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This paper presents a study of the global medium‐scale (scales620 km) gravity wave (GW) activity (in terms of zonal wind variance) and its seasonal, local time, and longitudinal variations by employing the enhanced‐resolution (50 km) whole atmosphere model (WAMT254) and space‐based observations for geomagnetically quiet conditions. It is found that the GW hotspots produced by WAMT254 in the troposphere and stratosphere agree well with previously well‐studied orographic and nonorographic sources. In the ionosphere‐thermosphere (IT) region, GWs spread out forming latitudinal band‐like hotspots. During solstices, a primary maximum in GW activity is observed in WAMT254 and GOCE over winter mid‐high latitudes, likely associated with higher‐order waves with primary sources in polar night jet, fronts, and polar vortex. During all the seasons, the enhancement of GWs around the geomagnetic poles as observed by GOCE (at 250 km) is well captured by simulations. WAMT254 GWs in the IT region also show dependence on local time due to their interaction with migrating tides leading to diurnal and semidiurnal variations. The GWs are more likely to propagate up from the MLT region during westward/weakly eastward phase of thermospheric tides, signifying the dominance of eastward GW momentum flux in the MLT. Additionally, as a novel finding, a wavenumber‐4 signature in GW activity is predicted by WAMT254 between 6 and 12 local times in the tropics at 250 km, which propagates eastward with local time. This behavior is likely associated with the modulation of GWs by wave‐4 signal of nonmigrating tides in the lower thermospheric zonal winds. 

Abstract On 3 February 2022, at 18:13 UTC, SpaceX launched and a short time later deployed 49 Starlink satellites at an orbit altitude between 210 and 320 km. The satellites were meant to be further raised to 550 km. However, the deployment took place during the main phase of a moderate geomagnetic storm, and another moderate storm occurred on the next day. The resulting increase in atmospheric drag led to 38 out of the 49 satellites reentering the atmosphere in the following days. In this work, we use both observations and simulations to perform a detailed investigation of the thermospheric conditions during this storm. Observations at higher altitudes, by Swarm‐A (∼438 km, 09/21 Local Time [LT]) and the Gravity Recovery and Climate Experiment Follow‐On (∼505 km, 06/18 LT) missions show that during the main phase of the storms the neutral mass density increased by 110% and 120%, respectively. The storm‐time enhancement extended to middle and low latitudes and was stronger in the northern hemisphere. To further investigate the thermospheric variations, we used six empirical and first‐principle numerical models. We found the models captured the upper and lower thermosphere changes, however, their simulated density enhancements differ by up to 70%. Further, the models showed that at the low orbital altitudes of the Starlink satellites (i.e., 200–300 km) the global averaged storm‐time density enhancement reached up to ∼35%–60%. Although such storm effects are far from the largest, they seem to be responsible for the reentry of the 38 satellites. 

Abstract. It is well known that the polar cap, delineated by the open–closed field line boundary (OCB),responds to changes in the interplanetary magnetic field (IMF).In general, the boundary moves equatorward when the IMF turns southward and contractspoleward when the IMF turns northward. However,observations of the OCB are spotty and limited in local time,making more detailed studies of its IMF dependence difficult.Here, we simulate five solar storm periods with the coupled model consisting of the OpenGeospace General Circulation Model (OpenGGCM) coupled with the Coupled Thermosphere IonosphereModel (CTIM) and the Rice Convection Model (RCM),i.e., the OpenGGCM-CTIM-RCM, to estimate the location and dynamics of the OCB.For these events, polar cap boundary location observations are also obtained from Defense MeteorologicalSatellite Program (DMSP) precipitation spectrograms and compared with the model output.There is a large scatter in the DMSP observations and in the model output.Although the model does not predict the OCB with high fidelity for every observation,it does reproduce the general trend as a function of IMF clock angle.On average, the model overestimates the latitude of the open–closed field line boundaryby 1.61∘. Additional analysis of the simulated polar cap boundary dynamics acrossall local times shows that the MLT of the largest polar cap expansion closely correlateswith the IMF clock angle, that the strongest correlation occurs when the IMF is southward, thatduring strong southward IMF the polar cap shifts sunward, and that the polar cap rapidlycontracts at all local times when the IMF turns northward. 

An expression of Rayleigh‐Taylor (R‐T) instability growth rate based on the field‐line integrated theory is newly established. This expression can be directly utilized in ionosphere models with magnetic flux tube structure based on Modified Apex Coordinates. The R‐T instability growth rates are calculated using the thermospheric and ionospheric conditions based on the coupled Whole Atmosphere Model and Ionosphere Plasmasphere Electrodynamic model (WAM‐IPE). The parameters used in this calculation include the field‐line integrated conductivities and currents, which consider the Quasi‐Dipole Coordinates and the modifications to the equations of electrodynamics. Detailed description of the new formulas and comprehensive analyses of diurnal, longitudinal, and seasonal variations of the R‐T instability growth rate are carried out. The dependencies of growth rates on pre‐reversal enhancement (PRE) vertical drifts and solar activity are also examined. The results show that pronounced R‐T growth rates are captured between 18 and 22 local time (LT) when strong PRE occurs in the equatorial ionosphere. The simulated R‐T growth rate increases with increasing solar activity levels and demonstrates strong correlations with the angle between the sunset terminator and the geomagnetic field line. These results are consistent with plasma irregularity occurrence rates shown in various satellite observations, suggesting that the newly developed R‐T growth rate calculation can effectively capture the probability of irregularities by considering the changes along magnetic flux‐tubes in the ionosphere. Since the WAM‐IPE is running in operation at National Oceanic and Atmospheric Administration Space Weather Prediction Center, the new calculations can be potentially implemented in the near future to provide forecasted information of the R‐T growth rate. 

Abstract The Iterative Driver Estimation and Assimilation (IDEA) data assimilation technique was used with the Whole Atmosphere Model (WAM) to improve neutral density specification in the upper thermosphere. Two different neutral density data sources were examined to enhance the capability of simulating the global thermospheric state. The first were accelerometer estimates of neutral density from the Challenging Mini‐Satellite Payload (CHAMP) satellite. The second were neutral density estimates from the Global Ultraviolet Imager (GUVI) limb‐scan airglow observations aboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. Due to the intensity of the November 2003 storm, two changes were necessary in WAM. The first was allowing the Kp geomagnetic index to exceed 9 and the second was changing the relationship between Kp and the solar wind parameters used to drive the model. With these changes, results show that IDEA effectively captures the thermospheric neutral density at the CHAMP satellite altitude and follows the time‐dependence through the November 2003 storm period. Furthermore, a cross‐comparison was conducted with the GUVI dayside limb scan measurements. GUVI neutral densities within 270–320 km show the closest agreement with WAM when CHAMP data was assimilated by IDEA. We speculate on the potential for observations from GUVI at 300 km to be used as a data source in the IDEA‐WAM simulations. These simulations demonstrate the utility of the IDEA data assimilation technique with physical models and that using either accelerometer observations or ultraviolet airglow limb measurement during extreme storm periods could be used.