An assessment study of the wavelet-based index of magnetic storm activity (WISA) and its comparison to the Dst index

Xu, Zhonghua; Zhu, L.; Sojka, J. J.; Kokoszka, Piotr; Jach, A

doi:10.1016/j.jastp.2008.05.007

Cited by 28 publications

(26 citation statements)

References 16 publications

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“…The reason for using the discrete wavelet methodology instead of a Fourier transform, as explained by Xu et al (2008), is due to the geomagnetic data containing several different kinds of variations with various spectral ranges which are related to complex current systems in the ionosphere and magnetosphere. On the one hand, the Fourier transform has been a traditional tool to analyze geophysical data.…”

Section: Methodsmentioning

confidence: 99%

“…As an alternative to the traditional Dst index (Sugiura, 1964), new indexes were developed using DWT, such as the wavelet-based index of storm activity (WISA; Jach et al, 2006;Xu et al, 2008) and Wp (Nosé et al, 2012), among others. Motivated by the works of Mendes et al (2005), Mendes da Costa et al (2011), Hafez et al (2013) and Klausner et al (2014aKlausner et al ( , b, 2016a, which use the DWT to detect transition regions and to localize singularities in geophysical data, in this work, the geomagnetic variation associated with the events of CIRs and HSSs in 2007 will be analyzed.…”

Section: Klausner Et Al: Analysis To Identify Local Geomagneticalmentioning

confidence: 99%

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An alternative way to identify local geomagnetically quiet days: a case study using wavelet analysis

et al. 2016

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Abstract. This paper proposes a new method to evaluate geomagnetic activity based on wavelet analysis during the solar minimum activity (2007). In order to accomplish this task, a newly developed algorithm called effectiveness wavelet coefficient (EWC) was applied. Furthermore, a comparison between the 5 geomagnetically quiet days determined by the Kp-based method and by wavelet-based method was performed. This paper provides a new insight since the geomagnetic activity indexes are mostly designed to quantify the extent of disturbance rather than the quietness. The results suggest that the EWC can be used as an alternative tool to accurately detect quiet days, and consequently, it can also be used as an alternative to determine the Sq baseline to the current Kp-based 5 quietest days method. Another important aspect of this paper is that most of the quietest local wavelet candidate days occurred in an interval 2 days prior to the high-speed-stream-driven storm events. In other words, the EWC algorithm may potentially be used to detect the quietest magnetic activity that tends to occur just before the arrival of high-speed-stream-driven storms.

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Section: Methodsmentioning

confidence: 99%

Section: Klausner Et Al: Analysis To Identify Local Geomagneticalmentioning

confidence: 99%

An alternative way to identify local geomagnetically quiet days: a case study using wavelet analysis

et al. 2016

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“…During magnetic storms they contain uneven local features occurring at random times and carrying important information on the processes in the magnetosphere [2][3][4][5][6][7][8][9][10][11][12][13][14]. 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.…”

Section: Introductionmentioning

confidence: 99%

“…In the paper [2] wavelet transform is applied to investigate the relations between short-period oscillations of the geomagnetic field, solar wind parameters and interplanetary field during geomagnetic storms. Based on the wavelet transform, we solve such problems as denoising and elimination of a periodic component from geomagnetic field variations which is caused by the Earth rotation [4]. Applying the discrete wavelet transform, the authors of the paper [3] suggested an algorithm for automatic detection of magnetic storm initial stage periods.…”

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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“…The magnetic field variations have a complex structure, and they consist of non-smooth local features of varying amplitude and duration in disturbed periods [1][2][3][4][5][6][7]. Analysis of formed local structures allows us to receive the information about the intensity and dynamics of geomagnetic disturbance development in the detail [2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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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An assessment study of the wavelet-based index of magnetic storm activity (WISA) and its comparison to the Dst index

Cited by 28 publications

References 16 publications

An alternative way to identify local geomagnetically quiet days: a case study using wavelet analysis

An alternative way to identify local geomagnetically quiet days: a case study using wavelet analysis

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

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

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