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Prediction Methods in Solar Sunspots Cycles
An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max)...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751534/ https://www.ncbi.nlm.nih.gov/pubmed/26868269 http://dx.doi.org/10.1038/srep21028 |
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author | Ng, Kim Kwee |
author_facet | Ng, Kim Kwee |
author_sort | Ng, Kim Kwee |
collection | PubMed |
description | An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle. |
format | Online Article Text |
id | pubmed-4751534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47515342016-02-22 Prediction Methods in Solar Sunspots Cycles Ng, Kim Kwee Sci Rep Article An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle. Nature Publishing Group 2016-02-12 /pmc/articles/PMC4751534/ /pubmed/26868269 http://dx.doi.org/10.1038/srep21028 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ng, Kim Kwee Prediction Methods in Solar Sunspots Cycles |
title | Prediction Methods in Solar Sunspots Cycles |
title_full | Prediction Methods in Solar Sunspots Cycles |
title_fullStr | Prediction Methods in Solar Sunspots Cycles |
title_full_unstemmed | Prediction Methods in Solar Sunspots Cycles |
title_short | Prediction Methods in Solar Sunspots Cycles |
title_sort | prediction methods in solar sunspots cycles |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4751534/ https://www.ncbi.nlm.nih.gov/pubmed/26868269 http://dx.doi.org/10.1038/srep21028 |
work_keys_str_mv | AT ngkimkwee predictionmethodsinsolarsunspotscycles |