Method for determining the geomagnetic activity index based on wavelet packets

Mandrikova, Oksana; Смирнов, С. Э.; Solovev, Igor

doi:10.1134/s0016793211060107

Cited by 11 publications

(15 citation statements)

References 1 publication

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“…To extract geomagnetic pulsations, following the results of [4,18], we used the expansion of the geomagnetic field variation into wavelet packets:…”

Section: Extraction Of Geomagnetic Pulsationsmentioning

confidence: 99%

“…Authors [12] proposed an algorithm for the interplanetary magnetic field processing and the Dst-index computation by neural networks. Authors of the present paper developed a method for magnetic data analysis based on the wavelet transform [4,18]. The method allows them to receive the information about the dynamics of geomagnetic field disturbances during magnetic storms.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of magnetic data of ground station network during strong magnetic storms

et al. 2017

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Abstract. The paper suggests a new technique for magnetic data analysis to detect and to estimate short-time anomalous increases in geomagnetic disturbance intensity. Based on the technique and applying the data of meridionally arranged stations in the north-east of Russia («Kotel'nyi» KTN, «Tixi» TIX, «Chokurdakh» CHD, «Zyryanka» ZYK, «Mys Shmidta» CPS, «Yakutsk» YAK, «Magadan» MGD, «Paratunka» PET, «Khabarovsk» KHB) and the near equatorial Indian stations ("Hyderabad" HYB and "Choutuppal" CPL), we analyzed the geomagnetic field variations during strong magnetic storms. This approach allowed us to detect simultaneously occurring local increases in geomagnetic activity observed a few hours before events and during the main phases of magnetic storms.

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“…To extract geomagnetic pulsations, following the results of [4,18], we used the expansion of the geomagnetic field variation into wavelet packets:…”

Section: Extraction Of Geomagnetic Pulsationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of magnetic data of ground station network during strong magnetic storms

et al. 2017

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“…The use of traditional methods and approaches does not allow us to research the rapidly-variable structure of geomagnetic field variations in detail and leads to the loss of meaningful information. One of the most effective modern methods of data analysis is the wavelet transform [3][4][5][6][7][8].The wavelet transform is now successfully used for the tasks of denoising the geomagnetic data [4,6,8], extraction of the periodic components caused by the Earth's rotation [4 ,8], search for the precursors of intense solar flares [3], automatic detection of magnetic storm development [8], studying of the characteristics of solar daily variations based on data from ground-based magnetic stations [7], automation of geomagnetic activity indices calculation such as K-index [9,10], Dst-index and wavelet based index of storm activity «WISA» [4,8] as well as several other issues. This mathematical apparatus is taken as the basis for the study.…”

Section: Introductionmentioning

confidence: 99%

“…Earlier, the authors in the works [9,10] proposed a geomagnetic field variation model (FVM) based on wavelets. It allows describing both the characteristic variations and nonstationary short-period changes characterizing fast processes in the magnetosphere.…”

Section: Introductionmentioning

confidence: 99%

Detection and analysis of short-period geomagnetic perturbations during increased solar activity and magnetic storms

2018

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The dynamics of geomagnetic field variations on the eve and during the periods of magnetic storms of 2015 and 2017 has been studied (data of the horizontal component of the Earth's magnetic field of the terrestrial station network were used). The method developed by the authors based on wavelet transform and adaptive threshold functions was applied. Weak geomagnetic disturbances synchronously appearing at the stations and preceding the onset of strong magnetic storms was extracted. The correlation of the isolated geomagnetic disturbances with the AEindex is shown, both in the occurrence times and in intensities. On the basis of comparison with interplanetary environment data (interplanetary magnetic field data and the solar wind parameters were analyzed), and also based on the results of other author works [1,2]. we assume that the isolated effects have solar nature.

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“…Traditional methods for data analysis applying basic models of time series, different techniques of smoothing and Fourier analysis methods are not effective enough to investigate fast unsteady processes. As it was noted in the papers [15][16][17][18], they do not allow one to identify thin local features characterizing short-period oscillations during increased geomagnetic activity and to estimate their dynamic characteristics before and during storms. At present, modern mathematic methods and technologies are intensively developing in this area [3-9, 14, 18-25].…”

Section: Introductionmentioning

confidence: 99%

Method of analysis of geomagnetic data based on wavelet transform and threshold functions

Mandrikova¹,

Solovev²,

Khomutov³

et al. 2017

Collection of Selected Papers of the III International Conference on Information Technology and Nanotechnology

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The suggested method is aimed at studying the dynamics of the magnetospheric current systems during magnetic storms. The method is based on algorithmic solutions for processing of geomagnetic field variations, detection of local increases in geomagnetic disturbance intensity and estimation of their dynamic characteristics. Parameters of the algorithms allow us to evaluate the characteristics of small-scale local features emerging during geomagnetic activity slight increases and large-scale variations observed during magnetic storms. To evaluate the method, geomagnetic data from the stations located in the north-east of Russia and equatorial India were used. The method testing showed the possibility to apply it for the detection of pre-storm anomalous effects in geomagnetic data.

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Method for determining the geomagnetic activity index based on wavelet packets

Cited by 11 publications

References 1 publication

Analysis of magnetic data of ground station network during strong magnetic storms

Analysis of magnetic data of ground station network during strong magnetic storms

Detection and analysis of short-period geomagnetic perturbations during increased solar activity and magnetic storms

Method of analysis of geomagnetic data based on wavelet transform and threshold functions

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