English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Conference Paper

Method of neutral density uncertainty estimation for satellite measurements based on data assimilation into a physics-based model

Authors

Fernandez Gomez,  Isabel
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Stefan,  Codrescu
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Timothy,  Kodikara
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Frank,  Heymann
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Claudia,  Borries
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in GFZpublic
Supplementary Material (public)
There is no public supplementary material available
Citation

Fernandez Gomez, I., Stefan, C., Timothy, K., Frank, H., Claudia, B. (2023): Method of neutral density uncertainty estimation for satellite measurements based on data assimilation into a physics-based model, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3193


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020365
Abstract
We developed a method to estimate the uncertainty in thermospheric neutral density measurements by assimilating these data into a physics-based model. Thermospheric neutral density is a critical parameter characterizing the upper atmosphere. Neutral density in this region impacts satellites in low Earth orbit through drag. Uncertainty in neutral density results in uncertainty in satellite trajectory calculations. For issues such as collision avoidance, it is important to understand the uncertainty in these measurements. While physics-based models can predict the behavior of the upper atmosphere, their accuracy is limited by our incomplete knowledge of the physical processes and inputs to the system. Data assimilation combines model predictions with measurements according to their uncertainties. In this study, we use the Coupled Thermosphere Ionosphere Plasmasphere with Electrodynamics (CTIPe) model while varying the measurement uncertainty input into the assimilation process to estimate satellite-derived neutral density uncertainty. The method was applied to data from two different missions, CHAMP and Swarm, during quiet geomagnetic conditions. Results from our uncertainty estimation will be presented.