Statistical method to predict the sunspots number
| Autor: | B.A. Marzouk, H. I. Abdel-Rahman |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Photosphere
Sunspot 010504 meteorology & atmospheric sciences Sunspot number lcsh:Astronomy lcsh:QC801-809 Astronomy and Astrophysics Solar cycle 24 01 natural sciences Solar cycle lcsh:QB1-991 lcsh:Geophysics. Cosmic physics Geophysics Solar cycle 1 Climatology 0103 physical sciences Environmental science Autoregressive integrated moving average Time series 010303 astronomy & astrophysics 0105 earth and related environmental sciences |
| Zdroj: | NRIAG Journal of Astronomy and Geophysics, Vol 7, Iss 2, Pp 175-179 (2018) |
| ISSN: | 2090-9977 |
| Popis: | Sunspots are dark regions, it is appearing in the deepest layer of solar atmosphere “photosphere”, and the average number of sunspots has cycle every 11 year approximately. Sunspots cycles were numbered with solar cycle 1 beginning in 1755 and the most recent solar cycle, is cycle 24, began in December, 2008. Many authors used different techniques and precursor methods to forecast solar sunspots cycles. In this work we applied a new statistical method “autoregressive integrated moving average Models (ARIMA)” on sunspots number data observed by National Oceanic and Atmospheric Administration (NOAA) during the period 1991 – 2017 (27 years), we predict the sunspot number for the ending of second brunch of current solar sunspots cycle 24. Our prediction of sunspot numbers was compared with the international sunspot number predicted by National Oceanic and Atmospheric Administration (NOAA). Our predictions of monthly mean sunspot numbers along ending years of present solar cycle 24 are in a good agreement with international sunspots number predictions published by NOAA. Keywords: Statistics, Time series analysis, Sun: sunspots number forecasting |
| Databáze: | OpenAIRE |
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