Lessons learned from predictions of Solar Cycle 24
Solar Cycle 24 has almost faded and the activity of Solar Cycle 25 is appearing. We have learned much about predicting solar activity in Solar Cycle 24, especially with the data provided by SDO and STEREO. Many advances have come in the short-term predictions of solar flares and coronal mass ejectio...
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doaj-31cb29b0c7504be28bc9124ac7b6d6482021-04-02T16:29:05ZengEDP SciencesJournal of Space Weather and Space Climate2115-72512020-01-01106010.1051/swsc/2020060swsc200057Lessons learned from predictions of Solar Cycle 24Pesnell W. Dean0https://orcid.org/0000-0002-8306-2500NASA Goddard Space Flight CenterSolar Cycle 24 has almost faded and the activity of Solar Cycle 25 is appearing. We have learned much about predicting solar activity in Solar Cycle 24, especially with the data provided by SDO and STEREO. Many advances have come in the short-term predictions of solar flares and coronal mass ejections, which have benefited from applying machine learning techniques to the new data. The arrival times of coronal mass ejections is a mid-range prediction whose accuracy has been improving, mostly due to a steady flow of data from SoHO, STEREO, and SDO. Longer term (greater than a year) predictions of solar activity have benefited from helioseismic studies of the plasma flows in the Sun. While these studies have complicated the dynamo models by introducing more complex internal flow patterns, the models should become more robust with the added information. But predictions made long before a sunspot cycle begins still rely on precursors. The success of some categories of the predictions of Solar Cycle 24 will be examined. The predictions in successful categories should be emphasized in future work. The SODA polar field precursor method, which has accurately predicted the last three cycles, is shown for Solar Cycle 25. Shape functions for the sunspot number and F10.7 are presented. What type of data is needed to better understand the polar regions of the Sun, the source of the most accurate precursor of long-term solar activity, will be discussed.https://www.swsc-journal.org/articles/swsc/full_html/2020/01/swsc200057/swsc200057.htmlsolar activityforecasting methods |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pesnell W. Dean |
spellingShingle |
Pesnell W. Dean Lessons learned from predictions of Solar Cycle 24 Journal of Space Weather and Space Climate solar activity forecasting methods |
author_facet |
Pesnell W. Dean |
author_sort |
Pesnell W. Dean |
title |
Lessons learned from predictions of Solar Cycle 24 |
title_short |
Lessons learned from predictions of Solar Cycle 24 |
title_full |
Lessons learned from predictions of Solar Cycle 24 |
title_fullStr |
Lessons learned from predictions of Solar Cycle 24 |
title_full_unstemmed |
Lessons learned from predictions of Solar Cycle 24 |
title_sort |
lessons learned from predictions of solar cycle 24 |
publisher |
EDP Sciences |
series |
Journal of Space Weather and Space Climate |
issn |
2115-7251 |
publishDate |
2020-01-01 |
description |
Solar Cycle 24 has almost faded and the activity of Solar Cycle 25 is appearing. We have learned much about predicting solar activity in Solar Cycle 24, especially with the data provided by SDO and STEREO. Many advances have come in the short-term predictions of solar flares and coronal mass ejections, which have benefited from applying machine learning techniques to the new data. The arrival times of coronal mass ejections is a mid-range prediction whose accuracy has been improving, mostly due to a steady flow of data from SoHO, STEREO, and SDO. Longer term (greater than a year) predictions of solar activity have benefited from helioseismic studies of the plasma flows in the Sun. While these studies have complicated the dynamo models by introducing more complex internal flow patterns, the models should become more robust with the added information. But predictions made long before a sunspot cycle begins still rely on precursors. The success of some categories of the predictions of Solar Cycle 24 will be examined. The predictions in successful categories should be emphasized in future work. The SODA polar field precursor method, which has accurately predicted the last three cycles, is shown for Solar Cycle 25. Shape functions for the sunspot number and F10.7 are presented. What type of data is needed to better understand the polar regions of the Sun, the source of the most accurate precursor of long-term solar activity, will be discussed. |
topic |
solar activity forecasting methods |
url |
https://www.swsc-journal.org/articles/swsc/full_html/2020/01/swsc200057/swsc200057.html |
work_keys_str_mv |
AT pesnellwdean lessonslearnedfrompredictionsofsolarcycle24 |
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