Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model
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 is a state‐of‐the‐art framework that offers full Sun‐to‐Earth simulations by computing the background solar wind, CME prop...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2022SW003262 |
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| author | Aniket Jivani Nishtha Sachdeva Zhenguang Huang Yang Chen Bart van derHolst Ward Manchester Daniel Iong Hongfan Chen Shasha Zou Xun Huan Gabor Toth |
| author_facet | Aniket Jivani Nishtha Sachdeva Zhenguang Huang Yang Chen Bart van derHolst Ward Manchester Daniel Iong Hongfan Chen Shasha Zou Xun Huan Gabor Toth |
| author_sort | Aniket Jivani |
| collection | DOAJ |
| description | 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 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. 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 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. |
| format | Article |
| id | doaj-art-cd4989552cba4c85b6a97715b4a8b227 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-cd4989552cba4c85b6a97715b4a8b2272025-01-14T16:35:23ZengWileySpace Weather1542-73902023-01-01211n/an/a10.1029/2022SW003262Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere ModelAniket Jivani0Nishtha Sachdeva1Zhenguang Huang2Yang Chen3Bart van derHolst4Ward Manchester5Daniel Iong6Hongfan Chen7Shasha Zou8Xun Huan9Gabor Toth10Department of Mechanical Engineering University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Statistics University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Statistics University of Michigan Ann Arbor MI USADepartment of Mechanical Engineering University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USADepartment of Mechanical Engineering University of Michigan Ann Arbor MI USADepartment of Climate and Space Sciences and Engineering University of Michigan Ann Arbor MI USAAbstract Modeling the impact of space weather events such as coronal mass ejections (CMEs) is crucial to protecting critical infrastructure. The Space Weather Modeling Framework 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. 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 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.https://doi.org/10.1029/2022SW003262uncertainty quantificationglobal sensitivity analysisspace weathersolar wind |
| spellingShingle | Aniket Jivani Nishtha Sachdeva Zhenguang Huang Yang Chen Bart van derHolst Ward Manchester Daniel Iong Hongfan Chen Shasha Zou Xun Huan Gabor Toth Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model Space Weather uncertainty quantification global sensitivity analysis space weather solar wind |
| title | Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model |
| title_full | Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model |
| title_fullStr | Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model |
| title_full_unstemmed | Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model |
| title_short | Global Sensitivity Analysis and Uncertainty Quantification for Background Solar Wind Using the Alfvén Wave Solar Atmosphere Model |
| title_sort | global sensitivity analysis and uncertainty quantification for background solar wind using the alfven wave solar atmosphere model |
| topic | uncertainty quantification global sensitivity analysis space weather solar wind |
| url | https://doi.org/10.1029/2022SW003262 |
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