NDLI: Ensemble Modeling of CMEs Using the WSA

Content Provider	Springer Nature Link
Author	Mays, M. L. Taktakishvili, A. Pulkkinen, A. MacNeice, P. J. Rastätter, L. Odstrcil, D. Jian, L. K. Richardson, I. G. LaSota, J. A. Zheng, Y. Kuznetsova, M. M.
Copyright Year	2015
Abstract	Ensemble modeling of coronal mass ejections (CMEs) provides a probabilistic forecast of CME arrival time that includes an estimation of arrival-time uncertainty from the spread and distribution of predictions and forecast confidence in the likelihood of CME arrival. The real-time ensemble modeling of CME propagation uses the Wang–Sheeley–Arge (WSA)–ENLIL+Cone model installed at the Community Coordinated Modeling Center (CCMC) and executed in real-time at the CCMC/Space Weather Research Center. The current implementation of this ensemble-modeling method evaluates the sensitivity of WSA–ENLIL+Cone model simulations of CME propagation to initial CME parameters. We discuss the results of real-time ensemble simulations for a total of 35 CME events that occurred between January 2013 – July 2014. For the 17 events where the CME was predicted to arrive at Earth, the mean absolute arrival-time prediction error was 12.3 hours, which is comparable to the errors reported in other studies. For predictions of CME arrival at Earth, the correct-rejection rate is 62 %, the false-alarm rate is 38 %, the correct-alarm ratio is 77 %, and the false-alarm ratio is 23 %. The arrival time was within the range of the ensemble arrival predictions for 8 out of 17 events. The Brier Score for CME arrival-predictions is 0.15 (where a score of 0 on a range of 0 to 1 is a perfect forecast), which indicates that on average, the predicted probability, or likelihood, of CME arrival is fairly accurate. The reliability of ensemble CME-arrival predictions is heavily dependent on the initial distribution of CME input parameters (e.g. speed, direction, and width), particularly the median and spread. Preliminary analysis of the probabilistic forecasts suggests undervariability, indicating that these ensembles do not sample a wide-enough spread in CME input parameters. Prediction errors can also arise from ambient-model parameters, the accuracy of the solar-wind background derived from coronal maps, or other model limitations. Finally, predictions of the K $_{P}$ geomagnetic index differ from observed values by less than one for 11 out of 17 of the ensembles and K $_{P}$ prediction errors computed from the mean predicted K $_{P}$ show a mean absolute error of 1.3.
Starting Page	1775
Ending Page	1814
Page Count	40
File Format	PDF
ISSN	00380938
Journal	Solar Physics
Volume Number	290
Issue Number	6
e-ISSN	1573093X
Language	English
Publisher	Springer Netherlands
Publisher Date	2015-05-13
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coronal mass ejections, modeling Coronal mass ejections, interplanetary Coronal mass ejections, forecasting Astrophysics and Astroparticles Atmospheric Sciences Extraterrestrial Physics, Space Sciences
Content Type	Text
Resource Type	Article
Subject	Astronomy and Astrophysics Space and Planetary Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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