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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, 04.-08. Mai. 2020, Online. doi: 10.5194/egusphere-egu2020-13024.

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


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.

Item URL in elib:https://elib.dlr.de/134996/
Document Type:Conference or Workshop Item (Other)
Title:Forecasting of the Upper Atmosphere via Assimilation of Electron Density Data
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Kodikara, TimothyUNSPECIFIEDhttps://orcid.org/0000-0003-4099-9966UNSPECIFIED
Date:4 May 2020
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
Publisher:EGU General Assembly 2020
Keywords:Data assimilation, Ensemble Kalman filter, Thermosphere, Ionosphere. Space weather forecast
Event Title:EGU General Assembly 2020
Event Location:Online
Event Type:international Conference
Event Dates:04.-08. Mai. 2020
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Communication and Navigation
DLR - Research area:Raumfahrt
DLR - Program:R KN - Kommunikation und Navigation
DLR - Research theme (Project):R - Vorhaben Ionosphäre (old)
Location: Neustrelitz
Institutes and Institutions:Institute for Solar-Terrestrial Physics > Solar-Terrestrial Coupling Processes
Deposited By: Kodikara, Dr Timothy
Deposited On:26 Aug 2020 12:59
Last Modified:06 Jun 2023 17:16

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