Please use this identifier to cite or link to this item: http://library.iigm.res.in:8080/xmlui/handle/123456798/137
Title: Randomness in sunspot number: a clue to predict solar cycle 25
Authors: Kakad, Bharati
Kumar, Raj
Kakad, Amar
Keywords: Solar Cycle
Models
Sunspots
Issue Date: 2020
Citation: Solar Physics, v. 295, https://doi.org/10.1007/s11207-020-01655-7
Abstract: Forecasting of solar activity is extremely important, due to its impact on our space-based technology. In recent years, we have observed a continuous decline in the peak sunspot number for Solar Cycles (SCs) 21 to 24. We are more curious about peak activity of SC 25 because if the solar activity weakens further, then it may be an indication of new extended minima. So far, the daily sunspot-number data make up the longest observational series of the solar activity available, and recently this has been replaced with the corrected new Version 2.0 sunspot-number series. In general, different prediction models are available to forecast the peak smoothed sunspot number (SSN) of the upcoming SC but they are based on the older Version 1.0 sunspot data. Therefore, it is necessary to check the applicability of earlier proposed models to predict the peak SSN using the Version 2.0 sunspot-number series. Here, we re-evaluate one such earlier proposed prediction model, which is based on the estimates of the Shannon entropy, a measure of randomness, for Version 2.0 sunspot data. We find that this prediction model is applicable to the Version 2.0 sunspot-number series. To verify the robustness of the prediction model, we used the histogram and additionally the kernel density estimator (KDE) method to calculate the probability distribution function (PDF). The estimate of the PDF is a prerequisite to compute the Shannon entropy. We found that the prediction model is robust and the correlation coefficients between model parameters are 0.93 and 0.92, respectively, for these two approaches. This exercise provides a new prediction model for the peak SSN based on the Version 2.0 sunspot-number series. The model forecasts the peak smoothed sunspot number of 136.9 ± 24 using a histogram derived PDF and 150.7 ± 25 using a KDE-derived PDF for the upcoming SC 25. These predictions for SC 25 are more reliable as up to date (December 2020) sunspot-number data have been utilized to get the entropy in the end phase of SC 24. It suggests that SC 25 would be similar or slightly stronger than SC 24.
URI: http://library.iigm.res.in:8080/xmlui/handle/123456798/137
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