IN039-11
Near Real Time Forecasting of Ground Magnetic Fluctuations and Geomagnetically Induced Currents Risk Assessment

Tuesday, 15 December 2020: 18:00
Virtual
Cameron Lamarre, University of New Hampshire Main Campus, Durham, NH, United States, Amy M Keesee, University of New Hampshire, Physics and Space Science Center, Durham, NH, United States, Victor A Pinto, University of New Hampshire Main Campus, Institute for the Study of Earth, Oceans and Space, Durham, NH, United States, Michael Coughlan, University of New Hampshire, Physics, Durham, NH, United States and Hyunju KIM Connor, University of Alaska Fairbanks, Fairbanks, AK, United States
Abstract:
Geomagnetically Induced Currents (GIC) are a constant threat to technological systems, pipelines and the power grid. Although direct GIC measurements are scarce, accurate prediction of ground magnetic field fluctuations can provide valuable information to correctly assess GIC risk of occurrence. By combining near-real time data streamed from NOAA for solar wind particles and magnetic fields with our recently developed series of machine learning-based models for the prediction of dBH/dt at several ground magnetometer stations at high and mid-latitudes, we present our efforts to build a real-time forecasting and risk assessment online platform.
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