Solar wind, a stream of charged particles emitted from the Sun, is a key driver of space weather at Earth and throughout the solar system. Extreme space weather events occur when disturbances in the Sun’s atmosphere, called coronal mass ejections (CMEs), reach the Earth’s magnetosphere. Space weather phenomena can create conditions hazardous for humans and instruments in space and on the ground. Accurately forecasting space weather is thus increasingly important for our technology-dependent society and will be critical while planning and operating missions to the Moon and Mars. This project will develop a new generation of software capable of near real-time modeling from the Sun to Earth's orbit (inner heliosphere) and predicting intense space weather events. The tools developed by this project can not only dramatically improve the accuracy and performance of currently operational space weather models, but also allow the broader scientific community to experiment with and extend these tools to create new capabilities that could eventually be transformational for operational activity. This work will also provide a leap forward in the computation and simulation of complex, turbulent plasma systems and is expected to have impact in several areas, including space physics and astrophysics. The project team includes both early-career and senior researchers at U.S. universities, NASA centers, national labs, and in the private sector; support for the non-academic collaborating institutions is to be provided by NASA.
The structuring of the solar wind into fast and slow streams is the source of recurrent geomagnetic activity. The largest geomagnetic storms are caused by CMEs propagating through and interacting with the solar wind. The connection of the interplanetary magnetic field to CME-related shocks and impulsive solar flares determines where solar energetic particles propagate. Therefore, data-driven modeling of stream interactions in the background solar wind, and CMEs propagating through it, is a necessary part of space weather forecasting. At present NOAA Space Weather Prediction Center forecasts the background solar wind and CME arrival times using empirically driven models. The goal of this project is to develop a data-driven, time-dependent model that will improve the current state of the art. The new model will consist of: 1) a surface flux transport model, 2) potential field solver, and 3) an MHD solar wind model. It will provide more accurate solutions and be scalable on massively parallel computing systems, including Graphic Processor Units. Products from this project will provide a leap forward in the computation and simulation of complex plasma systems involving multiple discontinuities. The developed software will also be useful for astrophysical problems possessing a distinct spherical geometry, including exoplanets, early sun, and sun-like stars.
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.
