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Forecasting of the Upper Atmosphere via Assimilation of Electron Density Data

Kodikara, Timothy (2020) Forecasting of the Upper Atmosphere via Assimilation of Electron Density Data. EGU General Assembly 2020. EGU General Assembly 2020, 2020-05-04 - 2020-05-08, Online. doi: 10.5194/egusphere-egu2020-13024.

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Offizielle URL: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-13024.html

Kurzfassung

This study presents experiments of driving a physics-based thermosphere model (TIE-GCM) by assimilating radio occultation electron density (Ne) profiles from the COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) mission using an ensemble Kalman filter. This study not only helps to gauge the accuracy of the assimilation, to explain the inherent model bias, and to understand the limitations of the framework, but it also demonstrates the capability of the assimilation technique to forecast the highly dynamical thermosphere in the presence of realistic data assimilation scenarios. Experiments cover both solar minimum (March 2008) and solar maximum (June 2014) periods. The results show that data assimilation improves the model state. Here the improvement is shown with comparisons to Ne and neutral density data from Swarm-A, Swarm-C, CHAMP, and GRACE-A satellite missions. The root mean squared error (RMSE) of Ne is reduced in the Ne-guided lower thermosphere more than that of the higher altitudes (e.g. 1.7×10^4 electrons/cm^3 at 200 km vs 2.9×10 ^4 electrons/cm^3 at 400 km). The average RMSE in the forecasted Ne is approximately 1.3×10^5 electrons/cm^3 at altitudes between 200 and 400 km, and drops to 0.7×10^5 electrons/cm^3 at 500 km. The study also reveals that only a limited number of bonafide Ne profiles are available for assimilation tasks in the experiments. These results also provide insights into the biases inherent in the physics-based model. The systematic biases that this study highlight could be an indication that the specification of plasma-neutral interactions in the model needs further adjustments.

elib-URL des Eintrags:https://elib.dlr.de/134996/
Dokumentart:Konferenzbeitrag (Anderer)
Titel:Forecasting of the Upper Atmosphere via Assimilation of Electron Density Data
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Kodikara, TimothyTimothy.Kodikara (at) dlr.dehttps://orcid.org/0000-0003-4099-9966NICHT SPEZIFIZIERT
Datum:4 Mai 2020
Referierte Publikation:Nein
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
DOI:10.5194/egusphere-egu2020-13024
Verlag:EGU General Assembly 2020
Status:veröffentlicht
Stichwörter:Data assimilation, Ensemble Kalman filter, Thermosphere, Ionosphere. Space weather forecast
Veranstaltungstitel:EGU General Assembly 2020
Veranstaltungsort:Online
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:4 Mai 2020
Veranstaltungsende:8 Mai 2020
Veranstalter :www.egu.eu
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Kommunikation und Navigation
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R KN - Kommunikation und Navigation
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben Ionosphäre (alt)
Standort: Neustrelitz
Institute & Einrichtungen:Institut für Solar-Terrestrische Physik > Solar-Terrestrische Kopplungsprozesse
Hinterlegt von: Kodikara, Dr Timothy
Hinterlegt am:26 Aug 2020 12:59
Letzte Änderung:24 Apr 2024 20:37

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