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Estimation and Prediction of Solar Wind Propagation from L1 Point to Earth’s Bow Shock

Tasnim, Samira and Zou, Ying and Borries, Claudia and Baumann, Carsten and Walsh, Brian and Khanal, Krishna and O'Brien, Connor (2022) Estimation and Prediction of Solar Wind Propagation from L1 Point to Earth’s Bow Shock. AGU Fall Meeting 2022. AGU Meeting 2022, 12th - 16th Dec 2022, Chicago, IL, USA.

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Official URL: https://www.agu.org/Fall-Meeting

Abstract

Having precise knowledge of the near-Earth solar wind (SW) and the embedded interplanetary magnetic field (IMF) is of critical importance to space weather operation due to the usage of SW and IMF in almost all magnetospheric and ionospheric models. The most widely used data source, OMNI, propagates SW properties from Lagrangian point L1 to the Earth’s bow shock by estimating the propagation time of the SW. However, the time difference between OMNI timeshifted IMF and the best match-up of IMF can reach ˜15 min. Firstly, we aim to develop an improved statistical algorithm to contribute to the SW propagation delay problem of space weather prediction. The algorithm focuses on matching SW features around the L1 point and upstream of the bow shock by computing the variance, cross-correlation coefficient, the plateau-shaped magnitude index, and the non-dimensional measure of average error index between the measurements at the two locations. The obtained propagation times are then compared to OMNI. Factors that limit the OMNI accuracy are also examined. Secondly, the automatic algorithm allows us to generate large sets of input and target variables using multiple spacecraft pairs at L1 and near-Earth locations to train, validate, and test machine learning models to specify and forecast near-Earth SW conditions. Finally, we offer a machine learning (ML) approach to specify and predict the propagation time from L1 monitors to a given location upstream or at the bow shock and forecast near-Earth SW conditions with the gradient boosting and random forest prediction models in the form of an ensemble of decision trees.

Item URL in elib:https://elib.dlr.de/192936/
Document Type:Conference or Workshop Item (Poster)
Title:Estimation and Prediction of Solar Wind Propagation from L1 Point to Earth’s Bow Shock
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Tasnim, SamiraUNSPECIFIEDhttps://orcid.org/0000-0002-0305-2071UNSPECIFIED
Zou, YingUNSPECIFIEDhttps://orcid.org/0000-0002-9704-1735UNSPECIFIED
Borries, ClaudiaUNSPECIFIEDhttps://orcid.org/0000-0001-9948-3353UNSPECIFIED
Baumann, CarstenUNSPECIFIEDhttps://orcid.org/0000-0001-7104-5992UNSPECIFIED
Walsh, BrianUNSPECIFIEDhttps://orcid.org/0000-0001-7426-5413UNSPECIFIED
Khanal, KrishnaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
O'Brien, ConnorUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:10 August 2022
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Publisher:AGU Fall Meeting 2022
Status:Accepted
Keywords:Solar Wind Propagation Delay, Earth's Bow Shock
Event Title:AGU Meeting 2022
Event Location:Chicago, IL, USA
Event Type:international Conference
Event Dates:12th - 16th Dec 2022
Organizer:American Geophysical Union
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Scaling of machine learning methods
Location: Neustrelitz
Institutes and Institutions:Institute for Solar-Terrestrial Physics > Solar-Terrestrial Coupling Processes
Deposited By: Tasnim, Samira
Deposited On:22 May 2023 14:48
Last Modified:22 May 2023 14:48

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