Coupled Thermosphere Ionosphere Plasmasphere Research Articles

Ionospheric Response to Solar EUV Radiation Variations Using GOLD Observations and the CTIPe Model

AbstractTo understand the global response of thermospheric‐ionospheric (TI) parameters to variations in solar irradiance measurements from the Global‐Scale Observations of the Limb and Disk (GOLD) ultraviolet imaging spectrograph, solar radio flux F10.7, predictions from the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model, and International Global Navigation Satellite System Service total electron content maps (TEC) have been used. Various parameters such as GOLD O/N2, O2, and the nighttime peak electron density (Nmax) have been compared with the CTIPe model simulations. The GOLD observed Nmax shows a number of significant features including a winter anomaly and an equatorial ionization anomaly. The comparison with solar proxies showed that the GOLD QEUV correlates very well with the EUV observations compared to the F10.7 index. The study also examined the relationship between the solar proxies and Nmax on different time scales and found that Nmax responded significantly to QEUV at both medium‐ and long‐term timescales. Furthermore, a low correlation between Nmax in the equatorial region and solar proxies was found. A delayed ionospheric TEC response against solar flux variations within the 27‐day solar rotation was investigated. This ionospheric delay of TEC with respect to solar flux was observed to be less than 1 day, which was reproduced in model simulations. The current study has shown that the GOLD observations can be used to investigate the delayed ionospheric response and to gain a better understanding of the influence of solar activity on the TI system.

Validation of Ionospheric Specifications During Geomagnetic Storms: TEC and foF2 During the 2013 March Storm Event‐II

AbstractAssessing space weather modeling capability is a key element in improving existing models and developing new ones. In order to track improvement of the models and investigate impacts of forcing, from the lower atmosphere below and from the magnetosphere above, on the performance of ionosphere‐thermosphere models, we expand our previous assessment for 2013 March storm event (Shim et al., 2018, https://doi.org/10.1029/2018SW002034). In this study, we evaluate new simulations from upgraded models (the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model version 4.1 and the Global Ionosphere Thermosphere Model (GITM) version 21.11) and from the NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM‐X) version 2.2 including eight simulations in the previous study. A simulation from the NCAR Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model version 2 (TIE‐GCM 2.0) is also included for comparison with WACCM‐X. TEC and foF2 changes from quiet‐time background are considered to evaluate the model performance on the storm impacts. For evaluation, we employ four skill scores: Correlation coefficient (CC), root‐mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (Yield), and timing error (TE). It is found that the models tend to underestimate the storm‐time enhancements of foF2 (F2‐layer critical frequency) and TEC (Total Electron Content) and to predict foF2 and/or TEC better in North America but worse in the Southern Hemisphere. The ensemble simulation for TEC is comparable to results from a data assimilation model (Utah State University‐Global Assimilation of Ionospheric Measurements (USU‐GAIM)) with differences in skill score less than 3% and 6% for CC and RMSE, respectively.

Improving estimates of the ionosphere during geomagnetic storm conditions through assimilation of thermospheric mass density

Dynamical changes in the ionosphere and thermosphere during geomagnetic storm times can have a significant impact on our communication and navigation applications, as well as satellite orbit determination and prediction activities. Because of the complex electrodynamics coupling processes during storms, which cannot be fully described with the sparse set of thermosphere–ionosphere (TI) observations, it is crucial to accurately model the state of the TI system. The approximation closest to the true state can be obtained by assimilating relevant measurements into physics-based models. Thermospheric mass density (TMD) derived from satellite measurements is ideal to improve the thermosphere through data assimilation. Given the coupled nature of the TI system, the changes in the thermosphere will also influence the ionosphere state. This study presents a quantification of the changes and improvement of the model state produced by assimilating TMD not only for the thermosphere density but also for the ionosphere electron density under storm conditions. TMD estimates derived from a single Swarm satellite and the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physics-based model are used for the data assimilation. The results are presented for a case study during the St. Patricks Day storm 2015. It is shown that the TMD data assimilation generates an improvement of the model’s thermosphere density of up to 40% (measured along the orbit of the non-assimilated Swarm satellites). The model’s electron density during the course of the storm has been improved by approximately 8 and 22% relative to Swarm-A and GRACE, respectively. The comparison of the model’s global electron density against a high-quality 3D electron density model, generated through assimilation of total electron content, shows that TMD assimilation modifies the model’s ionosphere state positively and negatively during storm time. The major improvement areas are the mid-low latitudes during the storm’s recovery phase.Graphical

