Ensemble CME Modeling Constrained by Heliospheric Imager Observations. Issue 3 (18th September 2020)
- Record Type:
- Journal Article
- Title:
- Ensemble CME Modeling Constrained by Heliospheric Imager Observations. Issue 3 (18th September 2020)
- Main Title:
- Ensemble CME Modeling Constrained by Heliospheric Imager Observations
- Authors:
- Barnard, L.
Owens, M. J.
Scott, C. J.
de Koning, C. A. - Abstract:
- Abstract : Predicting the arrival of coronal mass ejections (CMEs) is one key objective of space weather forecasting. In operational space weather forecasting, solar wind numerical models are used for this task and ensemble techniques are being increasingly explored as a means to improve these forecasts. Currently, these forecasts are not constrained by the available in situ and remote sensing observations, such as those from the heliospheric imagers (HIs) on the National Aeronautics and Space Administration's (NASA's) STEREO spacecraft, which record white‐light images of solar wind and CMEs. We report case studies of four CMEs and show how HI observations can be used to improve the skill and reduce the uncertainty of ensemble hindcasts of these events. Using a computationally efficient solar wind model, we produce 200‐member ensemble hindcasts, perturbing the modeled CME parameters within uniform distributions about the best estimates. By comparing the trajectory of the modeled CME flanks with HI observations, we compute a weight for each ensemble member. Weighting the ensemble distribution of CME arrival times improves the skill and reduces the hindcast uncertainty of each event. For these four events, the weighted ensembles show a mean reduction in arrival time error of 20.1 ± 4.1%, and a mean reduction in arrival time uncertainty of 15.0 ± 7.2%, relative to the unweighted ensembles. This technique could be applied in operational space weather forecasting, if real‐time HIAbstract : Predicting the arrival of coronal mass ejections (CMEs) is one key objective of space weather forecasting. In operational space weather forecasting, solar wind numerical models are used for this task and ensemble techniques are being increasingly explored as a means to improve these forecasts. Currently, these forecasts are not constrained by the available in situ and remote sensing observations, such as those from the heliospheric imagers (HIs) on the National Aeronautics and Space Administration's (NASA's) STEREO spacecraft, which record white‐light images of solar wind and CMEs. We report case studies of four CMEs and show how HI observations can be used to improve the skill and reduce the uncertainty of ensemble hindcasts of these events. Using a computationally efficient solar wind model, we produce 200‐member ensemble hindcasts, perturbing the modeled CME parameters within uniform distributions about the best estimates. By comparing the trajectory of the modeled CME flanks with HI observations, we compute a weight for each ensemble member. Weighting the ensemble distribution of CME arrival times improves the skill and reduces the hindcast uncertainty of each event. For these four events, the weighted ensembles show a mean reduction in arrival time error of 20.1 ± 4.1%, and a mean reduction in arrival time uncertainty of 15.0 ± 7.2%, relative to the unweighted ensembles. This technique could be applied in operational space weather forecasting, if real‐time HI observations were available. Therefore, as NASA and the European Space Agency are currently planning the next space weather monitoring missions, our proof‐of‐concept study provides some evidence of the potential value of including HIs on these missions. Plain Language Summary: Coronal mass ejections (CMEs) are large eruptions of magnetized plasma from the Sun's atmosphere that flow out through space. CMEs that reach Earth are the main cause of severe space weather and can disrupt technology we rely on, such as satellites, communications networks, and power grids. Consequently, forecasting the arrival of CMEs at Earth is an important service performed by various national weather agencies. Improving these forecasts is an important area of space weather research, particularly measuring and improving the uncertainty of the CME arrival time predictions. We show how pictures of CMEs taken by the heliospheric imagers on NASA's STEREO spacecraft can be used to reduce the uncertainty and improve the accuracy of CME arrival time predictions. NASA and ESA are currently planning the next spacecraft missions that will observe the Sun and space for space weather forecasting. Our proof‐of‐concept study provides some evidence that it would be useful to include a heliospheric imager on these future missions. Key Points: Ensemble modelling of CME arrival time is a useful space weather forecasting technique Heliospheric imager data can improve the skill and reduce the uncertainty of ensemble hindcasts This supports the idea of including a heliospheric imager on the next space weather monitor … (more)
- Is Part Of:
- AGU advances. Volume 1:Issue 3(2020)
- Journal:
- AGU advances
- Issue:
- Volume 1:Issue 3(2020)
- Issue Display:
- Volume 1, Issue 3 (2020)
- Year:
- 2020
- Volume:
- 1
- Issue:
- 3
- Issue Sort Value:
- 2020-0001-0003-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-09-18
- Subjects:
- space weather -- coronal mass ejections -- forecasting -- heliophysics
Earth sciences -- Periodicals
Space sciences -- Periodicals
550 - Journal URLs:
- https://agupubs.onlinelibrary.wiley.com/journal/2576604x ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2020AV000214 ↗
- Languages:
- English
- ISSNs:
- 2576-604X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17238.xml