研究目的
To predict declining solar activity trends during solar cycles 25 and 26 and indicate the onset of another solar minimum by analyzing historical solar parameter data using statistical methods.
研究成果
The analysis predicts that solar cycles 25 and 26 will have declining activity, with maximum sunspot numbers of 89 ± 9 and 78 ± 7, respectively, indicating an ongoing solar minimum similar to but distinct from the Dalton minima. The methods used show high persistence in solar parameters, allowing for reliable forecasts.
研究不足
The study is based on statistical methods and historical data, which may not account for unforeseen changes in solar behavior. The accuracy of predictions depends on the assumptions of the models used, such as the stationarity of trends and the applicability of the Hurst exponent and simplex projection to solar data.
1:Experimental Design and Method Selection:
The study uses statistical methods including the Hodrick Prescott filter to decompose time series into cyclic and trend components, rescaled range analysis to calculate the Hurst exponent for persistence, and simplex projection analysis for future predictions.
2:Sample Selection and Data Sources:
Monthly data of sunspot numbers, F
3:7 cm index, and Lyman alpha index from 1947 to 2017 were obtained from specific websites (http:
//www.sidc.be/silso/, http://www.wdcb.ru/stp/solar/solar_activity.html, http://lasp.colorado.edu/lisird/data/historical_tsi/).
4:List of Experimental Equipment and Materials:
No specific equipment or materials are mentioned; the study relies on computational methods and publicly available data.
5:Experimental Procedures and Operational Workflow:
Data was processed using the HP filter with a smoothing parameter of 129600 for monthly data to separate cyclic and trend components. The cyclic part was analyzed for persistence using rescaled range analysis, and the trend part was used with simplex projection to forecast future solar cycles.
6:Data Analysis Methods:
Statistical analysis included calculation of Hurst exponent and application of simplex projection for time series forecasting.
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