PMO OpenIR
Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting
Lu, J. Y.1; Jin, C. Q.1; Wang, M.1; Ji, H. S.2; Iluore, K.1; Guan, H. Y.3; Li, J. F.4; Li, J. Y.1
2019-04-01
Source PublicationSPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
ISSN1542-7390
Volume17Issue:4Pages:567-585
Corresponding AuthorLu, J. Y.(jylu@nuist.edu.cn)
AbstractOne of the main issues of space weather is the timely prediction of disturbed solar wind parameters at L1, especially caused by Coronal Mass Ejection (CME). Using the data from 170 front halo, flare-associated CMEs, and in-site solar wind data, an analysis of the Interplanetary Coronal Mass Ejection (ICME) peak velocity at L1 related to associated coronal parameters is performed. The statistical methods including the Generalized Additive Modeling (GAM) and Multiple Collinear (MC) have been applied to explain the underlying physical reasons and set up a new prediction model. Our results indicate that (1) X-flare integral flux, CME linear velocity, and Acceleration observed on corona play key roles in ICME velocity, while other coronal parameters only present a weak correlation, such as the CME Mass and Angular Width, (2) the relationship between ICME velocity and CME Acceleration, as well as CME linear velocity, is nonstationary, and the ICME velocity will increase with the increasing CME Acceleration or linear velocity until saturation, and (3) MC is an effective method to improve the forecast model performance. Compared with 0.52 for only GAM, the correlation coefficient using GAM + MC reaches to 0.71. To further testify the prediction ability, the GAM + MC model results are compared with the Back-Propagation network model and a typically empirical statistic relation proposed by Manoharan (2006, https://doi.org/10.1007/s11207-006-0100-y; their correlation coefficients and root mean squared errors are both roughly 0.6 and 100 km/s, respectively). It is found that the MC + GAM can upgrade the forecast at least over 10%.
DOI10.1029/2018SW002135
WOS KeywordCORONAL MASS EJECTIONS ; SOLAR-WIND SPEED ; FLUX
Indexed BySCI
Language英语
WOS Research AreaAstronomy & Astrophysics ; Geochemistry & Geophysics ; Meteorology & Atmospheric Sciences
WOS SubjectAstronomy & Astrophysics ; Geochemistry & Geophysics ; Meteorology & Atmospheric Sciences
WOS IDWOS:000468190700005
PublisherAMER GEOPHYSICAL UNION
Citation statistics
Document Type期刊论文
Identifierhttp://libir.pmo.ac.cn/handle/332002/26689
Collection中国科学院紫金山天文台
Corresponding AuthorLu, J. Y.
Affiliation1.Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Inst Space Weather, Nanjing, Jiangsu, Peoples R China
2.Purple Mt Observ, Nanjing, Jiangsu, Peoples R China
3.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing, Jiangsu, Peoples R China
4.Nanjing Univ Informat Sci & Technol, Sch Phys & Optoelect Engn, Nanjing, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Lu, J. Y.,Jin, C. Q.,Wang, M.,et al. Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting[J]. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,2019,17(4):567-585.
APA Lu, J. Y..,Jin, C. Q..,Wang, M..,Ji, H. S..,Iluore, K..,...&Li, J. Y..(2019).Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting.SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,17(4),567-585.
MLA Lu, J. Y.,et al."Generalized Additive Modelling Combined With Multiple Collinear for ICME Velocity Forecasting".SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 17.4(2019):567-585.
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