Abstract
We assess the predictive capabilities of various classes of avalanche models for solar flares. We demonstrate that avalanche models cannot generally be used to predict specific events because of their high sensitivity to the embedded stochastic process. We show that deterministically driven models can nevertheless alleviate this caveat and be efficiently used for predictions of large events. Our results suggest a new approach for predictions of large (typically X-class) solar flares based on simple and computationally inexpensive avalanche models.
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Acknowledgements
The authors thank an anonymous referee for valuable comments. The authors acknowledge stimulating discussions during the ISSI Workshops on Turbulence and Self-Organized Criticality (2012 – 2013) held in Bern, Switzerland; and during the “Festival de théorie” (2013) held in Aix-en-Provence, France. This research has made use of SunPy , an open-source and free community-developed solar data analysis package written in Python (Mumford et al., 2013). AS acknowledges financial support from CNES via a Solar Orbiter grant. We also acknowledge support from the Natural Sciences and Engineering Research Council of Canada.
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Strugarek, A., Charbonneau, P. Predictive Capabilities of Avalanche Models for Solar Flares. Sol Phys 289, 4137–4150 (2014). https://doi.org/10.1007/s11207-014-0570-2
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DOI: https://doi.org/10.1007/s11207-014-0570-2