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Towards Cooperative Global Mapping of the Ionosphere: Fusion Feasibility for IGS and IRI with Global Climate VTEC Maps

Authors :
Adam Froń
Ivan Galkin
Andrzej Krankowski
Dieter Bilitza
Manuel Hernández-Pajares
Bodo Reinisch
Zishen Li
Kacper Kotulak
Irina Zakharenkova
Iurii Cherniak
David Roma Dollase
Ningbo Wang
Paweł Flisek
Alberto García-Rigo
Source :
Remote Sensing, Vol 12, Iss 21, p 3531 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

Recommendations of the International Reference Ionosphere (IRI) Workshop 2017 in Taoyuan City, Taiwan and International GNSS Service (IGS) Workshop 2018 in Wuhan, China included establishment of an ionosphere mapping service that would fuse measurements from two independent sensor networks: IGS permanent GNSS receivers providing the vertical total electron content (VTEC) measurements and ionosondes of the Global Ionosphere Radio Observatory (GIRO) that compute the bottomside vertical profiles of the ionospheric plasma density. Using available GAMBIT software at GIRO, we introduced new VTEC products to its data roster: previously unavailable global average (climate) maps of VTEC and slab thickness based on climatological capabilities of IRI. Incorporation of the VTEC and τ maps into the GAMBIT Explorer environment provided data analysts with nearly 10-year history of the reference average VTEC records and opened access to the GAMBIT toolkit for evaluation and validation of the τ computations. This result is the first step towards establishing an infrastructure and the data workflow to provide GAMBIT users with the low latency and consistent quality and usability of the ionospheric weather-climate specifications. Combination of IGS-provided VTEC and GIRO-provided peak density of F2 layer NmF2 allows ground-based evaluation of the equivalent slab thickness τ, a derived property of the near-Earth plasma that characterizes the skewness of its vertical profile up to the GNSS spacecraft altitudes.

Details

Language :
English
ISSN :
20724292
Volume :
12
Issue :
21
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.92c68a5fcbfb4389ab1381ec2ca76e2f
Document Type :
article
Full Text :
https://doi.org/10.3390/rs12213531