<p>The last decade has truly witnessed the rise of the machine age. The enormous expansion of technology that can generate and&#160;manipulate massive amounts of information has transformed all aspects of society. Missions such as SDO and MMS, and numerical models such as the Space Weather Modeling Framework (SWMF) are now routinely generating terabytes of science data, far beyond what can be analyzed directly by humans. Fortunately, concurrent with this explosion in information has come the development of powerful capabilities, such as machine learning (ML) and artificial intelligence (AI), that can retrieve revolutionary new understanding and utility from the massive data sets.<span>&#160;</span></p><p><span>SOLSTICE (Solar Storms and Terrestrial Impacts Center) is a recently selected NASA/NSF DRIVE Center. It</span>&#160;will serve as the vanguard for&#160;developing and applying ML methods, which will then raise the capabilities of the entire community. We will combine&#160;next generation ML technology with our world-leading numerical models and the exquisite data from the space missions to make&#160;breakthrough advances in Heliophysics understanding and space weather capabilities, and then transition our technology to the&#160;CCMC for the benefit of all.</p><p>We use ML to attack Grand Challenge Problems that cover the major aspects of space weather science:&#160;(i) use interpretable deep learning models, archived solar observations and high-performance physics-based simulations to identify the&#160;onset mechanism of solar flares and coronal mass ejections; and&#160;(ii) use high-cadence observations and physics-based feature learning to predict solar storms many hours before eruption, training&#160;time-to-event models to predict event times and flare magnitudes using innovative machine learning techniques.</p>
The Space Weather Modeling Framework Goes Open Access
