Speaker: Jacob Bortnik
Institution: UCLA Atmospheric & Oceanic Sciences
We are all space travelers. We live aboard “spaceship Earth” that travels about the Sun at a dazzling speed, enjoying its life-giving light and warmth, but subjected to its frequent outbursts: solar flares, energetic particles, and clouds of plasma averaging over a trillion kilograms in mass that are ejected towards the Earth at speeds that are hundreds of times faster than a speeding bullet. The effects of this space environment on our technological systems is known as “space weather” and we are currently more vulnerable to space weather than ever before, as we launch an unprecedented number of satellites into orbit around the Earth, build ever longer pipelines, and enjoy electrical power grids that are interconnected across entire continents. Fortunately, we are also collecting more data than ever before, observing the Sun and the Earth in unprecedented detail, and running sophisticated numerical models to help us understand our observations, which create more data ... but what to do with all that data? In this talk, we review some of the essentials of space weather, and discuss novel ways in which the power of machine learning can be harnessed to understand, specify, and even predict what our temperamental star next door might do.