Study of Coronal Index Time Series Solar Activity Data in the Perspective of Probability Distribution

Coronal Index Time Series Solar Activity Data and Probability Distribution

Authors

  • Muhammad Fahim Akhter Mathematical Sciences Research Centre, Federal Urdu University of Arts, Sciences and Technology, Karachi, Pakistan
  • Shaheen Abbas Mathematical Sciences Research Centre, Federal Urdu University of Arts, Sciences and Technology, Karachi, Pakistan
  • Danish Hassan Mathematical Sciences Research Centre, Federal Urdu University of Arts, Sciences and Technology, Karachi, Pakistan

Keywords:

Solar activity, Coronal index cycle, probability distribution, statistical tests

Abstract

The different cycles of solar activity defines space weather variation and future space variability. Such as Solar Corona produces energy in micro and nano flares into the space climate. In this regards the time series analysis of monthly solar Coronal index data (1944 to 2008) is used, which contains six cycles of different length and peaks. In this study different probability distributions like Johnson SB, Beta, Gen. Pareto, Gen. Gamma, Triangular, Error, Dagum and Fatigue Life are fitted on Coronal cycles. The significance probability distributions are obtained using Kolmogrov- Smirnove, Anderson Darling and Chi square statistical tests. The Johnson SB distribution is found best fitted on all solar activity cycles along with the total time series data by Kolmogrov Smirnove test. The Coronal index monthly data is generated from 2008 to 2016 using a Monte Carlo simulation technique. While two other tests show variation in the fitted probability distributions for all cycles. With the help of significant probability distribution the expected length and peak of next Coronal index cycle data can be obtained.

References

Hassan, D., Abbas, S., Ansari, M. R. K., & Jan, B. Solar flares data analysis on application of probability distributions and fractal dimensions and a comparative analysis of North-south Hemispheric solar dlares data behavior. Proceedings of the Pakistan Academy of Sciences 51 (4): 345-353 (2014).

Babu, Arun. Coronal mass ejections from the sunpropagation and near earth fffects. arXiv preprint arXiv:1407.4258 (2014).

Mariska, J. T. The Solar Transition Region (Vol. 23). Cambridge University Press (1992).

Sharma, M. A., & Singh, J. B. Use of probability distribution in rainfall analysis. New York Science Journal 3 (9): 40-49 (2010).

Walk, C. Handbook on Statistical Distributions for Experimentalists. Internal Report SUF-PFY/96-01., University Stockholm (2007).

Wang, Y. M., Sheeley Jr, N. R., Hawley, S. H., Kraemer, J. R., Brueckner, G. E., Howard, R. A.,... & Schwenn, R. The green line corona and its to the photospheric magnetic z field. The Astrophysical Journal 485 (1): 419 (1997).

Podladchikova, O., Lefebvre, B., Krasnoselskikh, V., & Podladchikov, V. Classification of probability densities on the basis of Pearson’s curves with application to coronal heating simulations. Nonlinear Processes in Geophysics 10 (4/5): 323333 (2003).

Minarovjech, M., Rušin, V., & Saniga, M. The green corona database and the coronal index of solar activity. Contrib. Astron. Obs. Skalnaté Pleso 41: 137-141 (2011).

Schwenn, R., Inhester, B., Plunkett, S. P., Epple, A., Podlipnik, B., Bedford, D. K.,... & Lamy, P. L. First view of the extended green-line emission corona at solar activity minimum using the LASCO-C1 coronagraph on SOHO. In: The First Results from SOHO (p. 667-684). Springer, Netherlands (1997).

Hundhausen, A.J. Sizes and locations of coronal mass ejections: SMM observations from 1980 and 1984‐1989. Journal of Geophysical Research: Space Physics 98. A8: 13177-13200 (1993).

Vujic, J.L. Monte Carlo Sampling Methods. Nuclear Engineering Department, University of California, USA (2008).

Downloads

Published

2021-04-15

How to Cite

Akhter, M. F. ., Abbas, . S. ., & Hassan , . D. . (2021). Study of Coronal Index Time Series Solar Activity Data in the Perspective of Probability Distribution : Coronal Index Time Series Solar Activity Data and Probability Distribution. Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, 55(1), 27–33. Retrieved from http://ppaspk.org/index.php/PPAS-A/article/view/198

Issue

Section

Articles