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Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations

In this study, we evaluate a coronal mass ejection (CME) arrival prediction tool that utilizes the wide‐angle observations made by STEREO's heliospheric imagers (HI). The unsurpassable advantage of these imagers is the possibility to observe the evolution and propagation of a CME from close to...

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Autores principales: Amerstorfer, Tanja, Hinterreiter, Jürgen, Reiss, Martin A., Möstl, Christian, Davies, Jackie A., Bailey, Rachel L., Weiss, Andreas J., Dumbović, Mateja, Bauer, Maike, Amerstorfer, Ute V., Harrison, Richard A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8607470/
https://www.ncbi.nlm.nih.gov/pubmed/34853569
http://dx.doi.org/10.1029/2020SW002553
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author Amerstorfer, Tanja
Hinterreiter, Jürgen
Reiss, Martin A.
Möstl, Christian
Davies, Jackie A.
Bailey, Rachel L.
Weiss, Andreas J.
Dumbović, Mateja
Bauer, Maike
Amerstorfer, Ute V.
Harrison, Richard A.
author_facet Amerstorfer, Tanja
Hinterreiter, Jürgen
Reiss, Martin A.
Möstl, Christian
Davies, Jackie A.
Bailey, Rachel L.
Weiss, Andreas J.
Dumbović, Mateja
Bauer, Maike
Amerstorfer, Ute V.
Harrison, Richard A.
author_sort Amerstorfer, Tanja
collection PubMed
description In this study, we evaluate a coronal mass ejection (CME) arrival prediction tool that utilizes the wide‐angle observations made by STEREO's heliospheric imagers (HI). The unsurpassable advantage of these imagers is the possibility to observe the evolution and propagation of a CME from close to the Sun out to 1 AU and beyond. We believe that by exploiting this capability, instead of relying on coronagraph observations only, it is possible to improve today's CME arrival time predictions. The ELlipse Evolution model based on HI observations (ELEvoHI) assumes that the CME frontal shape within the ecliptic plane is an ellipse and allows the CME to adjust to the ambient solar wind speed; that is, it is drag based. ELEvoHI is used to perform ensemble simulations by varying the CME frontal shape within given boundary conditions that are consistent with the observations made by HI. In this work, we evaluate different setups of the model by performing hindcasts for 15 well‐defined isolated CMEs that occurred when STEREO was near L4/5, between the end of 2008 and the beginning of 2011. In this way, we find a mean absolute error of between 6.2 ± 7.9 and 9.9 ± 13 hr depending on the model setup used. ELEvoHI is specified for using data from future space weather missions carrying HIs located at L5 or L1. It can also be used with near‐real‐time STEREO‐A HI beacon data to provide CME arrival predictions during the next ∼7 years when STEREO‐A is observing the Sun‐Earth space.
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spelling pubmed-86074702021-11-29 Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations Amerstorfer, Tanja Hinterreiter, Jürgen Reiss, Martin A. Möstl, Christian Davies, Jackie A. Bailey, Rachel L. Weiss, Andreas J. Dumbović, Mateja Bauer, Maike Amerstorfer, Ute V. Harrison, Richard A. Space Weather Research Articles In this study, we evaluate a coronal mass ejection (CME) arrival prediction tool that utilizes the wide‐angle observations made by STEREO's heliospheric imagers (HI). The unsurpassable advantage of these imagers is the possibility to observe the evolution and propagation of a CME from close to the Sun out to 1 AU and beyond. We believe that by exploiting this capability, instead of relying on coronagraph observations only, it is possible to improve today's CME arrival time predictions. The ELlipse Evolution model based on HI observations (ELEvoHI) assumes that the CME frontal shape within the ecliptic plane is an ellipse and allows the CME to adjust to the ambient solar wind speed; that is, it is drag based. ELEvoHI is used to perform ensemble simulations by varying the CME frontal shape within given boundary conditions that are consistent with the observations made by HI. In this work, we evaluate different setups of the model by performing hindcasts for 15 well‐defined isolated CMEs that occurred when STEREO was near L4/5, between the end of 2008 and the beginning of 2011. In this way, we find a mean absolute error of between 6.2 ± 7.9 and 9.9 ± 13 hr depending on the model setup used. ELEvoHI is specified for using data from future space weather missions carrying HIs located at L5 or L1. It can also be used with near‐real‐time STEREO‐A HI beacon data to provide CME arrival predictions during the next ∼7 years when STEREO‐A is observing the Sun‐Earth space. John Wiley and Sons Inc. 2021-01-05 2021-01 /pmc/articles/PMC8607470/ /pubmed/34853569 http://dx.doi.org/10.1029/2020SW002553 Text en ©2020. The Authors. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Amerstorfer, Tanja
Hinterreiter, Jürgen
Reiss, Martin A.
Möstl, Christian
Davies, Jackie A.
Bailey, Rachel L.
Weiss, Andreas J.
Dumbović, Mateja
Bauer, Maike
Amerstorfer, Ute V.
Harrison, Richard A.
Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
title Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
title_full Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
title_fullStr Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
title_full_unstemmed Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
title_short Evaluation of CME Arrival Prediction Using Ensemble Modeling Based on Heliospheric Imaging Observations
title_sort evaluation of cme arrival prediction using ensemble modeling based on heliospheric imaging observations
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8607470/
https://www.ncbi.nlm.nih.gov/pubmed/34853569
http://dx.doi.org/10.1029/2020SW002553
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