Abstract
This work describes several important improvements made to the International Reference Ionosphere UPdate (IRI UP) method, and a careful validation of its performances under disturbed conditions. The IRI UP method has been improved developing an algorithm capable to properly filter wrongly autoscaled ionosonde data to be assimilated, avoiding the use of these in the assimilation process. Furthermore, the preliminary quality check used to choose the variogram model in the Universal Kriging method has been replaced with a new quality check routine (NQCR), based on statistical tests carried out using the variables Q1, Q2, and cR, built on variogram’s residuals. NQCR objectively identifies the best variogram model from which to get more reliable effective indices maps to be ingested in the IRI model to obtain updated foF2 and hmF2 maps. IRI UP has been applied on 30 different time intervals, between January 1, 2004, and December 31, 2016, characterized by moderate, strong, and severe geomagnetic conditions, over the European region. A statistical comparison between IRI UP and IRI at the truth sites located at Fairford (51.7°N, 1.5°W, UK) and San Vito (40.6°N, 17.8°E, Italy), for foF2 and hmF2, has been performed. From the statistical validation clearly emerges how IRI UP, for foF2, performs significantly better than IRI, for each of the 30 geomagnetic storms considered. Regarding hmF2, IRI UP performances are lower than those for foF2, although still better than IRI ones. In the light of the results achieved in this investigation, the IRI UP method represents an interesting approach to Space Weather forecast in the ionospheric domain.
Highlights
Space Weather events can significantly affect the functioning of radio systems, with effects that can be rapid or delayed
With regard to these two issues, in the work of Pignalberi et al (2018a, b), the reliability of foF2 and M(3000) F2 autoscaled data was based on a quality check of ionograms: for the reference stations equipped with the Automatic Real-Time Ionogram Scaler with True height analysis (ARTIST) software (Reinisch and Huang 1983; Reinisch et al 2005; Galkin and Reinisch 2008), only ionograms with a Confidence Score (CS) greater than 75 were selected; for the reference stations equipped with the Autoscala software (Scotto and Pezzopane 2002, 2008; Pezzopane and Scotto 2005, 2007; Scotto 2009; Scotto et al 2012), a careful visual inspection was adopted to select the reliable ionograms
The problem of how to choose among the possible variogram models described in “The Kriging interpolation method: a brief recall” section is of crucial importance, because this choice greatly affects the goodness of the IG12eff and R12eff maps and, the capability of delivering an accurate and trustworthy foF2, M(3000)F2, and hmF2 modeling
Summary
Space Weather events can significantly affect the functioning of radio systems, with effects that can be rapid (immediately after the event) or delayed (a few days after the event). In order to get a proper interpolation and reliable IG12eff and R12eff maps, it is extremely important that selected variogram models have a good quality With regard to these two issues, in the work of Pignalberi et al (2018a, b), the reliability of foF2 and M(3000) F2 autoscaled data was based on a quality check of ionograms: for the reference stations equipped with the Automatic Real-Time Ionogram Scaler with True height analysis (ARTIST) software (Reinisch and Huang 1983; Reinisch et al 2005; Galkin and Reinisch 2008), only ionograms with a Confidence Score (CS) greater than 75 (see http://www.ursi.org/files/CommissionWebsites/ INAG/web-73/confidence_score.pdf ) were selected; for the reference stations equipped with the Autoscala software (Scotto and Pezzopane 2002, 2008; Pezzopane and Scotto 2005, 2007; Scotto 2009; Scotto et al 2012), a careful visual inspection was adopted to select the reliable ionograms. This has a dual objective: (a) to improve the level of
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