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  5. Effective Solar Indices for Ionospheric Modeling: A Review and a Proposal for a Real-Time Regional IRI
 
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Effective Solar Indices for Ionospheric Modeling: A Review and a Proposal for a Real-Time Regional IRI

Author(s)
Pignalberi, Alessio  
Dipartimento di Fisica e Astronomia, Universita` di Bologna ‘‘Alma Mater Studiorum’’, Viale Berti Pichat 6/2, 40127 Bologna, Italy  
Pezzopane, Michael  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma2, Roma, Italia  
Rizzi, R.  
Dipartimento di Fisica e Astronomia, Universita` di Bologna ‘‘Alma Mater Studiorum’’, Viale Berti Pichat 6/2, 40127 Bologna, Italy  
Galkin, I.  
Space Science Laboratory, University of Massachusetts, 600 Suffolk Street, Lowell, MA 01854, USA  
Language
English
Obiettivo Specifico
2A. Fisica dell'alta atmosfera
1IT. Reti di monitoraggio
4IT. Banche dati
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Journal
Surveys in Geophysics  
Issue/vol(year)
/39 (2018)
Pages (printed)
125-167
Date Issued
January 2018
DOI
10.1007/s10712-017-9438-y
URI
https://www.earth-prints.org/handle/2122/10669
Abstract
The first part of this paper reviews methods using effective solar indices to update a background ionospheric model focusing on those employing the Kriging method to perform the spatial interpolation. Then, it proposes a method to update the International Reference Ionosphere (IRI) model through the assimilation of data collected by a European ionosonde network. The method, called International Reference Ionosphere UPdate (IRI UP), that can potentially operate in real time, is mathematically described and validated for the period 9–25 March 2015 (a time window including the well-known St. Patrick storm occurred on 17 March), using IRI and IRI Real Time Assimilative Model (IRTAM) models as the reference. It relies on foF2 and M(3000)F2 ionospheric characteristics, recorded routinely by a network of 12 European ionosonde stations, which are used to
calculate for each station effective values of IRI indices IG12 and R12 (identified as IG12eff and R12eff ); then, starting from this discrete dataset of values, two-dimensional (2D) maps of IG12eff and R12eff are generated through the universal Kriging method. Five variogram models are proposed and tested statistically to select the best performer for each effective index. Then, computed maps of IG12eff and R12eff are used in the IRI model to synthesize updated values of foF2 and hmF2. To evaluate the ability of the proposed method to reproduce rapid local changes that are common under disturbed conditions, quality metrics are calculated for two test stations whose measurements were not assimilated in IRI UP, Fairford (51.7°N, 1.5°W) and San Vito (40.6°N, 17.8°E), for IRI, IRI UP, and IRTAM models. The proposed method turns out to be very effective under highly disturbed conditions, with significant improvements of the foF2 representation and noticeable improvements of the hmF2 one. Important improvements have been verified also for quiet and moderately disturbed conditions. A visual analysis of foF2 and hmF2 maps highlights the ability of the IRI UP method to catch small-scale changes occurring under disturbed conditions which are not seen by IRI.
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