{"title":"Geomagnetic activity recurrences for predicting the amplitude and shape of solar cycle n. 25","authors":"P. Diego, M. Laurenza","doi":"10.1051/swsc/2021036","DOIUrl":null,"url":null,"abstract":"Predicting solar activity is one of the most challenging topics among the various Space Weather and Space Climate issues. In the last decades, the constant enhancement of Space Climate data improved the comprehension of the related physical phenomena and the statistical bases for prediction algorithms. For this purpose, we used geomagnetic indices to provide a powerful algorithm (see Diego et al. [2010. J Geophys Res 115: A06103]) for the solar activity prediction, based on evaluating the recurrence rate in the geomagnetic activity. This paper aims to present the validation of our algorithm over solar cycle n. 24, for which a successful prediction was made, and upgrade it to forecast the shape and time as well as the amplitude of the upcoming cycle n. 25. Contrary to the consensus, we predict it to be quite high, with a maximum sunspot number of 205 ± 29, which should be reached in the first half of 2023. This prediction is consistent with the scenario in which the long-term Gleissberg cycle has reached its minimum in cycle n. 24, and the rising phase is beginning.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1051/swsc/2021036","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 2
Abstract
Predicting solar activity is one of the most challenging topics among the various Space Weather and Space Climate issues. In the last decades, the constant enhancement of Space Climate data improved the comprehension of the related physical phenomena and the statistical bases for prediction algorithms. For this purpose, we used geomagnetic indices to provide a powerful algorithm (see Diego et al. [2010. J Geophys Res 115: A06103]) for the solar activity prediction, based on evaluating the recurrence rate in the geomagnetic activity. This paper aims to present the validation of our algorithm over solar cycle n. 24, for which a successful prediction was made, and upgrade it to forecast the shape and time as well as the amplitude of the upcoming cycle n. 25. Contrary to the consensus, we predict it to be quite high, with a maximum sunspot number of 205 ± 29, which should be reached in the first half of 2023. This prediction is consistent with the scenario in which the long-term Gleissberg cycle has reached its minimum in cycle n. 24, and the rising phase is beginning.