We define a new thermospheric concept, the reference heights of O/N_{2}, referring to a series of thermospheric heights corresponding to the fixed ratios of O to N_{2} number density. Here, based on Global Ultraviolet Imager (GUVI) limb measurement, we compare O/N_{2} column density ratio (∑O/N_{2}) and the reference heights of O/N_{2}. We choose the transition height of O and N_{2} (transition height hereafter), a special reference height at which O number density is equal to N_{2} number density, to verify the connection with ∑O/N_{2} during geomagnetically quiet periods. It is found that transition height and ∑O/N_{2} have noticeable negative correlation with correlation coefficient of ‐0.887. An empirical model of transition height (O/N_{2} model hereafter) is established based on nonlinear least‐squares‐fitting method. The considerable correlation (greater than 0.96), insignificant errors (less than 4%) and the great influencing weight of ∑O/N_{2} to reference heights indicate the validity of O/N_{2} model and the existence of quantitative relation between ∑O/N_{2} and transition height. Besides, it is verified that the similar quantitative relation also exists between ∑O/N_{2} and reference heights of other O/N_{2} values. Namely, using the O/N_{2} model coefficients, we can roughly get the whole altitude profiles of O/N_{2} within 6% precision for any given ∑O/N_{2}.

In this work, we evaluated the quasi‐realistic ionosphere forecasting capability by an ensemble Kalman filter (EnKF) ionosphere and thermosphere data assimilation algorithm. The National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model is used as the background model in the system. The slant total electron contents (TECs) from global International Global Navigation Satellite Systems Service ground‐based receivers and from the Constellation Observing System for Meteorology, Ionosphere and Climate are assimilated into the system, and the ionosphere is then predicted in advance during the quiet interval of 23 to 27 March 2010. The predicted ionosphere vertical TEC (VTEC) and the critical frequency foF_{2} are validated by the Massachusetts Institute of Technology VTEC and global ionosondes network, respectively. We found that the ionosphere forecast quality could be enhanced by optimizing the thermospheric neutral components via the EnKF method. The ionosphere electron density forecast accuracy can be improved by at least 10% for 24 hr. Furthermore, the Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics/Global Ultraviolet Imager (TIMED/GUVI) [O/N_{2}] observations are used to validate the predicted thermosphere [O/N_{2}]. The validation shows that the [O/N_{2}] optimized by EnKF has better agreement with the TIMED/GUVI observation. This study further demonstrates the validity of EnKF in enhancing the ionospheric forecast capability in addition to our previous observing system simulation experiments by He et al. (2019, https://doi.org/10.1029/2019JA026554).

The Global Ultraviolet Imager (GUVI) aboard the Thermosphere‐Ionosphere‐Mesosphere Energetics and Dynamics (TIMED) satellite senses far ultraviolet airglow emissions in the thermosphere. The retrieved altitude profiles of thermospheric neutral density from GUVI daytime limb scans are significant for ionosphere‐thermosphere study. Here, we use the profiles of the main neutral density to derive the total mass density during the period 2002–2007 under geomagnetic quiet conditions (*ap* < =12). We attempt to compare the obtained total mass density with the Challenging Minisatellite Payload (CHAMP) observations, making use of an empirical model (GUVI model hereafter). This GUVI model is aimed to solve the difficulty of the direct comparison of GUVI and CHAMP observations due to their different local times at a given location in a given day. The GUVI model is in good agreement with CHAMP observations with the small standard deviations of their ratios (less than 10%) except at low solar flux levels. The correlation coefficients are greater than 0.9, and the relative standard errors are less than 20%. Comparison between the GUVI model and CHAMP observations during solar minimum shows a large bias (~30%). The large bias at low solar flux levels might be due to the limitation of *F*_{10.7} as an extreme ultraviolet radiation flux proxy and the fitting method. Our results demonstrate the validity and accuracy of our model based on GUVI data against the density data from the CHAMP satellite.

We propose a new method to derive the nightside thermsopheric density by extending GUVI dayside limb observations using empirical orthogonal function (EOF) analysis. First, we acquire the GUVI dayside total mass density during 2002‐2005 to construct a preliminary empirical model (EM). Simultaneously, we decompose the background thermospheric density from US Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended (NRLMSISE‐00) model into different empirical orthogonal functions (EOFs). The decomposed EOFs are then used to fit the continuous density from EM, to develop a new nightside extended model (NEM). The preliminary EM and developed NEM are further evaluated with CHAMP satellite observations. Higher correlation coefficients and smaller relative standard errors (RSE) between CHAMP observations and the NEM results are obtained than those between CHAMP observations and the EM results, and the NEM results are in good agreement with the CHAMP observations in time series during both daytime and nighttime, which all prove the NEM method is effective to the reproduction and extension of GUVI original dayside observations. Furthermore, the NEM reveals two typical seasonal variation features, the semiannual variation and equinoctial asymmetry of thermospheric density. The model provides an effective tool to derive the nightside thermospheric density and explore the thermospheric intrinsic structure, and needs the further development to achieve more widespread application of the thermosphere.

%B Space Weather %8 10/2019 %G eng %U https://onlinelibrary.wiley.com/doi/abs/10.1029/2019SW002304 %! Space Weather %R 10.1029/2019SW002304 %0 Journal Article %J Journal of Geophysical Research: Space Physics %D 2013 %T East-west differences inThe global configuration of the geomagnetic field shows that the maximum east-west difference in geomagnetic declination of northern middle latitude lies in the US region (~32°), which produces the significant ionospheric east-west coast difference in terms of total electron content first revealed by Zhang et al. (2011). For verification, it is valuable to investigate this feature over the Far East area, which also shows significant geomagnetic declination east-west gradient but smaller (~15°) than that of the US. The current study provides evidence of the longitudinal change supporting the thermospheric zonal wind mechanism by examining the climatology of peak electron density (NmF2), electron density (Ne) of different altitudes in the Far East regions with a longitude separation of up to 40–60° based on ground ionosonde and space-based measurements. Although the east-west difference (*R*_{ew}) over the Far East area displays a clear diurnal variation similar to the US feature, that is negative *R*_{ew} (West Ne > East Ne) in the noon and positive at evening-night, the observational results reveal more differences including: (1) The noontime negative *R*_{ew} is most pronounced in April–June while in the US during February–March. Thus, for the late spring and summer period negative *R*_{ew} over the Far East region is more significant than that of the US. (2) The positive *R*_{ew} at night is much less evident than in the US, especially without winter enhancement. (3) The magnitude of negative *R*_{ew} tends to enhance toward solar maximum while in the US showing anticorrelation with the solar activity. The altitude distribution of pronounced negative difference (300–400 km) moves upward as the solar flux increases and hence produces the different solar activity dependence at different altitude. The result in the paper is not simply a comparison corresponding to the US results but raises some new features that are worth further studying and improve our current understanding of ionospheric longitude difference at midlatitude.