An empirical model of the ionospheric sporadic E layer based on GNSS radio occultation data

Yu, B., Xue, X., Scott, C. J. ORCID: https://orcid.org/0000-0001-6411-5649, Yue, X. and Dou, X. (2022) An empirical model of the ionospheric sporadic E layer based on GNSS radio occultation data. Space Weather, 20 (8). e2022SW003113. ISSN 1542-7390 doi: 10.1029/2022SW003113

Abstract/Summary

The intense plasma irregularities within the ionospheric sporadic E (Es) layers at 90–130 km altitude have a significant impact on radio communications and navigation systems. As a result, the modeling of the Es layer is very important for the accuracy, reliability, and further applications of modern real-time global navigation satellite system precise point positioning. In this study, we have constructed an empirical model of the Es layer using the multivariable nonlinear least-squares-fitting method, based on the S4max from Constellation Observing System for Meteorology, Ionosphere, and Climate satellite radio occultation measurements in the period 2006–2014. The model can describe the climatology of the intensity of Es layers as a function of altitude, latitude, longitude, universal time, and day of year. To validate the model, the outputs of the model were compared with ionosonde data. The correlation coefficients of the hourly foEs and the daily maximum foEs between the ground-based ionosonde observations and model outputs at Beijing are 0.52 and 0.68, respectively. The model can give a global climatology of the intensity of Es layers and the seasonal variations of Es layers, although the Es layers during the summer are highly variable and difficult to accurately predict. The outputs of the model can be implemented in comprehensive models for a description of the climatology of Es layers and provide relatively accurate information about the global variation of Es layers.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/107154
Identification Number/DOI	10.1029/2022SW003113
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Geophysical Union
Download/View statistics	View download statistics for this item