中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
predictionofthesmoothedmonthlymeansunspotnumbersforsolarcycle24

文献类型:期刊论文

作者JiaLong Wang1; Juan Miao2; SiQing Liu2; JianCun Gong2; CuiLian Zhu1
刊名scienceinchinaseriesgphysicsmechanicsastronomy
出版日期2008
卷号51期号:12页码:1938
ISSN号1672-1799
英文摘要The prediction for the smoothed monthly mean sunspot numbers (hereafter SMSNs) of solar cycle 23, which was given with a similar cycle method proposed by us at the beginning time of cycle 23, is analyzed and verified in this paper. Using our predicted maximum SMSN and the ascending length for solar cycle 24, and assuming their relative errors to be respectively 20% and +/- 7 months, solar cycles 2, 4, 8, 11, 17, 20 and 23 are selected to be the similar cycles to cycle 24. The selected solar cycles are divided into two groups. The first group consists of all the selected cycles; while the second group consists of only cycles 11, 17, 20 and 23. Two SMSN time profiles then may be obtained, respectively, for the two similar cycle groups. No significant difference is found between the two predicted time profiles. Considering the latest observed sunspot number so far available for cycle 23 and the predictions for the minimum SMSN of cycle 24, a date calibration is done for the obtained time profiles, and thus, SMSNs for 127 months of cycle 24, from October 2007 to April 2018, are predicted.
语种英语
源URL[http://ir.bao.ac.cn/handle/114a11/53195]  
专题中国科学院国家天文台
作者单位1.中国科学院国家天文台
2.中国科学院
推荐引用方式
GB/T 7714
JiaLong Wang,Juan Miao,SiQing Liu,et al. predictionofthesmoothedmonthlymeansunspotnumbersforsolarcycle24[J]. scienceinchinaseriesgphysicsmechanicsastronomy,2008,51(12):1938.
APA JiaLong Wang,Juan Miao,SiQing Liu,JianCun Gong,&CuiLian Zhu.(2008).predictionofthesmoothedmonthlymeansunspotnumbersforsolarcycle24.scienceinchinaseriesgphysicsmechanicsastronomy,51(12),1938.
MLA JiaLong Wang,et al."predictionofthesmoothedmonthlymeansunspotnumbersforsolarcycle24".scienceinchinaseriesgphysicsmechanicsastronomy 51.12(2008):1938.

入库方式: OAI收割

来源:国家天文台

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