Three-dimensional data assimilation for ionospheric reference scenarios
| Autor: | Volker Wilken, Tatjana Gerzen, Stefan Schlüter, Mohammed Mainul Hoque, David Minkwitz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Atmospheric Science
reconstruction 010504 meteorology & atmospheric sciences TEC 02 engineering and technology tomography 01 natural sciences Physics::Geophysics Data assimilation 0202 electrical engineering electronic engineering information engineering Earth and Planetary Sciences (miscellaneous) Radio occultation Ionosphere electron density lcsh:Science 0105 earth and related environmental sciences Remote sensing Total electron content ionosonde lcsh:QC801-809 data Assimilation 020206 networking & telecommunications Geology Astronomy and Astrophysics lcsh:QC1-999 STEC lcsh:Geophysics. Cosmic physics Space and Planetary Science GNSS applications Physics::Space Physics Environmental science lcsh:Q Satellite Ionosonde lcsh:Physics |
| Zdroj: | Annales Geophysicae, Vol 35, Pp 203-215 (2017) |
| ISSN: | 1432-0576 |
| Popis: | The reliable estimation of ionospheric refraction effects is an important topic in the GNSS (Global Navigation Satellite Systems) positioning and navigation domain, especially in safety-of-life applications. This paper describes a three-dimensional ionosphere reconstruction approach that combines three data sources with an ionospheric background model: space- and ground-based total electron content (TEC) measurements and ionosonde observations. First the background model is adjusted by F2 layer characteristics, obtained from space-based ionospheric radio occultation (IRO) profiles and ionosonde data, and secondly the final electron density distribution is estimated by an algebraic reconstruction technique.The method described is validated by TEC measurements of independent ground-based GNSS stations, space-based TEC from the Jason 1 and 2 satellites, and ionosonde observations. A significant improvement is achieved by the data assimilation, with a decrease in the residual errors by up to 98 % compared to the initial guess of the background. Furthermore, the results underpin the capability of space-based measurements to overcome data gaps in reconstruction areas where less GNSS ground-station infrastructure exists. |
| Databáze: | OpenAIRE |
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