2025
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3D Enlil Visualization Transition to Forecasting Center’s Proving Grounds
This follow-on project aims to transition the Enlil 3D visualization for the purpose of working with NOAA SWPC, CCMC, and M2M to carry out initial operational capability validation and transition. The previous project developed a capability that space weather forecasters have requested for use in operations.
2024
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Enhanced Data Products for the GOES-R Energetic Heavy Ion Sensor (SEISS/EHIS)
This project aims to improve the understanding of, and preparedness for, the disproportionate space weather impacts of energetic heavy ions from Solar particle events (SPEs) and galactic cosmic rays (GCRs). Examples of these impacts include Single Event Effects (SEEs) in space-based electronics and elevated radiation dosages for humans in space.
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Machine Learning-Enabled Data Assimilation for Understanding and Forecasting the Variation of Thermospheric Neutral Density
This research project aims to accomplish the development of accurate and reliable forecasting models for thermospheric neutral density under both storm and quiet conditions, as well as investigating and understanding the intricate relationship between solar emissions and the variation of neutral density. To accomplish these objectives, the project will establish and innovative Machine Learning-enabled data assimilation framework for neutral density forecasting.