A new method for forecasting the solar cycle descent time
| Autor: | Bharati Kakad, Durbha Sai Ramesh, Amar Kakad |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Solar minimum
Atmospheric Science Sunspot Correlation coefficient Shannon entropy Thermodynamics Solar cycle prediction Grand solar minima Dalton Minimum lcsh:QC851-999 Solar cycle Maxima and minima Space and Planetary Science Sunspot numbers Physics::Space Physics Applied mathematics Entropy (information theory) lcsh:Meteorology. Climatology Randomness Mathematics |
| Zdroj: | Journal of Space Weather and Space Climate, Vol 5, p A29 (2015) |
| ISSN: | 2115-7251 |
| Popis: | The prediction of an extended solar minimum is extremely important because of the severity of its impact on the near-earth space. Here, we present a new method for predicting the descent time of the forthcoming solar cycle (SC); the method is based on the estimation of the Shannon entropy. We use the daily and monthly smoothed international sunspot number. For each n th SC, we compute the parameter [T pre ]n by using information on the descent and ascent times of the n − 3th and n th SCs, respectively. We find that [T pre ] of n th SC and entropy can be effectively used to predict the descent time of the n + 2th SC. The correlation coefficient between [T d ]n +2 − [T pre ]n and [E ]n is found to be 0.95. Using these parameters the prediction model is developed. Solar magnetic field and F10.7 flux data are available for SCs 21–22 and 19–23, respectively, and they are also utilized to get estimates of the Shannon entropy. It is found that the Shannon entropy, a measure of randomness inherent in the SC, is reflected well in the various proxies of the solar activity (viz sunspot, magnetic field, F10.7 flux). The applicability and accuracy of the prediction model equation is verified by way of association of least entropy values with the Dalton minimum. The prediction model equation also provides possible criteria for the occurrence of unusually longer solar minima. |
| Databáze: | OpenAIRE |
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