Forecasting the Remaining Duration of an Ongoing Solar Flare
arXiv:2103.03957 · doi:10.1029/2021SW002754
Abstract
The solar X-ray irradiance is significantly heightened during the course of a solar flare, which can cause radio blackouts due to ionization of the atoms in the ionosphere. As the duration of a solar flare is not related to the size of that flare, it is not directly clear how long those blackouts can persist. Using a random forest regression model trained on data taken from X-ray light curves, we have developed a direct forecasting method that predicts how long the event will remain above background levels. We test this on a large collection of flares observed with GOES-15, and show that it generally outperforms simple linear regression. This forecast is computationally light enough to be performed in real time, allowing for the prediction to be made during the course of a flare.
arXiv commentResubmitted to Space Weather. Comments welcome!
References in corpus (8)
- Scikit-learn: Machine Learning in Python
- SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
- Magnetic Properties of Solar Active Regions that Govern Large Solar Flares and Eruptions
- Soft X-ray Pulsations in Solar Flares
- The Thermal Properties of Solar Flares Over Three Solar Cycles Using GOES X-ray Observations
- Statistical Study of GOES X-ray Quasi-Periodic Pulsations in Solar Flares
- Lyman-alpha Variability During Solar Flares Over Solar Cycle 24 Using GOES-15/EUVS-E
- What determines the X-ray intensity and duration of a solar flare?