Delayed ionospheric response to solar extreme ultraviolet radiation variations: A modeling approach

The behavior of the ionosphere is strongly dependent on solar activity conditions. Attempts have been made to understand the delayed response of the ionosphere at low and high solar activity in a systematic way. The total electron content provided by International GNSS Service (IGS) and Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) was used to study the delay during 2008 and 2013 at the location 50 ° N, 18 ° E. The comparative study shows that the model successfully reproduces the ionospheric behavior during low and high solar activity. In addition, the CTIPe has been used for sensitivity studies with different model components. The analysis suggests that the model reproduction of the ionospheric time delay is significantly affected by various processes such as diffusion, photodissociation, solar and geomagnetic activities. To this end, several model runs were performed during low and high solar activity conditions. Furthermore, we have systematically studied the delayed response of the ionosphere during low, medium, and high solar activity and it was confirmed that the ionospheric delay increases with increasing solar activity.

Storm time neutral density assimilation in the thermosphere ionosphere with TIDA

To improve Thermosphere–Ionosphere modeling during disturbed conditions, data assimilation schemes that can account for the large and fast-moving gradients moving through the modeled domain are necessary. We argue that this requires a physics based background model with a non-stationary covariance. An added benefit of using physics-based models would be improved forecasting capability over largely persistence-based forecasts of empirical models. As a reference implementation, we have developed an ensemble Kalman Filter (enKF) software called Thermosphere Ionosphere Data Assimilation (TIDA) using the physics-based Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model as the background. In this paper, we present detailed results from experiments during the 2003 Halloween Storm, 27–31 October 2003, under very disturbed (Kp = 9) conditions while assimilating GRACE-A and B, and CHAMP neutral density measurements. TIDA simulates this disturbed period without using the L1 solar wind measurements, which were contaminated by solar energetic protons, by estimating the model drivers from the density measurements. We also briefly present statistical results for two additional storms: September 27 – October 2, 2002, and July 26 – 30, 2004, to show that the improvement in assimilated neutral density specification is not an artifact of the corrupted forcing observations during the 2003 Halloween Storm. By showing statistical results from assimilating one satellite at a time, we show that TIDA produces a coherent global specification for neutral density throughout the storm – a critical capability in calculating satellite drag and debris collision avoidance for space traffic management.

Role of eddy diffusion in the delayed ionospheric response to solar flux changes

Abstract. Simulations of the ionospheric response to solar flux changes driven by the 27 d solar rotation have been performed using the global 3-D Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physics-based numerical model. Using the F10.7 index as a proxy for solar extreme ultraviolet (EUV) variations in the model, the ionospheric delay at the solar rotation period is well reproduced and amounts to about 1 d, which is consistent with satellite and in situ measurements. From mechanistic CTIPe studies with reduced and increased eddy diffusion, we conclude that the eddy diffusion is an important factor that influences the delay of the ionospheric total electron content (TEC). We observed that the peak response time of the atomic oxygen to molecular nitrogen ratio to the solar EUV flux changes quickly during the increased eddy diffusion compared with weaker eddy diffusion. These results suggest that an increase in the eddy diffusion leads to faster transport processes and an increased loss rate, resulting in a decrease in the ionospheric time delay. Furthermore, we found that an increase in solar activity leads to an enhanced ionospheric delay. At low latitudes, the influence of solar activity is stronger because EUV radiation drives ionization processes that lead to compositional changes. Therefore, the combined effect of eddy diffusion and solar activity leads to a longer delay in the low-latitude and midlatitude region.

