A Comparative Study of Ionospheric Day-To-Day Variability Over Wuhan Based on Ionosonde Measurements and Model Simulations

Abstract
Ionospheric day-to-day variability is essential for understanding the space environment, while it is still challenging to properly quantify and forecast. In the present work, the day-to-day variability of F2 layer peak electron densities (NmF2) is examined from both observational and modeling perspectives. Ionosonde data over Wuhan station (30.5°N, 114.5°E; 19.3°N magnetic latitude) are compared with simulations from the specific dynamics Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (SD-WACCM-X) and the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) in 2009 and 2012. Both SD-WACCM-X and TIEGCM are driven by the realistic 3 h geomagnetic index and daily solar input, and the former includes self-consistently solved physics and chemistry in the lower atmosphere. The correlation coefficient between observations and SD-WACCM-X simulations is much larger than that of the TIEGCM simulations, especially during dusk in 2009 and nighttime in 2012. Both the observed and SD-WACCM-X simulated day-to-day variability of NmF2 reveal a similar day-night dependence in 2012 that increases large during the nighttime and decreases during the daytime, and shows favorable consistency of daytime variability in 2009. Both the observations and SD-WACCM-X simulations also display semiannual variations in nighttime NmF2 variability, although the month with maximum variability is slightly different. However, TIEGCM does not reproduce the day-night dependence or the semiannual variations well. The results emphasize the necessity for realistic lower atmospheric perturbations to characterize ionospheric day-to-day variability. This work also provides a validation of the SD-WACCM-X in terms of ionospheric day-to-day variability.
Year of Publication
2021
Journal
Journal of Geophysical Research: Space Physics
Volume
126
Number of Pages
e2020JA028589
ISSN Number
2169-9402
URL
https://onlinelibrary.wiley.com/doi/abs/10.1029/2020JA028589
DOI
10.1029/2020JA028589
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