2012
DOI: 10.1029/2011ja017283
|View full text |Cite
|
Sign up to set email alerts
|

Is there long‐range memory in solar activity on timescales shorter than the sunspot period?

Abstract: [1] The sunspot number (SSN), the total solar irradiance (TSI), a TSI reconstruction, and the solar flare index (SFI) are analyzed for long-range persistence (LRP). Standard Hurst analysis yields H ≈ 0.9, which suggests strong LRP. However, solar activity time series are nonstationary because of the almost-periodic 11 year smooth component, and the analysis does not give the correct H for the stochastic component. Better estimates are obtained by detrended fluctuation analysis, but estimates are biased and err… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
15
0

Year Published

2013
2013
2020
2020

Publication Types

Select...
7

Relationship

1
6

Authors

Journals

citations
Cited by 16 publications
(17 citation statements)
references
References 22 publications
2
15
0
Order By: Relevance
“…In fact, they do not even have to belong to this wide class. It is sufficient that the process is stationary with finite second‐order structure function, which is a power‐law in the time lag [ Rypdal and Rypdal , ]. The Gaussian approximation is valid for deseasonalized surface temperature records, which are averaged over synoptic spatiotemporal scales (e.g., monthly means averaged over spatial scales 103 km).…”
Section: Introductionmentioning
confidence: 99%
“…In fact, they do not even have to belong to this wide class. It is sufficient that the process is stationary with finite second‐order structure function, which is a power‐law in the time lag [ Rypdal and Rypdal , ]. The Gaussian approximation is valid for deseasonalized surface temperature records, which are averaged over synoptic spatiotemporal scales (e.g., monthly means averaged over spatial scales 103 km).…”
Section: Introductionmentioning
confidence: 99%
“…2.3, if well-defined, the β exponent is related to the temporal correlations in the signal via simple formulas. In fact, for a (zero-mean) stationary process T (t) with −1 < β < 1 we have T (t)T (t + t) ∼ (β + 1)β t β−1 and for (a zero-mean) process with stationary increments and 1 < β < 3 we have T (t) T (t + t) ∼ (β − 1)(β − 2) t β−3 , where T (t) is the increment process of T (t) (Rypdal and Rypdal, 2012). Thus, the results presented so far in this paper do not rely on any assumptions of self-similar or multifractal scaling.…”
Section: A Note On Multifractal Processesmentioning
confidence: 99%
“…This preprocessing procedure allowed us to avoid a leakage effect where the LF parts influence HF parts and vice versa. A division into smooth and fluctuating parts such as this is often used (see, e.g., Rypdal & Rypdal 2012) but the breaking point is often chosen arbitrarily. Here we determined it with the optimization procedure.…”
Section: Preprocessingmentioning
confidence: 99%
“…Rypdal & Rypdal (2012) used amplitude detrending together with mean deterending to reveal stationary (or statistically stable) fluctuations. Envelopes, as we introduced above, can be used with the same goal.…”
Section: Envelopesmentioning
confidence: 99%