Ionospheric response to solar extreme ultraviolet radiation variations: comparison based on CTIPe model simulations and satellite measurements

Abstract. The ionospheric total electron content (TEC) provided by the International GNSS Service (IGS) and the TEC simulated by the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model have been used to investigate the delayed ionospheric response against solar flux and its trend during the years 2011 to 2013. The analysis of the distinct low-latitude and midlatitude TEC response over 15∘ E shows a better correlation of observed TEC and the solar radio flux index F10.7 in the Southern Hemisphere compared to the Northern Hemisphere. Thus, a significant hemispheric asymmetry is observed. The ionospheric delay estimated using model-simulated TEC is in good agreement with the delay estimated for observed TEC against the flux measured by the Solar Dynamics Observatory (SDO) extreme ultraviolet (EUV) Variability Experiment (EVE). The average delay for the observed (modeled) TEC is 17(16) h. The average delay calculated for observed and modeled TEC is 1 and 2 h longer in the Southern Hemisphere compared to the Northern Hemisphere. Furthermore, the observed TEC is compared with the modeled TEC simulated using the SOLAR2000 and EUVAC flux models within CTIPe over northern and southern hemispheric grid points. The analysis suggests that TEC simulated using the SOLAR2000 flux model overestimates the observed TEC, which is not the case when using the EUVAC flux model.

Evaluation of Total Electron Content Prediction Using Three Ionosphere‐Thermosphere Models

AbstractPrediction of ionospheric state is a critical space weather problem. We expand on our previous research of medium‐range ionospheric forecasts and present new results on evaluating prediction capabilities of three physics‐based ionosphere‐thermosphere models (Thermosphere Ionosphere Electrodynamics General Circulation Model, TIE‐GCM; Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics Model, CTIPe; and Global Ionosphere Thermosphere Model, GITM). The focus of our study is understanding how current modeling approaches may predict the global ionosphere for geomagnetic storms (as studied through 35 storms during 2000–2016). Prediction approach uses physics‐based modeling without any manual model adjustment, quality control, or selection of the results. Our goal is to understand to what extent current physics‐based modeling can be used in total electron content (TEC) prediction and explore uncertainties of these prediction efforts with multiday lead times. The ionosphere‐thermosphere model runs are driven by actual interplanetary conditions, whether those data come from real‐time measurements or predicted values themselves. These model runs were performed by the Community Coordinated Modeling Center (CCMC). Jet Propulsion Laboratory (JPL)‐produced global ionospheric maps (GIMs) were used to validate model TEC estimates. We utilize the True Skill Statistic (TSS) metric for the TEC prediction evaluation, noting that this is but one metric to assess predictive skill and that complete evaluations require combinations of such metrics. The meanings of contingency table elements for the prediction performance are analyzed in the context of ionosphere modeling. Prediction success is between about 0.2 and 0.5 for weak ionospheric disturbances and decreases for strong disturbances. We evaluate the prediction of TEC decreases and increases. Our results indicate that physics‐based modeling during storms shows promise in TEC prediction with multiday lead time.

