The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data

Abstract

This study presents a comprehensive comparison of the impact of solar activity on forecasting the upper atmosphere through assimilation of radio occultation (RO)-derived electron density ($Ne$) into a physics-based model (TIE-GCM) using an ensemble Kalman filter (KF). Globally abundant RO-derived $Ne$ offers one of the most promising means to test the effect of assimilation on the model forecasted state on a global scale. This study emphasizes the importance of understanding how the assimilation results vary with solar activity, which is one of the main drivers of thermosphere-ionosphere dynamics. This study validates the forecast states with independent RO-derived GRACE (Gravity Recovery and Climate Experiment mission) $Ne$ data. The principal result of the study is that the agreement between forecast $Ne$ and data is better during solar minimum than solar maximum. The results also show that the agreement between data and forecast is mostly better than that of the standalone TIE-GCM driven with observed geophysical indices. The results emphasize that TIE-GCM significantly underestimate $Ne$ in altitudes below 250~km and the assimilation of $Ne$ is not as effective in these lower altitudes as it is in higher altitudes. The results demonstrate that assimilation of $Ne$ significantly impacts the neutral mass density ($\rho$) estimates via the KF state vector---the impact is larger during solar maximum than solar minimum relative to a nonassimilation run. The results are useful to explain the inherent model bias, to understand the limitations of the data, and to demonstrate the capability of the assimilation technique.