Application of the SP algorithm to the INTERMAGNET magnetograms of the disturbed geomagnetic field

Abstract

The algorithmic system developed in the Laboratory of Geoinformatics at the Geophysical Cen ter, Russian Academy of Sciences, which is intended for recognizing spikes on the magnetograms from the global network INTERMAGNET provides the possibility to carry out retrospective analysis of the magneto grams from the World Data Centers. Application of this system to the analysis of the magnetograms allows automating the job of the experts-interpreters on identifying the artificial spikes in the INTERMAGNET data. The present paper is focused on the SP algorithm (abbreviated from SPIKE) which recognizes artificial spikes on the records of the geomagnetic field. Initially, this algorithm was trained on the magnetograms of 2007 and 2008, which recorded the quiet geomagnetic field. The results of training and testing showed that the algorithm is quite efficient. Applying this method to the problem of recognizing spikes on the data for periods of enhanced geomagnetic activity is a separate task. In this short communication, we present the results of applying the SP algorithm trained on the data of 2007 to the INTERMAGNET magnetograms for 2003 and 2005 sampled every minute. This analysis shows that the SP algorithm does not exhibit a worse per formance if applied to the records of a disturbed geomagnetic field.

On the feasibility of routine baseline improvement in processing of geomagnetic observatory data

“…It was found out experimentally that during the year the baseline value F b 0 for the total field intensity record was constant and equal to -5.5 nT. As the input data for the developed algorithm, we used the min variations of the components and the EMF modulus record, cleaned from anthropogenic disturbances using the algorithms (Bogoutdinov et al 2010;Soloviev et al 2012a, b;Sidorov et al 2012), as well as the absolute observations after outlier removal. In the calculations, the confidence factor λ was set equal to 0.5; the observed baseline values, if done more than once a day, were averaged and bound to a nearest whole hour.…”

The Study of Time Series Using the DMA Methods and Geophysical Applications

“…The approach to the studying of time series based on fuzzy logic, proposed in the paper, is largely focused on this challenge and finds its practical application. In particular, several algorithms based on DMA (Soloviev et al 2009;Bogoutdinov et al 2010;Soloviev et al 2012;Sidorov et al 2012;Zelinskiy et al 2014) are integrated into Russian-Ukrainian Geomagnetic Data Center (http://geomag.gcras.ru) and used for continuous automated detection of anthropogenic disturbances and geomagnetic pulsations in observatory data. Further research plans include, first of all, the expansion of analysis from a single time series f to a network S of time series f s (t), s ∈ S. This will allow to define the monitoring of activity in network, anomalous events in network, and more.…”

ULF wave power index for space weather and geophysical applications: A review

“…Algorithmic DMA approach enabled one to recognize low-amplitude geomagnetic pulsations of different types and their time limits [Zelinskiy et al, 2014]. What is important in our studies is that DMA-based methods have been implemented for an automated and unified anthropogenic anomaly recognition, such as spikes and jumps, in magnetograms from ground and satellite magnetometers [Bogoutdinov et al, 2010;Sidorov et al, 2012;Soloviev et al, 2009Soloviev et al, , 2012aSoloviev et al, , 2012b. These methods are applicable to both 1-minute and 1-second recordings, and are capable to operate continuously providing large data streams processing with high degree of reliability.…”