EGU23-8641
https://doi.org/10.5194/egusphere-egu23-8641
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Ensemble modeling of CMEs to reconstruct remote and in-situ observations

Nishtha Sachdeva, Gabor Toth, Ward Manchester, Bart van der Holst, Aniket Jivani, and Hongfan Chen
Nishtha Sachdeva et al.
  • University of Michigan, Ann Arbor, USA

Successful modeling of Coronal Mass Ejections (CMEs) is an important step towards accurately forecasting their space weather impact. Therefore, it is crucial to improve the various models, techniques and tools to reconstruct CMEs while validating simulations with observations of the solar corona and the inner heliosphere at various heliospheric distances with multi-viewpoint observations.

The Space Weather Modeling Framework (SWMF) includes MHD modeling of the solar wind and CMEs from the Sun to the Earth and beyond. The Alfven Wave Solar atmosphere Model (AWSoM) is a 3D extended-MHD solar corona model within SWMF that reproduces the solar wind background into which CMEs can propagate. The Eruptive Event Generator (EEG) module within SWMF is used to obtain flux-rope parameters to model realistic CMEs within AWSoM using different flux-rope configurations.

In this work supported by the NSF SWQU and LRAC programs, we use an ensemble of solar wind backgrounds to obtain the best solar wind plasma environments into which CMEs can be launched. We vary the flux-rope parameters within a fixed range and obtain an ensemble of CME simulations to match the model reconstructed results with remote coronagraph observations near the Sun (LASCO C2/C3 and STEREO COR1/COR2) as well as with in-situ observations of solar wind plasma at 1 au. The ensemble modeling is a step forward towards improving the accuracy of the tools that provide flux-rope parameter estimates as well as the uncertainty quantification of CME modeling.

How to cite: Sachdeva, N., Toth, G., Manchester, W., van der Holst, B., Jivani, A., and Chen, H.: Ensemble modeling of CMEs to reconstruct remote and in-situ observations, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8641, https://doi.org/10.5194/egusphere-egu23-8641, 2023.