On the difference between real-time and research simulations with CTIPe

Understanding the thermosphere and ionosphere conditions is crucial for spacecraft operations and many applications using radio signal transmission (e.g. in communication and navigation). In this sense, physics based modelling plays an important role, since it can adequately reproduce the complex coupling mechanisms in the magnetosphere-ionosphere-thermosphere (MIT) system. The accuracy of the physics based model results does not only depend on the appropriate implementation of the physical processes, but also on the quality of the input data (forcing). In this study, we analyze the impact of input data uncertainties on the model results. We use the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics model (CTIPe), which requires satellite based solar wind, interplanetary field and hemispheric power data from ACE and TIROS/NOAA missions. To identify the impact of the forcing uncertainties, two model runs are compared against each other. The first run uses the input data that were available in real-time (operational) and the second run uses the best estimate obtained in post-processing (research or historical run). The analysis is performed in a case study on the 20th November 2003 extreme geomagnetic storm, that caused significant perturbations in the MIT system. This paper validates the thermosphere and ionosphere response to this storm over Europe comparing both CTIPe model runs with measurements of Total Electron Content (TEC) and thermosphere neutral density. In general, CTIPe results show a good agreement with measurements. However, the deviations between the model and observations are larger in the ionosphere than in the thermosphere. The comparison of the two model runs reveals that the deviations between model results and measurements are larger for the operational run than the research run. It is evident for the storm analyzed here, that data gaps in the input data are impacting considerably the model performance. The consistency between simulation and measurements allows the interpretation of the physical mechanisms behind the ionosphere perturbations and the changes in neutral composition during this event. Joule heating in the Auroral region, generating meridional winds and large scale surges, is suggested to be the main driver of the positive ionospheric storm over central Europe. In the polar cap and Auroral region, convection processes dominate the thermosphere-ionosphere conditions. This study does not only illustrate the importance of working with a good estimate of the model forcing, but also indicates the necessity of using measurements and models, to get a better understanding of the most likely responsible processes for the observed storm effects.

Assessment of Current Capabilities in Modeling the Ionospheric Climatology for Space Weather Applications: foF2 and hmF2

AbstractThis paper presents preliminary results of a metrics‐based assessment of current modeling capabilities in predicting the ionospheric climatology for two ionospheric characteristics, the foF2 and hmF2. This work is part of the activities of the Ionosphere Working Group of the International Forum for Space Weather Modeling Capabilities Assessment that is facilitated by the Community Coordinated Modeling Center. The results are based on the comparison between modeled and observed monthly medians of the foF2 and hmF2. Modeling formulations considered here include two empirical models (the International Reference Ionosphere [IRI] and Massachusetts Institute of Technology [MIT] Empirical model), as well as two physics‐based, coupled ionosphere‐thermosphere models (the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics [CTIPe] and Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model [TIE‐GCM]). The comparisons were carried out in year 2012 over seven ionospheric locations distributed worldwide in the Northern Hemisphere. Based on our findings, although significant errors are occasionally obtained from all modeling approaches, empirical models tend to provide systematically better correlation with the observed medians and follow the observed distributions more successfully, offering smaller prediction errors than the physics‐based ones. In case of foF2, the averaged prediction accuracy in terms of root‐mean‐square error (RMSE) ranges around 1.5 MHz for physics‐based models and 0.5 MHz for empirical models. In case of hmF2, it ranges around 30 and 20 km, respectively. The prediction accuracy presents strong seasonal and local time dependence, which differs for different models and ionospheric characteristics (i.e., foF2 or hmF2): it is strong for physics‐based models, weaker for IRI, and very weak for MIT empirical model. This latter outcome may provide suggestive input for future improvements.

Occurrence of the dayside three‐peak density structure in the F2 and the topside ionosphere

AbstractIn this work, we discuss the occurrence of the dayside three‐peak electron density structure in the ionosphere. We first use a set of ground‐based and satellite‐borne instruments to demonstrate the development of a large‐amplitude electron density perturbation at the recovery phase of a moderate storm of 11 October 2008. The perturbation developed in the F2 and low topside ionospheric regions over the American sector; it was concentrated on the north from the equatorial ionization anomaly (EIA) but was clearly separated from it. At the F2 region height, the amplitude of the observed perturbation was comparable or even exceeded that of the EIA. Further analysis of the observational data together with the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics model simulation results showed that a particular local combination of the thermospheric wind surges provided favorable conditions for the generation of the three‐peak EIA structure. We further proceed with a statistical study of occurrence of the three‐peak density structure in the ionosphere in general. Based on the analysis of 7 years of the in situ data from CHAMP satellite, we found that such three‐peak density structure occurs sufficiently often during geomagnetically quiet time. The third ionization peak develops in the afternoon hours in the summer hemisphere at solstice periods. Based on analysis of several quiet time events, we conclude that during geomagnetically quiet time, the prevailing summer‐to‐winter thermospheric circulation acts in similar manner as the storm‐time enhanced thermospheric winds, playing the decisive role in generation of the third ionization peak in the daytime ionosphere.

