Bayesian approach for auroral oval reconstruction from ground-based observations

Naked eye observations of aurorae might be used to obtain information on the large-scale magnetic field of the Earth at historic times. Their abundance may also help bridge gaps in observational time-series of proxies for solar activity such as the sunspot number or cosmogenic isotopes. With information derived from aurora observations like observing site, time of aurora sighting and position on the sky we can reconstruct the auroral oval. Since aurorae are correlated with geomagnetic indices like the Kp index, it is possible to obtain information about the terrestrial magnetic field in the form of the position of the magnetic poles as well as the magnetic disturbance level. Here we present a Bayesian approach to reconstruct the auroral oval from ground-based observations by using two different auroral oval models. With this method we can estimate the position of the magnetic poles in corrected geomagnetic coordinates as well as the Kp index. The method is first validated on synthetic observations before it is applied to four modern geomagnetic storms between 2003 and 2017 where ground-based reports and photographs were used to obtain the necessary information. Based on the four modern geomagnetic storms we have shown, that we are able to reconstruct the pole location with an average accuracy of ≈2° in latitude and ≈11° in longitude. The Kp index can be inferred with a precision of one class. The future goal is to employ the method to historical storms, where we expect somewhat higher uncertainties, since observations may be less accurate or not favorably distributed.
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Journal of Atmospheric and Solar-Terrestrial Physics
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