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Decent Estimate of CME Arrival time from a Data-assimilated Ensemble in the Alfvén Wave Solar atmosphere Model (DECADE-AWSoM)
  • +7
  • Hongfan Chen,
  • Nishtha Sachdeva,
  • Zhenguang Huang,
  • Bartholomeus van der Holst,
  • Ward Beecher Manchester IV,
  • Aniket Jivani,
  • Shasha Zou,
  • Yang Chen,
  • Xun Huan,
  • Gabor Toth
Hongfan Chen
University of Michigan

Corresponding Author:[email protected]

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Nishtha Sachdeva
U. Michigan
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Zhenguang Huang
University of Michigan-Ann Arbor
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Bartholomeus van der Holst
University of Michigan-Ann Arbor
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Ward Beecher Manchester IV
University of Michigan-Ann Arbor
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Aniket Jivani
University of Michigan
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Shasha Zou
University of Michigan
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Yang Chen
University of Michigan
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Xun Huan
University of Michigan
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Gabor Toth
University of Michigan-Ann Arbor
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Abstract

Forecasting the arrival time of Earth-directed coronal mass ejections (CMEs) via physics-based simulations is an essential but challenging task in space weather research due to the complexity of the underlying physics and limited remote and in-situ observations of these events. Data assimilation (DA) techniques can assist in constraining free model parameters and reduce the uncertainty in subsequent model predictions. In this study, we show that CME simulations conducted with the Space Weather Modeling Framework (SWMF) can be assimilated with SOHO LASCO white-light (WL) observations and solar wind observations at L1 prior to the CME eruption to improve the prediction of CME arrival time. The L1 observations are used to constrain the model of the solar wind background into which the CME is launched. Average speed of CME shock front over propagation angles are extracted from both synthetic WL images from the Alfv\’en Wave Solar atmosphere Model (AWSoM) and the WL observations. We observe a strong rank correlation between the average WL speed and CME arrival time, with the Spearman’s rank correlation coefficients larger than 0.90 for three events occurring during different phases of the solar cycle. This enables us to develop a Bayesian framework to filter ensemble simulations using WL observations, which is found to reduce the mean absolute error of CME arrival time prediction from about 13.4$\pm$3.8 hours to 5.1$\pm$3.0 hours. The results show the potential of assimilating readily available L1 and WL observations within hours of the CME eruption to construct optimal ensembles of Sun-to-Earth CME simulations.
26 Sep 2024Submitted to ESS Open Archive
27 Sep 2024Published in ESS Open Archive