Lidar and CTIPe model studies of the fast amplitude growth with altitude of the diurnal temperature “tides” in the Antarctic winter lower thermosphere and dependence on geomagnetic activity

AbstractFour years of lidar observations at McMurdo reveal that the fast amplitude growth with altitude of diurnal temperature tides from 100 to 110 km during Antarctic winters, exceeding that of the freely propagating tides from the lower atmosphere, increases in strength with the Kp magnetic activity index. Simulations with the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model reproduce the lidar observations and exhibit concentric ring structures of diurnal amplitudes encircling the south geomagnetic pole and overlapping the auroral zone. These findings point to a magnetospheric source origin. Mechanistic studies using CTIPe show that the adiabatic cooling/heating associated with Hall ion drag is the dominant source of this feature, while Joule heating is a minor contributor due to the counteraction by Joule‐heating‐induced adiabatic cooling. The sum of total dynamical effects and Joule heating explains ~80% of the diurnal amplitudes. Auroral particle heating, lower atmosphere tides, and direct solar heating have minor contributions.

On the validation effort of the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics model

[1] The Coupled Thermosphere Ionosphere Plasmasphere electrodynamics model (CTIPe) has proven to be a valuable ionospheric research tool. Improving our knowledge of systematic and seasonal model biases is necessary if further improvements are to be made. This paper presents the next step in our verification and validation effort and in developing a standardized analysis methodology. A semi-automated software part of the near-real-time-run of CTIPe is described and results derived from its usage are presented. Model limitations and biases are detailed for the electron density profile peak (NmF2) and its corresponding height (hmF2). Model performance for hmF2 is constant throughout the whole year, with an average 10% deviation from observed values. There is a strong seasonal variation for NmF2, with greater deviations from the observed trends during summer. This effect seems to have latitude dependence, although the gaps in the available data do not allow for an exact determination of its nature.

A real‐time run of the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model

The availability of unprecedented amounts of real‐time data from Global Navigation Satellite Systems and ionosondes coupled with new and more stringent requirements for specification and forecast of the neutral and electron densities in the thermosphere‐ionosphere system are driving a new wave of development in data assimilation schemes for the thermosphere and ionosphere. However, such schemes require accurate knowledge of any biases affecting the state‐propagating models, and characterizing such biases involves significant effort. A first step in the estimation of the model biases, a steady state neutral temperature comparison with the empirical Mass Spectrometer Incoherent Scatter model, was published in Space Weather in 2008. Here we present another step in the validation of the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) general circulation model in preparation for its future inclusion in a data assimilation scheme. We describe an implementation of the model at the Space Weather Prediction Center (SWPC) and present real‐time comparisons between CTIPe and GPS total electron content and F2 layer ionosonde measurements. The CTIPe results are generated automatically about 20 min ahead of real time. The model inputs are based on NASA's Advanced Composition Explorer and F10.7 data available in the SWPC database. The results and the comparison with measurements for the current 2‐week period are available at http://helios.swpc.noaa.gov/ctipe/. The results are quite encouraging and offer hope that physics‐based models can compete with empirical models during quiet times and have tremendous potential to provide more reliable forecasts during periods of geomagnetic disturbance.

Large‐scale traveling ionospheric disturbances impacting equatorial ionization anomaly development in the local morning hours of the Halloween Superstorms on 29–30 October 2003

