Federal Project Grant Award Summary

The National Science Foundation's Division of Atmospheric and Geospace Sciences awarded The Johns Hopkins University a $300,000 Project Grant (CFDA 47.050, Geosciences program) effective July 1, 2026 through June 30, 2028. This EAGER (Early-concept Grants for Exploratory Research) award supports development of a machine learning (ML)-based geomagnetic field reconstruction framework designed to improve quantitative modeling of Earth's magnetosphere during magnetic storms. The project addresses significant limitations of traditional empirical models by leveraging advanced data mining techniques to identify and reconstruct magnetic field configurations with greater spatial and temporal fidelity than existing Tsyganenko models.

The primary deliverables include next-generation empirical geomagnetic field algorithms, open-source software tools, precomputed field reconstructions, and user-friendly applications accessible to the broader space science research community. By making computationally advanced ML-based methods broadly available through public platforms and documentation, the project aims to democratize access to high-fidelity magnetospheric field reconstructions and enhance space weather prediction capabilities. The work will be performed at Johns Hopkins University's Applied Physics Laboratory in Laurel, Maryland, leveraging the institution's extensive experience in space science research and federal partnerships.