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The thermosphere-ionosphere (T-I) system is significantly controlled by solar EUV/UV variability. Apart from solar influences, a significant part of T-I variability is known to be driven by lower atmospheric forcings such as tides, gravity waves, and planetary waves originating in the lower atmosphere. To improve our understanding of this highly complex region of the Earth's atmosphere, a simulation study using the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model was conducted to systematically investigate the influence of lower atmospheric forcing. Several simulations were performed to investigate the impact of nudging using different lower atmosphere data sources such as Whole Atmospheric Model (WAM), Whole Atmosphere Community Climate Model-Extended (WACCM-X), and Navy Global Environmental Model a high-altitude version (NAVGEM-HA). The comparative study based on different nudging sources shows significant differences in the ionospheric parameters such as total electron content, electron density, and neutrals. In addition, we studied the delayed electron density in relation to the solar EUV variations at the time scale of the 27-day solar rotation period, taking into account the influence of the lower atmospheric forcings. The results show that the ionospheric delay is significantly modulated by the lower atmospheric forcings., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

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.

We analyse solar extreme ultraviolet (EUV) irradiance observed by the Solar EUV Experiment (SEE) onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite, and solar proxies (the F10.7 index, and Mg-II index), and compare their variability with the one of the global mean Total Electron Content (GTEC). Cross-wavelet analysis confirms the joint 27 days periodicity in GTEC and solar proxies. We focus on a comparison for solar minimum (2007-2009) and maximum (2013-2015) and find significant differences in the correlation during low and high solar activity years. GTEC is delayed by approximately 1-2 days in comparison to solar proxies during both low and high solar activity at the 27 days solar rotation period. To investigate the dynamics of the delay process, Coupled Thermosphere Ionosphere Plasmasphere electrodynamics model simulations have been performed for low and high solar activity conditions. Preliminary results using cross correlation analysis show an ionospheric delay of 1 day in GTEC with respect to the F10.7 index during low and high solar activity. Wir analysieren vom Solar Extreme Ultraviolet Experiment (SEE) an Bord des Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) Satelliten gemessene solare EUV-Irradianzen, solare Proxies (den F10.7-Index und denMg-II-Index), und vergleichen deren Variabilität mit derjenigen des global gemittelten Gesamtelektronengehalts (GTEC). Kreuzwaveletanalysen bestätigen eine gemeinsame Variabilität im Periodenbereich der solaren Rotation (27 Tage). Wir vergleichen insbesondere den Zusammenhang während des solaren Minimums (2007- 2009) und Maximums (2013-2015), wobei signifikante Unterschiede der Korrelation zwischen solaren und ionosphärischen Parametern auftreten. Es tritt eine Verzögerung der Maxima und Minima von GTEC gegenüber denjenigen der solaren Proxies von einem Tag sowohl im solaren Minimum als auch im solaren Maximum auf.

Rationale. Infantile Hemangiomas (IH) are the most frequent tumors of vascular origin, and the differential diagnosis from vascular malformations is difficult to establish. Specific types of IH due to the location, dimensions and fast evolution, can determine important functional and esthetic sequels. To avoid these unfortunate consequences it is necessary to establish the exact appropriate moment to begin the treatment and decide which the most adequate therapeutic procedure is. Objective. Based on clinical data collected by a serial clinical observations correlated with imaging data, and processed by a computer-aided diagnosis system (CAD), the study intended to develop a treatment algorithm to accurately predict the best final results, from the esthetical and functional point of view, for a certain type of lesion. Methods and Results. The preliminary database was composed of 75 patients divided into 4 groups according to the treatment management they received: medical therapy, sclerotherapy, surgical excision and no treatment. The serial clinical observation was performed each month and all the data was processed by using CAD. Discussions. The project goal was to create a software that incorporated advanced methods to accurately measure the specific IH lesions, integrated medical information, statistical methods and computational methods to correlate this information with that obtained from the processing of images. Based on these correlations, a prediction mechanism of the evolution of hemangioma, which helped determine the best method of therapeutic intervention to minimize further complications, was established. Abbreviations: Infantile Hemangiomas = IH, Computer Aided Diagnosis = CAD, Society for the Study of Vascular Anomalies = ISSVA, Color-coded duplex sonography = CCDS

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.

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.

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.

During geomagnetic storm, the energy transfer from solar wind to magnetosphere-ionosphere system adversely affects the communication and navigation systems. Quantifying storm impacts on TEC (Total Electron Content) and assessment of modeling capability of reproducing storm impacts on TEC are of importance to specifying and forecasting space weather. In order to quantify storm impacts on TEC, we considered several parameters: TEC changes compared to quiet time (the day before storm), TEC difference between 24-hour intervals, and maximum increase/decrease during the storm. We investigated the spatial and temporal variations of the parameters during the 2006 AGU storm event (14-15 Dec. 2006) using ground-based GPS TEC measurements in the selected 5 degree eight longitude sectors. The latitudinal variations were also studied in two longitude sectors among the eight sectors where data coverage is relatively better. We obtained modeled TEC from various ionosphere/thermosphere (IT) models. The parameters from the models were compared with each other and with the observed values. We quantified performance of the models in reproducing the TEC variations during the storm using skill scores. This study has been supported by the Community Coordinated Modeling Center (CCMC) at the Goddard Space Flight Center. Model outputs and observational data used for the study will be permanently posted at the CCMC website (http://ccmc.gsfc.nasa.gov) for the space science communities to use.

International audience; The upper atmosphere dynamics in the polar cap is mainly driven by ion-drag momentum sources imposed by the mapping of magnetosphere convection into the thermosphere/ionosphere and by Joule and auroral particle heating. Auroral particles also enhance conductivity particularly in the middle and lower ionosphere. Changes in the magnetospheric energy and momentum sources can significantly modify the wind circulation during geomagnetic storms. To observe these effects, a Michelson interferometer has been installed in Svalbard to measure winds in the thermosphere. Prior to 30 October 2003, cloud cover over Svalbard rendered the conditions unfavorable for optical observation. However, meteorological conditions improved after this date to enable the thermospheric response to the 28 October coronal mass ejection to be made. During quiet geomagnetic conditions measured wind velocities were in good agreement with those predicted by the Horizontal Wind Model (HWM). During disturbed geomagnetic conditions, HWM tended to underestimate the observed velocities. Comparison of the wind observations with a physical model tended to show reasonable agreement during both the strongly driven and recovery phase of the storm. Although the physical model did not always capture the timing of the rapid changes in the wind response in the early phase of the storm, the amplitudes of the fluctuations were in good agreement. After the initial phase the physical model agreed well with both the timing and amplitude of the meridional and zonal wind fluctuations. The meridional wind component was also derived from the EISCAT Svalbard Radar ion velocity and was found to be in close agreement with the optical winds observations.