This study investigates the development of EIA‐like features during the Halloween Superstorms. These features are similar to a well‐developed equatorial ionospheric anomaly (EIA) and therefore suggest superfountain effects. We tracked EIA‐like features in the early‐morning sector of 29–30 October 2003 and at around midday on 30 October. Their plasma environment was studied with field‐aligned plasma density, vertical plasma drift, electron temperature, and vertical plasma flow profiles. Coupled thermosphere‐ionosphere plasmasphere (CTIP) simulations reproduced storm‐generated equatorward wind surges. When these EIA‐like features appeared early morning on 29–30 October, there was no forward fountain circulation; only large‐scale traveling ionospheric disturbances (TIDs) and strong equatorward winds were present. These provide observational evidence that large‐scale TIDs created large plasma depletions over the dip equator and with the aid of equatorward winds some large enhancements at ∼±30°N (geomagnetic), resulting in the development of early‐morning EIA‐like features. We identified TID signatures in the equatorial and midlatitude ionosonde and magnetometer data, and studied EIA‐like features at around midday on 30 October utilizing non‐field‐aligned TOPEX TEC (2000 UT) and published CHAMP TEC (2030 UT; 2200 UT) line plots. According to our analysis, the EIA‐like features seen in the TEC data were created by large‐scale TIDs at 2000 and 2030 UT and by the combined effects of large‐scale TIDs and forward superfountain at 2200 UT. CTIP simulations demonstrate the crucial role of the neutral winds' mechanical or direct effects in the development of high plasma densities at low midlatitudes.

Thermospheric winds and temperatures above Mawson, Antarctica, observed with an all-sky imaging, Fabry-Perot spectrometer

Abstract. A new all-sky imaging Fabry-Perot spectrometer has been installed at Mawson station (67°36' S, 62°52' E), Antarctica. This instrument is capable of recording independent spectra from many tens of locations across the sky simultaneously. Useful operation began in March 2007, with spectra recorded on a total of 186 nights. Initial analysis has focused on the large-scale daily and average behavior of winds and temperatures derived from observations of the 630.0 nm airglow line of atomic oxygen, originating from a broad layer centered around 240 km altitude, in the ionospheric F-region. The 1993 Horizontal Wind Model (HWM93), NRLMSISE-00 atmospheric model, and the Coupled Thermosphere/Ionosphere Plasmasphere (CTIP) model were used for comparison. During the geomagnetically quiet period studied, observed winds and temperatures were generally well modelled, although temperatures were consistently higher than NRLMSISE-00 predicted, by up to 100 K. CTIP temperatures better matched our data, particularly later in the night, but predicted zonal winds which were offset from those observed by 70–180 ms−1 westward. During periods of increased activity both winds and temperatures showed much greater variability over time-scales of less than an hour. For the active night presented here, a period of 45 min saw wind speeds decrease by around 180 ms−1, and temperatures increase by approximately 100 K. Active-period winds were poorly modelled by HWM93 and CTIP, although observed median temperatures were in better agreement with NRLMSISE-00 during such periods. Average behavior was found to be generally consistent with previous studies of thermospheric winds above Mawson. The collected data set was representative of quiet geomagnetic and solar conditions. Geographic eastward winds in the afternoon/evening generally continued until around local midnight, when winds turned equatorward. Geographic meridional and zonal winds in the afternoon were approximately 50 ms−1 weaker than expected from HWM93, as was the transition to equatorward flow around midnight. There was also a negligible geographic zonal component to the post-midnight wind where HWM93 predicted strong westward flow. Average temperatures between 19:00 and 04:00 local solar time were around 60 K higher than predicted by NRLMSISE-00.

The CTIP Model with SuperDARN Electric Potential Patterns as Input: First Comparison of Modelled Ion Densities with Radio Tomography Observations

In a recent development of the Coupled Thermosphere Ionosphere Plasmasphere (CTIP) model, electric potential patterns from the SuperDARN radar network are used as the input to drive the high-latitude ionospheric convection. Spatial images of the ionised atmosphere under conditions of IMF Bz negative given by the Aberystwyth University tomography experiments in Scandinavia and the UK are compared with model simulations for assessment of the model development. Results are presented showing broad agreement between the observations and the model.

