Recovering of local magnetic K-indices from global magnetic Kp-indices using neural networks: an application to Antarctica

• Published in: Annals of Geophysics
• Main Authors: Segarra, Antoni, Curto, Juan José
• Format: Article in Journal/Newspaper
• Language: English
• Published: Istituto Nazionale di Geofisica e Vulcanologia, INGV 2015
• Subjects: K-index; Neural networks; Local magnetic indices; Antarctica; 04.05.03. Global and regional models; 05.01.02. Cellular automata; fuzzy logic; genetic alghoritms; 05.07.01. Solar-terrestrial interaction; Antarc*
• Online Access: https://www.annalsofgeophysics.eu/index.php/annals/article/view/6719; https://doi.org/10.4401/ag-6719

This paper describes a method to obtain local magnetic index, K, from the global index, Kp. Until now, however, for the cases of areas without magnetic observatories, to estimate the geomagnetic activity there, global indices were the only option. The methodology that we used to estimate local index was based on neural networks. This tool has a great potential for processing information from complex systems as in the case of the geomagnetic system. Local K index calculated with this method resulted to be a better option than directly using the global index Kp when we need an indicator of geomagnetic activity in a specific area. The best results of our method were for moderate and high geomagnetic activity, which are of major interest in Space Weather.