A K Singh
Articles written in Journal of Earth System Science
Volume 125 Issue 5 July 2016 pp 899-908
Space weather prediction involves advance forecasting of the magnitude and onset time of major geomagneticstorms on Earth. In this paper, we discuss the development of an artificial neural network-basedmodel to study the precursor leading to intense and moderate geomagnetic storms, following halo coronalmass ejection (CME) and related interplanetary (IP) events. IP inputs were considered within a 5-daytime window after the commencement of storm. The artificial neural network (ANN) model training,testing and validation datasets were constructed based on 110 halo CMEs (both full and partial halo andtheir properties) observed during the ascending phase of the 24th solar cycle between 2009 and 2014. Thegeomagnetic storm occurrence rate from halo CMEs is estimated at a probability of 79%, by this model.
Volume 126 Issue 7 October 2017 Article ID 0101
Magnetovariational studies were carried out along four different EW profiles in Saurashtra region in different phases, during January 2007–March 2012. Transient geomagnetic field variations (X, Y horizontal field and Z vertical field components) recorded along these profiles are analyzed to infer the electrical conductivity distribution of the region. The vertical field transfer functions which depict the characteristics of electrical conductivity distribution are presented in the form of induction arrows. From the spatial distribution of these arrows, it is inferred that the sediments filling the offshore basins have more conductivity than those basins in Saurashtra region.