Validation of the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics model: CTIPE‐Mass Spectrometer Incoherent Scatter temperature comparison

New requirements for specification and forecast of the space environment and the availability of unprecedented amounts of real‐time data are now driving the development of data assimilation schemes for the thermosphere and ionosphere. Such schemes require accurate knowledge of any biases affecting the models. Finding the biases is not trivial and requires significant effort. Here we present a first step in the validation of a coupled thermosphere ionosphere general circulation model in preparation for its inclusion in a data assimilation scheme. We present a comparison between the Mass Spectrometer Incoherent Scatter (MSIS) radar empirical model neutral temperatures and the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPE) neutral temperature predictions for three solar cycle conditions (F10.7 = 70, 125, and 200), three geomagnetic activity conditions (Kp = 1, 3, and 7), and three seasons (equinox, summer, and winter). The CTIPE model was run for each case with constant inputs until a diurnally reproducible (“steady state”) global temperature pattern was obtained. MSIS predictions were generated for “perpetually constant” equivalent conditions. The temperature comparisons are performed on a 300 km altitude shell. We present global temperature averages, area‐weighted root mean square differences, and zonally averaged temperature comparisons. CTIPE temperatures at 300 km altitude are lower than MSIS if Joule heating calculations do not include small‐scale E field variability. This is the first global assessment of a general circulation model for the thermosphere over such a wide range of geomagnetic and solar conditions.

The role of the tongue‐of‐ionization in the formation of the poleward wall of the main trough in the European post‐midnight sector

A series of radio tomography reconstructions from the University of Wales Aberystwyth receiver chains in Scandinavia and the UK, imaging the midnight‐dawn sector on 13 December 2001, reveal a persistent large‐scale electron density enhancement, which forms the poleward wall of the main ionization trough. Measurements by the European Incoherent Scatter radar (EISCAT) rule out in situ soft‐particle precipitation as the main source of the higher densities. SuperDARN plasma drift observations and electric potential patterns place the feature in the dawn cell of the high‐latitude convection, leading to the conclusion that the higher density is likely to have originated as photoionization and was convected over the polar cap to the nightside and around toward dawn in a tongue‐of‐ionization (TOI). Suitable runs of the Coupled Thermosphere‐Ionosphere‐Plasmasphere (CTIP) model support this interpretation and also reveal that the formation of the TOI is heavily UT dependent, which would lead to it being most prominent at nighttime in the European sector.

Low‐latitude total electron content enhancement at low geomagnetic activity observed over Japan

Numerous total electron content (TEC) values derived from GPS signals are averaged within 1.5° × 1.5° cells in a 1‐hour time frame, and the relative deviations of these average values from corresponding monthly medians are used to produce latitude‐time plots over Japan. The paper analyzes the appearance and development of enhancements of TEC of equatorial origin (ETEs), occurring outside initial and main phases of geomagnetic storms. ETE structures appear mainly as single‐crest structures in the evening hours local time, with TEC peak around 1900 LT. TEC usually decreases with latitude, and the structures disappear below 40°N. In some cases the TEC peak is found above the plot boundary of 24°N, as depletions toward the equator are also observed. The observed enhanced structures are linked to the well‐known evening prereversal enhancement of ion drift in the equatorial F region. Double‐crest ETEs are also observed, with the second peak occurring in early morning hours. Most of the ETE events appear in periods of low geomagnetic activity, 1–3 days after the main phase of the storms. In some cases the time of rising of ETE structures coincides with the increase of interplanetary electric field (IEF), a fact showing the importance of directly penetrating electric field in formation of ETEs. Often, ETEs appear repeatedly in 2 or 3 consecutive days. It is supposed that planetary atmospheric waves are responsible for this phenomenon. Most of the observed features of ETEs can be explained by the published results of simulations of the coupled thermosphere‐ionosphere‐plasmasphere (CTIP) model and the thermosphere/ionosphere/electrodynamic general circulation model (TIEGCM). It is suggested that ETE structures are produced mainly by a disturbance winds dynamo electric field, built up after the main phase of the storms. Some ETE events, appearing at the end of a prolonged period of low geomagnetic activity, can be linked to directly penetrating IEF in equatorial ionosphere. The intensity of these electric fields is much smaller than is needed to explain the observations.