Abstract:
Vertical EXB drift measured using the ionosonde Doppler sounding during the daytime suffers
from an underestimation of the actual EXB drift because the reflection height of the ionosonde signals is also affected by the photochemistry of the ionosphere. Systematic investigations have indicated a fair/good correlation to exist between the C/NOFS and ionosonde Doppler-measured vertical EXB drift during the daytime over magnetic equator. A detailed analysis, however, indicated that the linear relation between the ionosonde Doppler drift and C/NOFS EXB drift varied with seasons. Thus, solar, seasonal, and also geomagnetic variables were included in the Doppler drift correction, using the artificial neural network-based approach. The RMS error in the neural network was found to be smaller than that in the linear regression analysis. Daytime EXB drift was derived using the neural network which was also used to model the ionospheric redistribution in the SAMI2 model. SAMI2 model reproduced strong (weak) equatorial ionization anomaly (EIA) for cases when neural network corrected daytime vertical EXB drift was high (low). Similar features were also observed in GIM TEC maps. Thus, the results indicate that the neural network can be utilized to derive the vertical EXB drift from its proxies, like the ionosonde Doppler drift. These results indicate that the daytime ionosonde measured vertical EXB drift can be relied upon, provided that adequate corrections are applied to it.
