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Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind using the Alfvén Wave Solar Atmosphere Model
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  • Aniket Jivani,
  • Nishtha Sachdeva,
  • Zhenguang Huang,
  • Yang Chen,
  • Bart van der Holst,
  • Ward Manchester,
  • Daniel Iong,
  • Hongfan Chen,
  • Shasha Zou,
  • Xun Huan,
  • Gabor Toth
Aniket Jivani
University of Michigan, University of Michigan

Corresponding Author:[email protected]

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Nishtha Sachdeva
University of Michigan, University of Michigan
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Zhenguang Huang
University of Michigan, University of Michigan
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Yang Chen
University of Michigan, University of Michigan
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Bart van der Holst
University of Michigan, University of Michigan
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Ward Manchester
University of Michigan, University of Michigan
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Daniel Iong
University of Michigan, University of Michigan
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Hongfan Chen
University of Michigan, University of Michigan
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Shasha Zou
University of Michigan, University of Michigan
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Xun Huan
University of Michigan, University of Michigan
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Gabor Toth
University of Michigan, University of Michigan
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Abstract

Modeling the impact of space weather events such as coronal mass ejections (CMEs) is crucial to protecting critical infrastructure. The Space Weather Modeling Framework (SWMF) is a state-of-the-art framework that offers full Sun-to-Earth simulations by computing the background solar wind, CME propagation and magnetospheric impact. However, reliable long-term predictions of CME events require uncertainty quantification (UQ) and data assimilation (DA). We take the first steps by performing global sensitivity analysis (GSA) and UQ for background solar wind simulations produced by the Alfvén Wave Solar atmosphere Model (AWSoM) for two Carrington rotations: CR2152 (solar maximum) and CR2208 (solar minimum). We conduct GSA by computing Sobol indices that quantify contributions from model parameter uncertainty to the variance of solar wind speed and density at 1 au, both crucial quantities for CME propagation and strength. Sobol indices also allow us to rank and retain only the most important parameters, which aids in the construction of smaller ensembles for the reduced-dimension parameter space. We present an efficient procedure for computing the Sobol indices using polynomial chaos expansion (PCE) surrogates and space-filling designs. The PCEs further enable inexpensive forward UQ. Overall, we identify three important model parameters: the multiplicative factor applied to the magnetogram, Poynting flux per magnetic field strength constant used at the inner boundary, and the coefficient of the perpendicular correlation length in the turbulent cascade model in AWSoM.
Jan 2023Published in Space Weather volume 21 issue 1. 10.1029/2022SW003262