A Bayesian Approach to <i>F</i> ‐Region Mesoscale Flow Estimation With EISCAT_3D

Abstract The ionospheric electric field is a key parameter for understanding ionospheric electrodynamics and the magnetosphere–ionosphere coupling. Several methods have been developed to reconstruct the two‐dimensional distribution of the ionospheric electric field from line‐of‐sight (LOS) ion velocities observed by incoherent scatter radars. Approaches tailored to the upcoming tri‐static incoherent scatter radar system, EISCAT_3D (E3D), have also been proposed. In this study, we propose a new method to reconstruct mesoscale flows using a Bayesian estimation. We applied maximum a posteriori estimation to reconstruct shear flow fields with maximum velocities of 1,000 m/s at 200 km altitude. The electric field was then estimated under the assumption of drift. The reconstructed shear flows showed root‐mean‐square errors (RMSEs) of 57–101 m/s in the ion velocity and 3–5 mV/m in the electric field. Typical mesoscale flow structures were reconstructed with errors of less than 100 m/s within about 150–200 km centered on the magnetic zenith. These results demonstrate the feasibility of resolving mesoscale ionospheric structures. Our method will be extended to reconstruct electric current structures in future studies.