IRI and NeQuick representation of the Winter Anomaly: a comparison with GNSS-derived TEC data
Abstract
International Reference Ionosphere (IRI) and NeQuick2 are renowned empirical models conceived to represent the climatological behavior of the ionosphere. They are able to estimate the electron concentration at any given location and time in the near-Earth space and therefore the vertical total electron content (vTEC) by means of numerical integration. In this work an assessment has been done on IRI and NeQuick models' capability to reproduce the main features of the Winter Anomaly (WA), the phenomenon consisting in the fact that at a given location the (daytime) maximum vTEC (or foF2) is greater in winter than in summer. Two approaches have been considered to analyse the relevant hemispheric asymmetry of IRI and NeQuick. The first one has been focused on the models' representation of the WA in terms of its occurrence as a function of solar activity and geographic location. The second approach has been based on the comparison of the winter and summer vTEC daily patterns produced by the models, with the corresponding (median) vTEC daily patterns experimentally-derived from a specific set of International GNSS Service (IGS) receivers. For this purpose, the LPIM software has been utilised and GNSS-derived vTEC values corresponding to the period 1998 - 2018 have been estimated at 15 minutes time interval for 20+ stations during solar cycle 23 and 40+ stations during solar cycle 24. The first analysis results indicate that, as expected, IRI and NeQuick exhibit a hemispheric asymmetry in the representation of the WA. Then, in some geographic regions, the models tend to over-represent the WA by (i) predicting its occurrence (especially during low solar activity periods) where GNSS-derived TEC data do not show clear WA effects and (ii) by overestimating the Winter-minus-Summer vTEC difference during periods of high solar activity, when the existence of WA effects is correctly predicted in agreement with the experimental evidence.
- Publication:
-
43rd COSPAR Scientific Assembly. Held 28 January - 4 February
- Pub Date:
- January 2021
- Bibcode:
- 2021cosp...43E.800N