As we advance in the technological age our risk exposure to the space weather, severe storms in the near-Earth space environment driven by the complex magnetic field interactions at the Sun, continues to increase. The alterations in the ionized portion of the upper atmosphere driven by interaction of the complicated plasma and magnetic field structures emitted by the Sun, aka CMEs, and the Earth’s magnetic field can lead to significant degradations on the availability and accuracy of global positioning system (GPS). This interaction can also impact high-frequency (HF) radio communications forcing airlines to divert aircraft from trans-polar routings to longer lower latitude routes at significant costs. The severe storms can also drive strong currents in the electric power grid, potentially leading to blackouts, and long-distance pipelines, contributing to enhanced corrosion. Aspects of our understanding of the basic science behind these affects are quite good, but work remains to be done to create a robust, reliable, and effective set of forecast tools.
Modern modeling of space weather is accomplished through coupling of regional models of the thermosphere, ionosphere, and magnetosphere that can be driven by solar wind conditions taken from satellite observations or by the results of models of solar wind driven by solar coronal simulations. These numerical simulations can provide forecast of the space environment and are beginning to be transitioned into operations at NOAA’s Space Weather Prediction Center (SWPC) to provide information for government and industrial users. High Performance Computing (HPC) platforms allow simulations to be conducted at unprecedented resolution and over long simulation intervals. The large data sets produced by these simulations provide opportunities for novel discoveries through data mining. An excellent example of this discovery process is linkage of bursty bulk flows to magnetic reconnection in the mid-tail through high-resolution simulations. The future of space weather modeling includes many challenges. Key among these are the is the ability to predict the magnetic field inside the CME, utilization of new modeling techniques such as hybrid methods within the magnetospheric simulations, and development of a robust whole geospace model.