Space weather caused by structures and irregularities in Earthâ€™s ionosphere can disrupt transmission of Global Navigation Satellite System signals critical for precise positioning, navigation and timing, and can influence propagation of trans-ionospheric radio waves used in land-satellite communication. Despite decades of work, forecasting this space weather phenomenon remains a challenge. This project advances fundamental research underpinning such forecasts by establishing integrated models of ionosphere-thermosphere conditions that lead to ionospheric plasma irregularities. Novel data-assimilation techniques and uncertainty quantification methods are applied to estimate uncertainties in model predictions. Spatial and temporal variations of simulated ionosphere-thermosphere parameters are validated with ground- and satellite-based observations. The project team includes both senior and early-career scientists with expertise in space physics as well as software engineers and a graduate student. Collaborations with the UK, Japan, and Taiwan expand the availability and dissemination of the models and code. The improved models will be adopted into the operational version at NOAA Space Weather Prediction Center. This project directly addresses objectives in the National Space Weather Strategy and Action Plan and the National Strategic Computing Initiative Update.
The project improves the coupled whole atmosphere model and ionosphere-plasmasphere electrodynamics model (WAM-IPE) with high resolution capability (10s of km) using the Cornell ionospheric dynamics model. The data assimilation scheme address uncertainty in external forcing especially solar EUV irradiance and high-latitude heating associated with geomagnetic activity, and constrain the large-scale ionosphere-thermosphere dynamics while preserving small-scale perturbations generated by WAM-IPE without requiring unrealistic local adjustments. Highly scalable uncertainty quantification strategies based on low rank approximations are adopted and extended to estimate the model prediction uncertainties in the presence of high-dimensional input uncertainty. Key science questions investigated here include: can the high-resolution global model generate the range of scales driving plasma irregularities at low- and mid-latitudes; which parts of the spectrum of waves and background ionosphere-thermosphere conditions lead to the formation of plasma irregularities; and what are the key drivers controlling model parameters and their uncertainty?
This award is made as a part of the joint NSF-NASA pilot program on Next Generation Software for Data-driven Models of Space Weather with Quantified Uncertainties (SWQU). All software developed as a result of this award will be made available by the awardee free of charge for non-commercial use; the software license will permit modification and redistribution of the software free of charge for non-commercial use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.