Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

Accurate determination of thermospheric neutral density holds crucial importance for satellite drag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and three physicsâ based models of the ionosphereâ thermosphere are compared with the neutral densities along the Challenging Microâ Satellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias), (2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set of metrics for the neutral density.Plain Language SummaryThermospheric neutral density is the largest source of uncertainty in atmospheric drag calculations. Consequently, mission and maneuver planning, satellite lifetime predictions, collision avoidance, and orbit determination depend on the accurate estimation of the thermospheric neutral density. Thermospheric neutral density varies in different timescales. In short timescales, the largest variations occur due to the geomagnetic storms. Several empirical and physicsâ based models of the ionosphereâ thermosphere system are used for estimating the variations in the neutral density. However, the storm time responses from the models are clouded by the climatology (background variations), upon which the effect of geomagnetic storms is superimposed. In this work, we show that it is critical to use reference levels for the neutral density to extract the true performance of the models for the evaluation of the storm time performances. We demonstrate that mean absolute error, prediction efficiency, and normalized root mean square error should be considered together for the performance evaluations, since each of them provides different aspects of the error.Key PointsUsing the average and maximum values of neutral densities to determine the model performances can be misleadingRemoving the quiet time trend from the neutral density reveals the actual performance of the model in simulating the storm time variationsMean absolute error, prediction efficiency, and normalized root mean square error should be considered together for the evaluationsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/1/swe20816_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/2/swe20816-sup-0001-2018SW002033-SI.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148396/3/swe20816.pd

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

Analysis of the 20th November 2003 extreme geomagnetic storm using CTIPe model and GNSS data

The ionospheric instabilities produced by solar activity generate disturbances in ionospheric density (ionospheric storms) with important terrestrial consequences such as disrupting communications and positioning. During the 20th November 2003 extreme geomagnetic storm, significant perturbations were produced in the ionosphere - thermosphere system. In this work, we replicate how this system responded to the onset of this particular storm, using the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics physics-based model. CTIPe simulates the changes in the neutral winds, temperature, composition and electron densities. Although modelling the ionosphere under this conditions is a challenging task due to energy flow uncertainties, the model reproduces some of the storm features necessary to interpret the physical mechanisms behind the Total Electron Content (TEC) increase and the dramatic changes in composition during this event. Corresponding effects are observed in the TEC simulations from other physics-based models and from observations derived from Global Navigation Satellite System (GNSS) and ground-based measurements. The study illustrates the necessity of using both, measurements and models, to have a complete understanding of the processes that are most likely responsible for the observed effects

Capabilities of the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model to reproduce storm conditions

Since the ionosphere is impacting various communication and navigation applications relying on radio signal transmission, accurate monitoring and forecasting of the ionosphere is of great importance. For this purpose, physics based modelling of the coupled thermosphere ionosphere system is rather important, because good forecasts of ionospheric variability especially during storms need to consider the various physical driving processes in the thermosphere and ionosphere. This includes the energy transmission from the solar wind to the magnetosphere and ionosphere-thermosphere, as well as the electric field modifications, enhancement of ionosphere currents and thermosphere circulation and composition disturbances. One of the state of the art numerical models is the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model. The implementation of the model has been enhanced step by step over decades. Recent developments improved the capabilities of reproducing thermosphere ionosphere conditions during storms. These capabilities will be demonstrated based on comparison of CTIPe results during the St. Patrick’s Day storm on 17 March 2015 with ground and space based observations. We will make use of Swarm measurements, ionosondes and GNSS based TEC estimations. The validation results show a rather good reproduction of thermosphere conditions with CTIPe. Especially radiative cooling has improved significantly. The deviations between model and observations are larger for the ionosphere. Based on the validation results the limitations of the model are discussed and next steps for implementation are proposed

CTIPe model capabilities during the 2015 St. Patrick Day storm

The Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model is a global physics-based model that will be used to explore the ionosphere-thermosphere system response to the onset of 2015 St. Patrick day storm. This storm, which was one of the strongest geomagnetic storms of the solar cycle 24, was generated by a magnetic cloud followed by a coronal mass ejection (CME) impact. The ionospheric disturbances are identified to be caused by superposition of many effects, like prompt penetration electric fields, neutral winds, thermal expansion and composition changes. Over Europe, measurements like ionosonde observations and Total Electron Content (TEC) maps derived from Global Navigation Satellite System (GNSS) indicate four storm phases (compression, the start of the main phase, partial recovery and second substorm) during 17th March 2015. CTIPe reproduces well the positive ionospheric storm phases, the compression of the ionosphere to a thin shell and the surges excited in the Auroral region. Furthermore, it reproduces well the changes in the neutral mass density measured by the SWARM satellites. Finally, CTIPe exhibits a coherent storm response for the thermospheric winds, temperature, composition and electron densities during the storm. These model results will be used to support the interpretation of the storms driving mechanisms

