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Predicting the Effects of Solar Storms on the Ionosphere Based on a Comparison of Real-Time Solar Wind Data with the Best-Fitting Historical Storm Event

Schmölter, Erik und Berdermann, Jens (2021) Predicting the Effects of Solar Storms on the Ionosphere Based on a Comparison of Real-Time Solar Wind Data with the Best-Fitting Historical Storm Event. Atmosphere, 12 (12). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/atmos12121684. ISSN 2073-4433.

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Offizielle URL: https://www.mdpi.com/2073-4433/12/12/1684

Kurzfassung

This study presents a new modeling approach that aims for long time predictions (more than 12 h) of ionospheric disturbances driven by solar storm events. The proposed model shall run in an operational framework to deliver fast and precise localized warnings for these disturbances in the future. The solar wind data driven approach uses a data base of historical solar storm impacts covering two solar cycles to reconstruct future events and resulting ionospheric disturbances. The basic components of the model are presented and discussed in this study, and the strengths of the reconstruction based on historical events are presented by showing the good correlations for predicted and observed geomagnetic activity. Initial results on the ionospheric response are discussed for all historical events using global total electron content (GTEC) and in more detail using total electron content (TEC) maps for two specific case studies (including the St. Patrick's Day geomagnetic storm during the 17 March 2015). Average root mean square error (RMSE) values of 3.90 and 5.21 TECU are calculated for these cases confirming good results for the current configuration of the model. Possible future improvements of the individual model parts, as well as the planned extensions and applications are discussed in detail.

elib-URL des Eintrags:https://elib.dlr.de/147936/
Dokumentart:Zeitschriftenbeitrag
Titel:Predicting the Effects of Solar Storms on the Ionosphere Based on a Comparison of Real-Time Solar Wind Data with the Best-Fitting Historical Storm Event
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Schmölter, ErikErik.Schmoelter (at) dlr.dehttps://orcid.org/0000-0002-9284-6489NICHT SPEZIFIZIERT
Berdermann, JensJens.Berdermann (at) dlr.dehttps://orcid.org/0000-0002-3308-4584NICHT SPEZIFIZIERT
Datum:16 Dezember 2021
Erschienen in:Atmosphere
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:12
DOI:10.3390/atmos12121684
Verlag:Multidisciplinary Digital Publishing Institute (MDPI)
Name der Reihe:Ionospheric Monitoring and Modelling for Space Weather
ISSN:2073-4433
Status:veröffentlicht
Stichwörter:ionosphere modeling total electron content space weather
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Projekt Weltraumwetterforschung
Standort: Neustrelitz
Institute & Einrichtungen:Institut für Solar-Terrestrische Physik > Weltraumwettereinfluß
Hinterlegt von: Schmölter, Erik
Hinterlegt am:17 Jan 2022 12:07
Letzte Änderung:17 Jan 2022 12:07

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