Adapting a climatology model to improve estimation of ionosphere parameters and subsequent validation with radio occultation and ionosonde data

作者:Habarulema John Bosco*; Ssessanga Nicholas
来源:Space Weather-The International Journal of Research and Applications, 2017, 15(1): 84-98.
DOI:10.1002/2016SW001549

摘要

This paper reports on the adaptation and modification of a climatological model, the International Reference Ionosphere (IRI 2012 model) with the use of total electron content (TEC) data derived from the Global Navigation Satellite System (GNSS), and most importantly its subsequent validation with both radio occultation from Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and ionosonde data. By adjusting the solar activity indices used within the standard IRI 2012 model with the aim of minimizing error differences between IRI TEC and GNSS TEC, the adjusted indices are used as drivers of the IRI 2012 model on a regional scale and results for electron density (Ne) profiles, maximum height of the F-2 layer (h(m)F(2)), TEC, and critical frequency of the F-2 layer (f(o)F(2)) generated. Validation was done by direct comparison with ionosonde and COSMIC-derived data parameters. By averaging results over low, equatorial, and midlatitude regions, the modified IRI 2012 gave an improvement of about 18% in estimating TEC during the storm period of 9 March 2012. An important result observed during our candidate period of study is that COSMIC data provides maximum electron density of the F-2 layer (NmF2) and h(m)F(2) closer to ionosonde data even during the disturbed period and is hence a suitable data set that can be incorporated into the climatological IRI model to improve its performance. The Ne profiles from the modified IRI 2012 model accurately approximates ionosonde Ne profiles especially below 300 km altitude but underestimates the ionosonde NmF2 and hence f(o)F(2) in midlatitude regions. In most cases both standard and modified IRI 2012 models match COSMIC data for topside electron density representation, making the COSMIC data set a valuable resource for the improvement of ionospheric climatological models.

  • 出版日期2017-1