2017
DOI: 10.1002/2016ea000217
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Analysis of supersubstorm events with reference to polar cap potential and polar cap index

Abstract: The coupling process between solar wind-magnetosphere-ionosphere is an important physical 14 mechanism for the delineating concept of the magnetosphere-ionosphere system. In this work, we have studied the polar cap potential (PCV) and merging electric field (E m ) during three different supersubstorm (SSS) events. We have also studied the roles of polar cap index and auroral electrojet (AE) indices to observe polar cap activity during SSSs. To substantiate results, wavelet transform and cross-correlation techn… Show more

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Cited by 27 publications
(31 citation statements)
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References 54 publications
(118 reference statements)
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“…Stasiewicz and Potemra [] studied satellite observation and revealed that the magnetospheric FACs show highly complex and variable structures, where current density may vary from a few to several hundred μAm −2 . Adhikari et al [] studied supersubstorm events (on 21 November 2001, 20 January 2005, and 24 August 2005) and found that maximum polar cap potential (PCV) is ~1700 keV with merging electric field ( E m ) ~40 mVm. They found singularity and discontinuity on PCV for SSS events.…”
Section: Resultsmentioning
confidence: 99%
“…Stasiewicz and Potemra [] studied satellite observation and revealed that the magnetospheric FACs show highly complex and variable structures, where current density may vary from a few to several hundred μAm −2 . Adhikari et al [] studied supersubstorm events (on 21 November 2001, 20 January 2005, and 24 August 2005) and found that maximum polar cap potential (PCV) is ~1700 keV with merging electric field ( E m ) ~40 mVm. They found singularity and discontinuity on PCV for SSS events.…”
Section: Resultsmentioning
confidence: 99%
“…In order to analyze the local disturbances in the signal, we took Daubechies wavelet coefficients (Gonzalez et al, 1994, Kalausner et al, 2014. The advantage of this method is it can detect the first order disturbances along with its derivatives (Adhikari & Chapagain, 2016). DWT is not only used to find the change in signal but also to detectthe singularities present in signals.…”
Section: Discrete Wavelet Transform (Dwt)mentioning
confidence: 99%
“…In this transformation a continuous signal is expressed into wavelets (Grassmann & Morlet, 1983;Adhikari & Chapagain, 2016). The CWT coefficientisis defined as W (a, b) = ʃ f(t) ((t -b)/a) dt; Where represents the complex conjugate of and the parameters a and b are scaling and shifting factors respectively and W (a, b) gives the values of the coefficients.…”
Section: Continuous Wavelet Transform (Cwt)mentioning
confidence: 99%
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