2015
DOI: 10.1002/2014ja020661
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Systematic averaging interval effects on solar wind statistics

Abstract: The choice of interval of averaging in computing statistics of solar wind fluctuations is known to be a sensitive issue in which the need for adequate sampling statistics must be balanced with the complications of establishing an ensemble, given that the solar wind admits inhomogeneity, structure, and variability at its sources. Here we examine the quantitative dependence of interval of averaging (sample size) on estimates of basic statistics such as means, variances, and anisotropies of the measured interplan… Show more

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Cited by 51 publications
(45 citation statements)
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“…In this study we used the correlation time computed in Parashar et al (2019). However there are there are few subtleties associated with this calculation, and Smith et al (2001); Isaacs et al (2015); Krishna Jagarlamudi et al (2019); Bandyopadhyay et al (2019) offer more insights and discussion on this topic along with potential issues in such determination. We also carried out the analysis for various different averaging times (from 1 to 12 hours) and it was observed to have minimal affect on the outcome.…”
Section: Data Selection and Methodologymentioning
confidence: 99%
“…In this study we used the correlation time computed in Parashar et al (2019). However there are there are few subtleties associated with this calculation, and Smith et al (2001); Isaacs et al (2015); Krishna Jagarlamudi et al (2019); Bandyopadhyay et al (2019) offer more insights and discussion on this topic along with potential issues in such determination. We also carried out the analysis for various different averaging times (from 1 to 12 hours) and it was observed to have minimal affect on the outcome.…”
Section: Data Selection and Methodologymentioning
confidence: 99%
“…where δB(t) = B(t) − B , also for 1-day intervals 9 . The correlation scale, τ c , can be obtained from C(τ ) in various ways (e.g., Ruiz et al 2014;Isaacs et al 2015); here it was taken as the point where C decreases such that C(τ c ) = e −1 . The radial variation of the two outer scale estimates, τ b and τ c , is shown in Figure 9(a-b).…”
Section: Turbulence Outer Scalementioning
confidence: 99%
“…While the solar wind correlation time has been shown to depend on the length of the interval used to calculate it(Matthaeus & Goldstein 1982;Isaacs et al 2015;Krishna Jagarlamudi et al 2019), here we choose 1-day intervals as a reasonable compromise, and are more interested in its radial dependence than absolute value.…”
mentioning
confidence: 99%
“…At 150 Gm, typical values of the turbulent velocity Z(150 Gm) and correlation length L(150 Gm) are 25 km s −1 and 1 Gm, respectively (Ruiz et al 2014;Isaacs et al 2015). Both of these quantities are approximately log-normally distributed, soextreme outliers are to be expected.…”
Section: Fading Of the Striaementioning
confidence: 99%