From Earth to the Edge of Space: How Data Assimilation Advances the Science and Engineering of Forecasting Near-Earth Space Environments

Prediction serves as the ultimate test of our scientific understanding of geophysical systems. Accurate forecasting of near-Earth space environmental conditions is critical to radio communication, navigation, and space traffic management. Effective numerical prediction of the region’s conditions allows us to better protect important space assets and related systems in the event of natural hazards. My research group aims to advance the science and engineering of forecasting, as applied to the Earth’s atmosphere extending from the ground to geospace. Prediction of the constantly changing near-Earth space environmental conditions – affected by both space and terrestrial weather – is inherently challenging. Data assimilation provides a systematic approach to integrating observations with first-principles models, extending the predictive capability of numerical models by reducing uncertainties in drivers and preconditions and constraining model dynamics with observations. The data assimilation and ensemble-based probabilistic modeling framework can also be applied to the design of future missions and the targeting of observations to maximize scientific returns of observing systems. This seminar showcases some of the latest data assimilation research and outlines future plans, setting the stage a discussion on how we can work together to advance the next generation of predictive modeling and observational strategies.