4.7 Article

The Drag-based Ensemble Model (DBEM) for Coronal Mass Ejection Propagation

期刊

ASTROPHYSICAL JOURNAL
卷 854, 期 2, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.3847/1538-4357/aaaa66

关键词

magnetohydrodynamics (MHD); methods: analytical; methods: statistical; solar-terrestrial relations; solar wind; Sun: coronal mass ejections (CMEs)

资金

  1. European Union's Horizon research and innovation programme under the Marie Skodowska-Curie grant [745782]
  2. Croatian Science Foundation [6212]
  3. FFG/ASAP Programme [859729]
  4. Austrian Science Fund (FWF) [P24092-N16, V195-N16]
  5. Scientific & Technological Cooperation between Austria-Croatia [HR 24/2018]
  6. Marie Curie Actions (MSCA) [745782] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

The drag-based model for heliospheric propagation of coronal mass ejections (CMEs) is a widely used analytical model that can predict CME arrival time and speed at a given heliospheric location. It is based on the assumption that the propagation of CMEs in interplanetary space is solely under the influence of magnetohydrodynamical drag, where CME propagation is determined based on CME initial properties as well as the properties of the ambient solar wind. We present an upgraded version, the drag-based ensemble model (DBEM), that covers ensemble modeling to produce a distribution of possible ICME arrival times and speeds. Multiple runs using uncertainty ranges for the input values can be performed in almost real-time, within a few minutes. This allows us to define the most likely ICME arrival times and speeds, quantify prediction uncertainties, and determine forecast confidence. The performance of the DBEM is evaluated and compared to that of ensemble WSA-ENLIL+Cone model (ENLIL) using the same sample of events. It is found that the mean error is ME = -9.7 hr, mean absolute error MAE = 14.3 hr, and root mean square error RMSE = 16.7 hr, which is somewhat higher than, but comparable to ENLIL errors (ME = -6.1 hr, MAE = 12.8 hr and RMSE = 14.4 hr). Overall, DBEM and ENLIL show a similar performance. Furthermore, we find that in both models fast CMEs are predicted to arrive earlier than observed, most likely owing to the physical limitations of models, but possibly also related to an overestimation of the CME initial speed for fast CMEs.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据