English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Conference Paper

Plasmasphere Data Assimilation and Comparison With In-Situ Observations

Authors

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

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

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

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

Alfredo,  Del Corpo
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Massimo,  Vellante
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

Jorgensen, A., Balazs, H., Janos, L., David, K., Alfredo, D. C., Massimo, V. (2023): Plasmasphere Data Assimilation and Comparison With In-Situ Observations, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4283


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021719
Abstract
The Earth's plasmasphere is a dynamic region of dense plasma with itssource in the ionosphere. Accurate knowledge of the plasma densitydistribution and boundaries are important for the accurate modeling ofthe radiation belts and ring current growth and decay mechanisms. Theplasmasphere densities can be determined in many ways, from space andfrom the ground. However almost all such observations are limited topoint observations or single flux tube observations. For completeknowledge the regions between observations must be filled in with amodel. The combination of a model with observations to obtain anoptimal global map is called data assimilation. We will show someresults which combine a simple plasmasphere model, the Dynamic GlobalCore Plasma Model with a variety of observations in an EnsembleKalman Filter framework to produce maps of the global plasma densitydynamics. These maps are then compared with in-situ spacecraftobservations for validation.