Overview of the St. Patrick's day storm of 2015 using CTIPe model and GNSS data

The complexity of the Sun-Earth system increases during magnetically disturbed conditions, caused by intense solar activity. One of the strongest geomagnetic storms of the solar cycle 24 occurred following a coronal mass ejection (CME) impact; it was the St. Patrick day storm on the 17 March 2015. As a result of these extreme conditions, ionospheric instabilities were produced, generating disturbances in the ionospheric density (ionospheric storms) that could derive into disruptions of communication and positioning. To explore how the ionosphere-thermosphere system responded to this event, we use the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics global, three dimensional, non-linear physics-based model (CTIPe), that reproduces the changes in the thermospheric winds, composition and electron densities during the storm. To have a more complete understanding of the processes responsible of the observed effects, observational data derived from Global Navigation Satellite Systems (GNSS) and ground-based measurements are used to support the interpretation of the model outcome

CTIPe physics based model during the extreme geomagnetic storm on the 20th November 2003

Significant perturbations were produced in the thermosphere-ionosphere-magnetosphere system during the geomagnetic storm of the 20th November of 2003, one of the largest ever recorded. Under these extreme conditions, modelling the ionosphere will be a challenging task due to energy flow uncertainties. This work addresses the ionospheric perturbations over Europe, reproduced by the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physic based numerical code [1,2] and compared with observations of the Total Electron Content (TEC) derived from Global Navigation Satellite System (GNSS) measurements [3] and ionosonde measurements. Travelling Ionsopheric Disturbances (TIDs) are the signatures of atmospheric surges causing neutral composition changes, and are associated with strong TEC enhancement as the one observed during the 20th November 2003 storm. CTIPe reproduce the strong perturbations in Joule heating and neutral winds over Europe, located at exactly the location of the source region of TIDs. Even the signatures of atmospheric surges with similar characteristics of the observed TIDs are reproduced by CTIPe. Joule heating initiated meridional winds [4] and the associated storm-time neutral circulation seem to be the main driver of the ionospheric perturbations observed over Europe. However, comparisons with GNSS measurements show that the TEC enhancement (Fig.1) and TEC rate over Europe are underestimated by the CTIPe model. Nevertheless, the results provide valuable information on the physics of the processes that operate in the ionosphere/thermosphere during this extreme geomagnetic storm, and they may be improved by using better estimates of the thermosphere/ionosphere forcing during the storm

Studying the dynamics in the ionosphere-thermosphere system during 20th November 2003 storm with CTIPe

Geomagnetic storms often go along with ionospheric disturbances which may threaten radio systems used for communication and navigation. During the super storm on 20 November 2003 for example, plenty of strong and unusual perturbations were reported. This paper analyses the dynamics of the high-latitude ionosphere over Europe during this storm. Here, Total Electron Content (TEC) measurements derived from ground-based Global Navigation Satellite System (GNSS) observations are used to monitor large scale traveling ionospheric disturbances (LSTIDs). The source region of these LSTIDs is characterized by enhanced spatial gradients, TEC depletion, strong electron density uplifting, the proximity of the eastward auroral electrojet and strong Aurora E-layers. In the course of the storm, the TEC observations show a southward shift of the source region of the TIDs. These meridional dislocation effects are obviously related to a strong compression of the plasmasphere. The Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) clearly reproduces intensive Joule heating in the source region of the LSTIDs. The sudden heating of the thermosphere leads to strong vertical winds in the heating region and the development of so-called storm wind cells. The sudden changes in wind and pressure generate thermospheric wind surges, which are observed as LSTID signatures in the TEC. The surges are also reproduced by CTIPe in the vertical winds. As potential source mechanisms for the Joule heating the dissipation of the eastward auroral electrojet and/or particle precipitation are considered. The presented results demonstrate the complex interaction processes in the thermosphere-ionosphere-magnetosphere system during the extreme storm on 20 November 2003

Ionospheric response to solar EUV variations: Preliminary results

We investigate the ionospheric response to solar Extreme Ultraviolet (EUV) variations using different proxies, based on solar EUV spectra observed from the Solar Extreme Ultraviolet Experiment (SEE) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite, the F10.7 index (solar irradiance at 10.7cm), and the Bremen composite Mg-II index during January 2003 to December 2016. The daily mean solar proxies are compared with global mean Total Electron Content (GTEC) values calculated from global IGS TEC maps. The preliminary analysis shows a significant correlation between GTEC and both the integrated flux from SEE and the Mg II index, while F10.7 correlates less strongly with GTEC. The correlations of EUV proxies and GTEC at different time periods are presented. An ionospheric delay in GTEC is observed at the 27 days solar rotation period with the time scale of about  ∼ 1–2 days. An experiment with the physics based global 3-D Coupled Thermosphere/Ionosphere Plasmasphere electrodynamics (CTIPe) numerical model was performed to reproduce the ionospheric delay. Model simulations were performed for different values of the F10.7 index while keeping all the other model inputs constant. Preliminary results qualitatively reproduce the observed  ∼ 1–2 days delay in GTEC, which is might be due to vertical transport processes