Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data
Abstract Geometric modeling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modeling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind...
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Wiley
2022-01-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2021SW002841 |
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| author | L. Barnard M. J. Owens C. J. Scott M. Lockwood C. A. deKoning T. Amerstorfer J. Hinterreiter C. Möstl J. A. Davies P. Riley |
| author_facet | L. Barnard M. J. Owens C. J. Scott M. Lockwood C. A. deKoning T. Amerstorfer J. Hinterreiter C. Möstl J. A. Davies P. Riley |
| author_sort | L. Barnard |
| collection | DOAJ |
| description | Abstract Geometric modeling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modeling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modeling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models to estimate the CME kinematics. The errors of geometric modeling depend on the location of the observer, but do not seem to depend on the CME scenario. In general, geometric models are biased towards predicting CME apex distances that are larger than the true value. For these CME scenarios, geometric modeling errors are minimised for an observer in the L5 region. Furthermore, geometric modeling errors increase with the level of solar wind structure in the path of the CME. The ELEvoHI arrival time errors are minimised for an observer in the L5 region, with mean absolute arrival time errors of 8.2 ± 1.2 h, 8.3 ± 1.0 h, and 5.8 ± 0.9 h for the average, fast, and extreme CME scenarios. |
| format | Article |
| id | doaj-art-38d66f9c85ea4b3aaf806deb10ffdc48 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-38d66f9c85ea4b3aaf806deb10ffdc482025-01-14T16:35:20ZengWileySpace Weather1542-73902022-01-01201n/an/a10.1029/2021SW002841Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager DataL. Barnard0M. J. Owens1C. J. Scott2M. Lockwood3C. A. deKoning4T. Amerstorfer5J. Hinterreiter6C. Möstl7J. A. Davies8P. Riley9Department of Meteorology University of Reading Reading UKDepartment of Meteorology University of Reading Reading UKDepartment of Meteorology University of Reading Reading UKDepartment of Meteorology University of Reading Reading UKCooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder Colorado USASpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaRAL Space Rutherford Appleton Laboratory Harwell Campus Didcot UKPredictive Science Inc. San Diego CA USAAbstract Geometric modeling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modeling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modeling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models to estimate the CME kinematics. The errors of geometric modeling depend on the location of the observer, but do not seem to depend on the CME scenario. In general, geometric models are biased towards predicting CME apex distances that are larger than the true value. For these CME scenarios, geometric modeling errors are minimised for an observer in the L5 region. Furthermore, geometric modeling errors increase with the level of solar wind structure in the path of the CME. The ELEvoHI arrival time errors are minimised for an observer in the L5 region, with mean absolute arrival time errors of 8.2 ± 1.2 h, 8.3 ± 1.0 h, and 5.8 ± 0.9 h for the average, fast, and extreme CME scenarios.https://doi.org/10.1029/2021SW002841coronal mass ejectionsgeometric modelingforecastingELEvoHIHUXtuncertainty |
| spellingShingle | L. Barnard M. J. Owens C. J. Scott M. Lockwood C. A. deKoning T. Amerstorfer J. Hinterreiter C. Möstl J. A. Davies P. Riley Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data Space Weather coronal mass ejections geometric modeling forecasting ELEvoHI HUXt uncertainty |
| title | Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data |
| title_full | Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data |
| title_fullStr | Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data |
| title_full_unstemmed | Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data |
| title_short | Quantifying the Uncertainty in CME Kinematics Derived From Geometric Modeling of Heliospheric Imager Data |
| title_sort | quantifying the uncertainty in cme kinematics derived from geometric modeling of heliospheric imager data |
| topic | coronal mass ejections geometric modeling forecasting ELEvoHI HUXt uncertainty |
| url | https://doi.org/10.1029/2021SW002841 |
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