The efficient transfer of energy from solar wind into the Earth’s magnetic field causes geomagnetic storms. The resulting variations in the magnetic field increase errors in magnetic navigation. The disturbance-storm-time index, or DST, is a measure of the severity of the geomagnetic storm. As a key specification of the magnetospheric dynamics, the Dst index is used to drive geomagnetic disturbance models. Additionally, magnetic surveyors, government agencies, academic institutions, satellite operators, and power grid operators use the Dst index to analyze the strength and duration of geomagnetic storms. Over the past three decades, several models were proposed for solar wind forecasting of Dst, including empirical, physics-based, and machine learning approaches. While the ML models generally perform better than models based on the other approaches, there is still room to improve, especially when predicting extreme events. NOAA is asking the crowd to develop models for forecasting Dst that push the boundary of predictive performance, under operationally viable constraints, using the real-time solar-wind data feeds from NOAA’s DSCOVR and NASA’s ACE satellites.
Partner Organization: NOAA
Awards: $30,000 in total prizes
Open Date: December 15, 2020
Close Date: February 12, 2021
Frequency: Once
For more information, visit: https://www.drivendata.org/competitions/73/noaa-magnetic-forecasting/