Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2021GL096275 |
Reconstructing solar wind profiles associated with extreme magnetic storms: A machine learning approach | |
Ryuho Kataoka; Shin’; ya Nakano | |
2021-11-15 | |
发表期刊 | Geophysical Research Letters
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出版年 | 2021 |
英文摘要 | The lack of data on solar wind have prevented a detailed understanding of extreme magnetic storms. To address this issue, we apply a machine learning technique in the form of an Echo State Network (ESN) to reconstruct solar wind data for several extreme magnetic storms for which little or no solar wind data were previously available. Multiple geomagnetic activity indices are used as the input data for the ESN, which produces a continuous time series of solar wind parameters as output. As a result, the solar wind parameters for the largest storm event in March 1989 are obtained, and the minimum Bz is estimated to be -95 nT±10 nT. Two different types of solar wind profiles are discussed for the extreme magnetic storms−a sheath-driven profile and a magnetic cloud-driven profile. The results reported here will be highly useful as input data for future simulation studies modeling extreme magnetic storms. |
领域 | 气候变化 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/342081 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | Ryuho Kataoka,Shin’,ya Nakano. Reconstructing solar wind profiles associated with extreme magnetic storms: A machine learning approach[J]. Geophysical Research Letters,2021. |
APA | Ryuho Kataoka,Shin’,&ya Nakano.(2021).Reconstructing solar wind profiles associated with extreme magnetic storms: A machine learning approach.Geophysical Research Letters. |
MLA | Ryuho Kataoka,et al."Reconstructing solar wind profiles associated with extreme magnetic storms: A machine learning approach".Geophysical Research Letters (2021). |
条目包含的文件 | 条目无相关文件。 |
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