Artículos de revistas
Assessment of global ionospheric maps performance by means of ionosonde data
Fecha
2020-10-02Registro en:
Remote Sensing, v. 12, n. 20, p. 1-18, 2020.
2072-4292
10.3390/rs12203452
2-s2.0-85093955920
Autor
Universidade Estadual Paulista (Unesp)
UPC-IonSAT and UPC-IEEC Research Groups
German Aerospace Center (DLR)
Institución
Resumen
This work presents a new method for assessing global ionospheric maps (GIM) using ionosonde data. The method is based on the critical frequency at the F2 layer directly measured by ionosondes to validate VTEC (vertical total electron content) values from GIMs. The analysis considered four different approaches to using foF2. The study was performed over one of the most challenging scenarios, the Brazilian region, considering four ionosondes (combined in six pairs) and thirteen GIM products available at CDDIS (Crustal Dynamics Data Information System). Analysis was conducted using daily, weekly, one year (2015), and four years (2014–2017) of data. Additional information from the ionosphere was estimated to complement the daily analysis, such as slab thickness and shape function peak. Results indicated that slab thickness and shape function peak could be used as alternative indicators of periods and regions where this method could be applied. The weekly analysis indicated the squared frequency ratio with local time correction as the best approach of using foF2, between the ones evaluated. The analysis of one-year data (2015) was performed considering thirteen GIMs, where CODG and UQRG were the two GIMs that presented the best performance. The four-year time series (2014–2017) were analyzed considering these two products. Regional and temporal ionospheric influences could be noticed in the results, with expected larger errors during the solar cycle peak in 2014 and at locations with pairs of ionosondes with the larger distance apart. Therefore, we have confirmed the viability of the developed approach as an assessment method to analyze GIMs quality based on ionosonde data.