Abstract:
An artificial neural network-based two-dimensional ionospheric model (ANNIM) that can predict
the ionospheric F2-layer peak density (NmF2) and altitude (hmF2) had recently been developed using
long-term data of Formosat-3/COSMIC GPS radio occultation (RO) observations (Sai Gowtam & Tulasi Ram,
2017a, https://doi.org/10.1002/2017JA024795). In this current paper, we present an improved version of
ANNIM that was developed by assimilating additional ionospheric data from CHAMP, GRACE RO, worldwide
ground-based Digisonde observations, and by using a modified spatial gridding approach based on the
magnetic dip latitudes. The improved ANNIM better reproduces the spatial and temporal variations of NmF2
and hmF2, including the postsunset enhancement in equatorial hmF2 associated with the prereversal
enhancement in the zonal electric field. The ANNIM-predicted NmF2 and hmF2 exhibit excellent correlations
with ground-based Digisonde observations over different solar activity periods. The ANNIM simulations
under enhanced geomagnetic activity predict the depletion of NmF2 at auroral-high latitudes, and
enhancement over low latitude to midlatitude with respect to quiet conditions, which is consistent with the
storm time meridional wind circulation and the associated neutral composition changes. The improved
ANNIM also predicts a significant enhancement in hmF2 around auroral latitudes due to increased plasma
scale height associated with particle and Joule heating during storm periods. Further, the ANNIM
successfully reproduces the coherent oscillations in NmF2 and hmF2 with recurrent cororating interaction
region-driven geomagnetic activity during the extreme solar minimum year 2008 and can distinguish the
roles of recurrent geomagnetic activity and solar irradiance through controlled simulations.
