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  1. Abstract

    The semidiurnal tidal spectrum in the F‐region ionosphere obtained from hourly COSMIC‐2 Global Ionospheric Specification (GIS) data assimilation is greatly (>50%) enhanced during the January 2021 Sudden Stratospheric Warming (SSW). Moreover, the semidiurnal migrating tidal response in topside electron densities closely follows the day‐to‐day changes of the 10 hPa, 60°N zonal wind from MERRA‐2 during the SSW. The response is similar in the northern and southern crests of the Equatorial Ionization Anomaly (EIA) but persists toward higher magnetic latitudes and the EIA trough. A slight phase shift toward earlier local times is consistent with theoretical expectations of an E‐region dynamo driving and agrees with semidiurnal tidal diagnostics of MIGHTI/ICON zonal winds at 105 km. COSMIC‐2 GIS are the first data set to resolve the tidal weather of the ionosphere on a day‐to‐day basis and, therefore, provide a new perspective on space weather variability driven by lower and middle atmosphere dynamics.

     
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  2. Abstract

    We develop a new methodology for the multi‐resolution assimilation of electric fields by extending a Gaussian process model (Lattice Kriging) used for scalar field originally to vector field. This method takes the background empirical model as “a priori” knowledge and fuses real observations under the Gaussian process framework. The comparison of assimilated results under two different background models and three different resolutions suggests that (a) the new method significantly reduces fitting errors compared with the global spherical harmonic fitting (SHF) because it uses range‐limited basis functions ideal for the local fitting and (b) the fitting resolution, determined by the number of basis functions, is adjustable and higher resolution leads to smaller errors, indicating that more structures in the data are captured. We also test the sensitivity of the fitting results to the total amount of input data: (a) as the data amount increases, the fitting results deviate from the background model and become more determined by data and (b) the impacts of data can reach remote regions with no data available. The assimilation also better captures short‐period variations in local PFISR measurements than the SHF and maintains a coherent pattern with the surrounding. The multi‐resolution Lattice Kriging is examined via attributing basis functions into multiple levels with different resolutions (fine level is located in the region with observations). Such multi‐resolution fitting has the smallest error and shortest computation time, making the regional high‐resolution modeling efficient. Our method can be modified to achieve the multi‐resolution assimilation for other vector fields from unevenly distributed observations.

     
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  3. We quantify the short-term (<30 day) variability of column O/N 2 measured by GOLD from January 2019 to August 2022 for various geomagnetic activity conditions. We find enhanced variabilities at high latitudes during active (Kp ≥ 3.0) times and weak but statistically significant variabilities at low latitudes. For active times, the largest absolute variability of O/N 2 ratio is 0.14 and the largest relative variability is 20.6% at ∼60.0°N in Fall, which are about twice those of quiet times. The variability at higher latitudes can be larger than that of lower latitudes by a factor of 5–8. We further quantify contributions of magnetospheric forcing to O/N 2 variability in the Ionosphere-Thermosphere region by correlating O/N 2 perturbations with Dst. During geomagnetic active times, positive correlations as large as +0.66 and negative correlations as large as −0.65 are found at high and low latitudes, respectively, indicative of storm-induced O and N 2 upwelling at high latitudes and down welling at low latitudes. During quiet times, correlations between O/N 2 perturbations and Dst become insignificant at all latitudes, implying a more substantial contribution from below. O/N 2 variabilities maximize in Fall and decrease towards Summer, while correlations maximize in Spring/Summer and decrease in Winter/Spring, which may be related to seasonal variations of geomagnetic activity and mean circulation. 
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