICoE is a cross-disciplinary umbrella hosting monthly seminars on diverse topics; featuring new collaboration and funding opportunities; advanced computational resources and technology; examples of AI applied to specific science problems; innovative methods for AI, ML, and deep learning for scientific discovery; and helpful co-learning workshops."
Further, "The paper outlines and demonstrates new methods to observed atmospheric and ocean properties from space. It enhances NASA's heritage approach in two main ways: (1) using a powerful statistical methodology called Optimal Estimation to provide uncertainty estimates and quality metrics on each retrieved quantity, and (2) using machine learning to speed up calculations and make the method more computationally practical for large-scale satellite data processing." The paper is led by Amir Ibrahim, a civil servant in the Ocean Ecology Laboratory (Code 616).
Ibrahim, A. (616/GSFC), B. Franz (616/GSFC), A. Sayer (616/UMBC), K. Knobelspiesse (616/GSFC), M. Zhang (616/SAIC), S. Bailey (616/GSFC), L. I. W. McKinna (Go2Q Pty, Ltd.), M. Gao (616/SSAI), and P. J. Werdell (616/GSFC) (2022), Optimal estimation framework for ocean color atmospheric correction and pixel-level uncertainty quantification, Appl. Opt., 61(22), 6453-6475, https://doi.org/10.1364/AO.461861.
Young-Kwon Lim of the GMAO at NASA GSFC also was a third-author of a recent publication:
Jeong, Y.-C. (Hanyang Univ.), S.-Y. Yeh (Hanyang Univ.), Y.-K. Lim (610.1/UMBC), A. Santoso (CSHOR), and G. Wang (CSHOR) (2022), Indian Ocean warming as key driver of long-term positive trend of Arctic Oscillation, NPJ (Nature Partner Journal) Clim. Atmos. Sci., 5(56), https://doi.org/10.1038/s41612-022-00279-x.