Development of near real time and cumulative GIC proxy indices.
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Geomagnetic storms are phenomena which can give rise to geomagnetically induced currents (GICs), which have an adverse effect on technology in that they can cause anomalous low frequency currents that damage critical infrastructure. The problems with quantifying the damage in the absence of accurate GIC data (which can show the level of damage) are twofold, namely, for near real-time applications and the other for long-term applications respectively. Since GIC data is not easily available due to power utilities either not having measuring devices or not allowing its dissemination readily, other methods of quantifying damage as unambiguously as possible using data from more attainable sources such as local magnetometer stations, are necessary improvements that can be made. Attempts are made in this work, using an algorithm similar to that of Wintoft et al. , to address these problems via the creation of two GIC proxies to, in the case of near-real time applications, track damage, and in the long-term case, by combining ideas from Yu and Ridley  as well as Lotz and Danskin , to indicate damage incurred during storms. Using these algorithms, results are acquired by making use of Pearson’s correlation and graphical methods, although the data set is too small to draw statistically significant conclusions. The results from the short-term index show that the index works well with the best indicators of shortterm behaviour available as well as GIC data from power stations in South Africa. The results from the long-term index corroborates with the literature, in that damage done in long, yet less intense events can can be as significant as damage done by short-term, yet highly intense events, as reported by Lotz and Danskin .