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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Main Author: Pesnell W. Dean
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:Journal of Space Weather and Space Climate
Subjects:
Online Access:https://www.swsc-journal.org/articles/swsc/full_html/2020/01/swsc200057/swsc200057.html
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spelling 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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