Prediction of solar cycle 24 and beyond

Hiremath, K. M.

doi:10.1007/s10509-007-9728-9

Cited by 54 publications

(27 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Autoregressive forecasts are also classified as spectral. Representative examples are given by Kane (1999), Duhau (2003), De Meyer (2003), Clilverd et al (2006), andHiremath (2008).…”

Section: Introductionmentioning

confidence: 99%

Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24

Uzal¹,

Piacentini²,

Verdes³

2012

Sol Phys

View full text Add to dashboard Cite

In this work we predict the maximum amplitude, its time of occurrence, and the total length of Solar Cycle 24 by linear regression to the curvature (second derivative) at the preceding minimum of a smoothed version of the sunspots time series. We characterise the predictive power of the proposed methodology in a causal manner by an incremental incorporation of past solar cycles to the available data base. In regressing maximum cycle intensity to curvature at the leading minimum we obtain a correlation coefficient R ≈ 0.91 and for the upcoming Cycle 24 a forecast of 78 (90% confidence interval: 56 -106).Ascent time also appears to be highly correlated to the second derivative at the starting minimum (R ≈ -0.77), predicting maximum solar activity for October 2013 (90% confidence interval: January 2013 to September 2014). Solar Cycle 24 should come to an end by February 2020 (90% confidence interval: January 2019 to July 2021), although in this case correlational evidence is weaker (R ≈ -0.56).

show abstract

“…Autoregressive forecasts are also classified as spectral. Representative examples are given by Kane (1999), Duhau (2003), De Meyer (2003), Clilverd et al (2006), andHiremath (2008).…”

Section: Introductionmentioning

confidence: 99%

Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24

Uzal¹,

Piacentini²,

Verdes³

2012

Sol Phys

View full text Add to dashboard Cite

show abstract

“…Many other predictions obtained applying the empirical or combined methods are within this span (Schatten 2003(Schatten , 2005Kane 2007b), just below our lower limit (Svalgaard et al 2005;Javaraiah 2007), slightly above our higher limit (Lantos 2006a;Du & Du 2006;Hiremath 2008), or significantly above it (Kane 2007a). Our prediction is in qualitative agreement with a forecast based on a dynamo model Jiang et al 2007).…”

Section: Summary Discussion and Conclusionmentioning

confidence: 50%

“…24) the empirical methods predict lower amplitudes (Schatten 2005;Svalgaard et al 2005;Du & Du 2006;Javaraiah 2007;Hiremath 2008) and the methods based on dynamo models higher amplitudes Dikpati et al , 2008b. However, this distinction is not a strict one, and in both classes of methods opposite examples can be found.…”

Section: Introductionmentioning

confidence: 99%

On solar cycle predictions and reconstructions

Brajša

Wöhl

Hanslmeier

et al. 2009

A&A

View full text Add to dashboard Cite

Context. Generally, there are two procedures for solar cycle predictions: the empirical methods -statistical methods based on extrapolations and precursor methods -and methods based on dynamo models. Aims. The goal of the present analysis is to forecast the strength and epochs of the next solar cycle, to investigate proxies for grand solar minima and to reconstruct the relative sunspot number in the Maunder minimum. Methods. We calculate the asymmetry of the ascending and descending solar cycle phases (Method 1) and use this parameter as a proxy for solar activity on longer time scales. Further, we correlate the relative sunspot numbers in the epochs of solar activity minima and maxima (Method 2) and estimate the parameters of an autoregressive moving average model (ARMA, Method 3). Finally, the power spectrum of data obtained with the Method 1 is analysed and the Methods 1 and 3 are combined. Results. Signatures of the Maunder, Dalton and Gleissberg minima were found with Method 1. A period of about 70 years, somewhat shorter than the Gleissberg period was identified in the asymmetry data. The maximal smoothed monthly sunspot number during the Maunder minimum was reconstructed and found to be in the range 0-35 (Method 1). The estimated Wolf number (also called the relative sunspot number) of the next solar maximum is in the range 88-102 (Method 2). Method 3 predicts the next solar maximum between 2011 and 2012 and the next solar minimum for 2017. Also, it forecasts the relative sunspot number in the next maximum to be 90 ± 27. A combination of the Methods 1 and 3 gives for the next solar maximum relative sunspot numbers between 78 and 99. Conclusions. The asymmetry parameter provided by Method 1 is a good proxy for solar activity in the past, also in the periods for which no relative sunspot numbers are available. Our prediction for the next solar cycle No. 24 is that it will be weaker than the last cycle, No. 23. This prediction is based on various independent methods.

show abstract

“…This fact is also true for sunspot data of the well-known Greenwich Photo-heliographic Results from which many controversial results, such as the cycle variation of rotation rates or meridional circulation, are used to explain the origin of the solar cycle from the so-called flux transport dynamo mechanism. This despite the fact that these mechanisms are questionable (Hiremath 2008.…”

Section: Estimation Of Errors In Positional Measurementsmentioning

confidence: 99%

Abnormal rotation rates of sunspots and durations of associated flares

Suryanarayana

Hiremath

Bagare

et al. 2015

A&A

Self Cite

View full text Add to dashboard Cite

Context. Short-duration and long-duration flares are important in terms of their association with coronal heating and coronal mass ejections, respectively. Sunspot motions in the photosphere have been known to be associated with flare occurrences. Aims. We study the association between the abnormal rotation rates (longitudinal displacement in a given latitude in contrast with the rotation of spots around their umbral centre) of sunspots and flare duration. Methods. We compute the rotation rates of sunspots for different days during their evolution. We consider rotation rates that are in excess of one standard deviation as abnormal rotation rates. Also, the duration of time between the initial and final stages of the flares are computed. Results. Using Kodaikanal Observatory white light picture and GOES soft X-ray flare data, we find that a good association with a high significance exists between abnormal rotation rates of sunspots and flare durations. In contrast, we find that duration of flare is independent of sunspot area. Conclusions. The present study suggests that sub-surface dynamics plays a dominant role in determining the duration and rate of dissipation of energy during flares.

show abstract

Prediction of solar cycle 24 and beyond

Cited by 54 publications

References 37 publications

Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24

Predictions of the Maximum Amplitude, Time of Occurrence, and Total Length of Solar Cycle 24

On solar cycle predictions and reconstructions

Abnormal rotation rates of sunspots and durations of associated flares

Contact Info

Product

Resources

About