FORECASTING SUNSPOT NUMBERS FOR SOLAR CYCLE 25 USING AUTOREGRESSIVE MODELS FOR BOTH HEMISPHERES OF THE SUN

被引:6
作者
Werner, Rolf [1 ]
Guineva, Veneta [1 ]
机构
[1] Bulgarian Acad Sci, Inst Space Res & Technol, Stara Zagora Dept, POB 7, Stara Zagora 6000, Bulgaria
来源
COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES | 2020年 / 73卷 / 01期
关键词
solar cycle 25; SunSpot Numbers (SSNs); forecast; auto-regression (AR) models; PREDICTION;
D O I
10.7546/CRABS.2020.01.10
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The SunSpot Numbers (SSNs), a proxy of the solar activity, were considered as a time series and their statistical characteristics were studied. The dynamic processes in both solar hemispheres are not strong coupled. Hence, the progress of the solar cycles was described by auto-regression (AR) models worked out for the first time separately for the Northern and the Southern hemispheres and by summation, the total SSNs were calculated. Semi-annual data were used. The model orders were determined by best approximation exante prognosis using AR models of different order to the observed solar cycle 24. A similar procedure was applied to the new solar cycle 25. The SSN maximum in the Northern hemisphere should be achieved before the maximum in the Southern hemisphere. The solar activity in the southern hemisphere would be dominant. The maximum of the total SSNs of about 117 (with a confidence interval from 77 to 165) is predicted for 2023.
引用
收藏
页码:82 / 89
页数:10
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