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Abstract Observation‐based simulations of the ionosphere were performed with the NRLMSISE‐00 model for six locations around the globe during 1–9 February 2022, which includes the so‐called Starlink Storm. Unlike other studies, we focused on the magnetically quiet days around the storm. Unexpectedly, the observed values of the F2‐layer peak density were ∼50% larger than the simulated values. We show that this implies that the daytime O density in the thermosphere was systematically ∼30% larger than the NRLMSISE‐00 predicts. Further investigation shows that this discrepancy is not an exclusive feature of the period around the Starlink Storm and a similar problem happens for some periods for different years. It is unclear if the reason is an actual increase of the O density or its underestimation by the model. Resolving this problem is critical for providing accurate predictions of the atmosphere to avoid the degradation of normal operation or even loss of space assets. 

Abstract Local empirical models of the F2 layer peak electron density (NmF2) are developed for 43 low‐ middle latitude ionosonde stations using auto‐scaled data from Lowell GIRO data center and manually scaled data from World Data Center for Ionosphere and Space Weather. Data coverage at these stations ranges from a few years to up to 6 decades. Flare Irradiance Spectral Model index version 2 (FISM2) and ap3 index are used to parametrize the solar extreme ultraviolet (EUV) flux and geomagnetic activity dependence of NmF2. Learning curves suggest that approximately 8 years of data coverage is required to constrain the solar activity dependence of NmF2. Output of local models altogether captures well known anomalies of the F2 ionospheric layer. Performance metrics demonstrate that the model parametrized using FISM2 has better accuracy than a similarly parametrized model with F10.7, as well as than the IRI‐2020 model. Skill score metrics indicate that the FISM2 based model outperforms F10.7 model at all solar activity levels. The improved accuracy of model with FISM2 over F10.7 is due to better representation of solar rotation by FISM2, and due to its performance at solar extremum. Application of singular spectrum analysis to model output reveals that solar rotation contributes to about 2%–3% of the variance in NmF2 data and FISM2 based model, while F10.7 based models overestimate the strength of solar rotation to be at 4%–7%. At solar extremum, both F10.7‐based model and IRI‐2020 tend to overestimate the NmF2 while FISM2 provides the most accurate prediction out of three. 

Abstract This study focuses on understanding what drives the previously observed deep nighttime ionospheric hole in the American sector during the January 2013 sudden stratospheric warming (SSW). Performing a set of numerical experiments with the thermosphere‐ionosphere‐mesosphere‐electrodynamics general circulation model (TIME‐GCM) constrained by a high‐altitude version of the Navy Global Environmental Model, we demonstrate that this nighttime ionospheric hole was the result of increased poleward and down magnetic field line plasma motion at low and midlatitudes in response to alteredF‐region neutral meridional winds. Thermospheric meridional wind modifications that produced this nighttime depletion resulted from the well‐known enhancements in semidiurnal tidal amplitudes associated with stratospheric warming (SSWs) in the upper mesosphere and thermosphere. Investigations into other deep nighttime ionospheric depletions and their cause were also considered. Measurements of total electron content from Global Navigation Satellite System receivers and additional constrained TIME‐GCM simulations showed that nighttime ionospheric depletions were also observed on several nights during the January‐February 2010 SSW, which resulted from the same forcing mechanisms as those observed in January 2013. Lastly, the recent January 2021 SSW was examined using Modern‐Era Retrospective Analysis for Research and Applications, Version 2, COSMIC‐2 Global Ionospheric Specification electron density, and ICON Michelson Interferometer for Global High‐Resolution Thermospheric Imaging horizontal wind data and revealed a deep nighttime ionospheric depletion in the American sector was likely driven by modified meridional winds in the thermosphere. The results shown herein highlight the importance of thermospheric winds in driving nighttime ionospheric variability over a wide latitude range. 

Abstract We expand the assessment study of modeling capabilities in the prediction of foF2 and hmF2 for the ionospheric climatology (Tsagouri et al., 2018,https://doi.org/10.1029/2018sw002035) by using updated empirical (IRI and MIT Empirical model) and physics‐based models (CTIPe, WACCM‐X, and TIE‐GCM) as well as the additional observations in the southern hemisphere. Monthly medians of foF2 and hmF2 are considered to evaluate the model performance for the entire year of 2012. For quantitative evaluation, we employ several metrics including the correlation coefficient (R), coefficient of determination (R²), root‐mean square error (RMSE), mean error (ME), and mean relative error (MRE). The linear regression analysis shows that the empirical models perform much better than physics‐based models for foF2 but to a lesser degree for hmF2. There are negligible hemispheric differences in the predictions from empirical models. All the physics‐based models show relatively good correlations with the observations for foF2 in the northern hemisphere compared to the southern hemisphere, but the hemispheric differences are small for hmF2. The results of the study indicate that recent versions of empirical models tend to perform better than old versions of the models, but this is not always true for physics‐based models. 

Abstract During geomagnetically quiet and solar minimum conditions, spatial variations of the early morning thermosphere‐ionosphere (TI) system are expected to be mainly governed by wave dynamics. To study the postmidnight dynamical coupling, we investigated the early morning equatorial ionization anomaly (EIA) using Global‐scale Observations of the Limb and Disk (GOLD) measurements of OI‐135.6 nm nightglow emission and global navigation satellite system (GNSS)‐based total electron content (TEC) maps. The EIA structures in the OI‐135.6 nm emission over the American landmass resemble, spatially and temporally, those observed in the GNSS‐TEC maps. The early morning EIA (EM‐EIA) crests are well separated in latitude and mostly located over the middle of South America during October–November. In February–April the crests are less separated in latitude and predominantly located over the west coast sector of South America. Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (WACCMX) simulations with constant solar minimum and quiet‐geomagnetic conditions show that EM‐EIA can occur globally and shows properties similar to longitudinal Wave 4 pattern. Thus, we propose that EM‐EIA is driven by dynamical changes associated with the lower atmospheric waves. 

Abstract NRLMSIS® 2.0 is an empirical atmospheric model that extends from the ground to the exobase and describes the average observed behavior of temperature, eight species densities, and mass density via a parametric analytic formulation. The model inputs are location, day of year, time of day, solar activity, and geomagnetic activity. NRLMSIS 2.0 is a major, reformulated upgrade of the previous version, NRLMSISE‐00. The model now couples thermospheric species densities to the entire column, via an effective mass profile that transitions each species from the fully mixed region below ~70 km altitude to the diffusively separated region above ~200 km. Other changes include the extension of atomic oxygen down to 50 km and the use of geopotential height as the internal vertical coordinate. We assimilated extensive new lower and middle atmosphere temperature, O, and H data, along with global average thermospheric mass density derived from satellite orbits, and we validated the model against independent samples of these data. In the mesosphere and below, residual biases and standard deviations are considerably lower than NRLMSISE‐00. The new model is warmer in the upper troposphere and cooler in the stratosphere and mesosphere. In the thermosphere, N₂and O densities are lower in NRLMSIS 2.0; otherwise, the NRLMSISE‐00 thermosphere is largely retained. Future advances in thermospheric specification will likely require new in situ mass spectrometer measurements, new techniques for species density measurement between 100 and 200 km, and the reconciliation of systematic biases among thermospheric temperature and composition data sets, including biases attributable to long‐term changes.