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Can One Predict Coronal Mass Ejection Arrival Times With Thirty-Minute Accuracy?

dc.contributor.authorTóth, Gábor
dc.contributor.authorHolst, Bart
dc.contributor.authorManchester, Ward
dc.date.accessioned2023-06-01T20:50:01Z
dc.date.available2024-06-01 16:50:00en
dc.date.available2023-06-01T20:50:01Z
dc.date.issued2023-05
dc.identifier.citationTóth, Gábor ; Holst, Bart; Manchester, Ward (2023). "Can One Predict Coronal Mass Ejection Arrival Times With Thirty- Minute Accuracy?." Space Weather 21(5): n/a-n/a.
dc.identifier.issn1542-7390
dc.identifier.issn1542-7390
dc.identifier.urihttps://hdl.handle.net/2027.42/176855
dc.description.abstractJ. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961) have recently claimed that they can predict Coronal Mass Ejection (CME) arrival times with an accuracy of 0.9 ± 1.9 hr for four separate events. They also stated that the accuracy gets better with increased grid resolution. Here, we show that combining their results with the Richardson extrapolation (Richardson & Gaunt, 1927, https://doi.org/10.1098/rsta.1927.0008), which is a standard technique in computational fluid dynamics, could predict the CME arrival time with 0.2 ± 0.26 hr accuracy. The CME arrival time errors of this model would lie in a 95% confidence interval [−0.21, 0.61] hr. We also show that the probability of getting these accurate arrival time predictions with a model with a standard deviation exceeding 2 hr is less than 0.1%, indicating that these results cannot be due to random chance. This unprecedented accuracy is about 20 times better than the current state-of-the-art prediction of CME arrival times with an average error of about ±10 hr. Based on our analysis there are only two possibilities: the results shown by J. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961) were not obtained from reproducible numerical simulations, or their method combined by the Richardson extrapolation is in fact providing CME arrival times with half an hour accuracy. We believe that this latter interpretation is very unlikely to hold true. We also discuss how the peer-review process apparently failed to even question the validity of the results presented by J. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961).Plain Language SummaryJ. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961) have recently proposed a model that claims to predict the arrival time of Coronal Mass Ejections at Earth with about 2 hr accuracy. This paper shows that the method could be improved and reduce the error to less than 30 min, however this is extremely unlikely to be true. The only possible explanation is that the results presented by J. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961) are not based on actual numerical simulations. The review process has failed to identify these issues. We provide some recommendations how the review process can be improved.Key PointsIf J. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961) work was reproducible then Coronal Mass Ejection arrival times could be predicted with about 30 min accuracyThe results shown by J. Schmidt and Cairns (2019, https://doi.org/10.48550/arXiv.1905.08961) are not based on reproducible numerical simulationsThe review process has potentially allowed prior work of similarly doubtful validity to get published in leading journals
dc.publisherRetraction Watch
dc.publisherWiley Periodicals, Inc.
dc.subject.otherfirst-principles models
dc.subject.otherCME arrival time
dc.subject.otherpeer-review process
dc.subject.otherCME
dc.subject.otherspace weather
dc.titleCan One Predict Coronal Mass Ejection Arrival Times With Thirty-Minute Accuracy?
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelElectrical Engineering
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/176855/1/swe21508_am.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/176855/2/swe21508.pdf
dc.identifier.doi10.1029/2023SW003463
dc.identifier.sourceSpace Weather
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dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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