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GEOMAGNETIC STUDIES AS PART OF THE MODELS REGARDING SPACE WEATHER AND CLIMATIC CHANGE
Abstract
Geomagnetic disturbances and their associated phenomena can be an important parameter as data input in climatology studies and climate change. This paper is a preamble to a deliverable "Development of a catalog on the typology of geomagnetic variations based on records from the Surlari Geomagnetic Observatory" within the Space Weather project which is part of the complex multidisciplinary project „Institutional capacities and services for research, monitoring and forecasting of risks in extra-atmospheric space” which includes eight institutions. The basic material from which we start, for the analysis of the transient geomagnetic field, was the digital recordings and the absolute measurements performed at the observatory. The processing of the observation material allows the differentiation of regular geomagnetic variations, due to the tidal movements of the Moon-Sun and the thermal movements of the upper atmosphere by the geomagnetic disturbances generated by the interaction between the magnetosphere and the solar wind. In both cases it is the relationship between the Earth's magnetic field and the conducting beds of the atmosphere, but the sources that provide it can be completely different. The first category includes the solar diurnal variation, which is the most important phenomenon. For the analysis of the magnetic activity, we calculated and used the three-hourly indices K, from the data registered at observatory and the planetary indices Kp by the specialized sites. In addition to global geomagnetic phenomena, which affect the entire planet but with different intensities, there are also individual phenomena highlighted based on data recorded at observatory. Regarding the methodology of data processing and interpretation, we used statistical, spectral and wavelet analyses. Also, we used Auto-Regressive Integrated Moving Average and Machine learning procedures to predict some phenomena. In this paper we refer to the processing, analysis and forecasting of some phenomena based on the data registered in this year within the observatory as well as the highlighting of some more important phenomena.
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