Solar EUV Research Articles

Long Term Global Ionospheric Total Electron Content Trend Analysis

AbstractSimulations based on physical models of the thermosphere‐ionosphere system suggest that the ionosphere will sink as the thermosphere cools and contracts in response to increasing greenhouse gas concentrations. As a consequence, long‐term trends can be expected in ionospheric parameters such as: total electron content (TEC), the critical frequency of the F2 layer, foF2, and its peak height, hmF2. Since early 1990s, foF2 and hmF2, though to a lesser extent, have been widely analyzed to find these trends. This study shows long‐term TEC trends for the period 1999–2023 from available global International GNSS service TEC maps. Using F30, F10.7 or MgII as proxies to filter out the effect of solar EUV, the trends are negative, not only for the mean global value but also for most regions with very few exceptions. This would align with the greenhouse effect hypothesis, even though our results show higher negative trend values than expected theoretically.

Selecting the best solar EUV proxy for long-term timescale applications

Solar EUV proxies are a solution to the difficulties in obtaining solar EUV time series covering extended periods or during times without measurements available. Despite being very similar at interannual and decadal timescales, proxies are not identical. The upper atmosphere, highly sensitive to this spectral range, can serve as a “witness” of solar EUV variations to help selecting the best proxy. Its choice can be critical depending on the problem we are trying to solve through the proxy implementation and on the nature of the proxies’ non-identical part variation. We analyze the best proxy selection process whose outcome depends on the method and on the physics knowledge we have of the system. This study aims to contribute and highlight certain critical aspects of selection methodologies. A case where this issue becomes critical is upper atmosphere long-term trends’ estimation in order to detect the increasing greenhouse gas effect along the last decades.

The Venus Global Ionosphere‐Thermosphere Model (V‐GITM): A Coupled Thermosphere and Ionosphere Formulation

AbstractThis paper introduces the new Venus global ionosphere‐thermosphere model (V‐GITM) which incorporates the terrestrial GITM framework with Venus‐specific parameters, ion‐neutral chemistry, and radiative processes in order to simulate some of the observable features regarding the temperatures, composition, and dynamical structure of the Venus atmosphere from 70 to 170 km. Atmospheric processes are included based upon formulations used in previous Venus GCMs, several augmentations exist, such as improved horizontal and vertical momentum equations and tracking exothermic chemistry. Explicitly solving the momentum equations allows for the exploration of its dynamical effects on the day‐night structure. In addition, V‐GITM's use of exothermic chemistry instead of a strong heating efficiency accounts for the heating due to the solar EUV while producing comparable temperatures to empirical models. V‐GITM neutral temperatures and neutral‐ion densities are compared to upper atmosphere measurements obtained from Pioneer Venus and Venus Express. V‐GITM demonstrates asymmetric horizontal wind velocities through the cloud tops to the middle thermosphere and explains the mechanisms for sustaining the wind structure. In addition, V‐GITM produces reasonable dayside ion densities and shows that the neutral winds can carry the ions to the nightside via an experiment advecting .

The effect of mixing EUV proxies on the correlation with foF2 and on long-term trends estimations

Solar proxies are a valuable tool used in most atmospheric models to simulate or predict the state and variation of the different layers linked to the solar source. In this work, we analyze the performance, through correlation analysis, of six solar EUV proxies, and different combination of them, to reproduce annual ionospheric F2 critical frequency (foF2) from ten different stations. We find that certain combinations of traditional proxies outperform the capacity to reproduce interannual ionospheric foF2 variability, resulting in better statistical correlation and time stability, these new proxies could be a valuable tool to predict the state of the atmosphere and for interpolation in case of missing data. Different combinations of proxies such as F30, MgII, Sn or Lya, creates better indicators than using them alone. These new EUV proxies are also used to estimate long-term trends along the ten stations. As we increase the correlation, the estimated trend decrease as expected by definition. However, a key point is that the average trends, after filtering solar activity, result negative as was predicted by the increase of the greenhouse gases.

Influences of Space Weather Forecasting Uncertainty on Satellite Conjunction Assessment

AbstractA significant increase in the number of anthropogenic objects in Earth orbit has necessitated the development of satellite conjunction assessment and collision avoidance capabilities for new spacecraft. Neutral mass density variability in the thermosphere, driven by enhanced geomagnetic activity and solar EUV absorption, is a major source of satellite propagation error. This work investigates the impacts of space weather driver forecasting uncertainty on satellite drag and collision avoidance maneuver decision‐making. Since most operational space weather driver forecasts do not offer an uncertainty assessment, the satellite operator community is left to make dangerous assumptions about the trustworthiness of the forecast models they use to perform satellite state propagation. Climatological persistence‐based forecast models are developed for F10.7 and Kp. These models accurately capture the heteroscedastic and, at times, highly non‐Gaussian uncertainty distribution on forecasts of the drivers of interest. A set of realistic satellite conjunction scenarios is simulated to demonstrate the contributions of space weather driver forecast uncertainty on the probability of collision and maneuver decisions. Improved driver forecasts, especially forecasts of F10.7, are demonstrated to be very useful for enabling durable maneuver decisions with additional lead time (up to 24 hr for the period examined), though the improvement depends on the specific conjunction scenario of interest.

The electron density at the midpoint of the plasmapause

The high density plasmasphere in the magnetosphere is often separated from a lower density region outside of the plasmasphere, called the plasmatrough, by a sharp gradient in electron density called the plasmapause. Here we use plasmapause events identified from electron density data from the ISEE, CRRES, Polar, and IMAGE missions, and the nonlinear genetic algorithm TuringBot, to find models for the electron density at the midpoint of the plasmapause, ne,pp. A good model for ne,pp should include dependence on L, which is the strongest dependence. But models can be improved by including weaker dependencies on the magnetic local time, MLT, the solar EUV index F10.7, and geomagnetic activity as indicated by averages of Kp and AE. The most complicated model that we present predicts ne,pp within a factor of 1.64, and is within the range of observed plasmapause densities for about 96% of our events. These models can be useful for separating plasma populations into plasmasphere-like and plasmatrough-like populations. We also make available our database of electron density measurements categorized into various populations.

Exploring ionospheric dynamics: a comprehensive analysis of GNSS TEC estimations during the solar phases using linear function model

Abstract The modeling and forecasting of Total Electron Content (TEC) play a major role in influencing signals from satellite-based navigation systems and impact the performance of diverse satellite-dependent technologies. The intensity of solar ionizing radiation and the state of geomagnetic field activity influence the Global Navigation Satellite System (GNSS)-TEC. This paper uses a Linear TEC Function (LTF) climatology model to understand ionospheric behavior under solar and geomagnetic activities that cause variations in the electron distribution of the ionosphere medium. The LTF model integrates representations of solar EUV photon (MgII) and geomagnetic (SYMH) activities, incorporating solar-modulated oscillations (periodic variations) at four seasonal cycles and a linear trend. The LTF model examined the time series of GPS-TEC at a location (geographic 34.95° N, 134.05° E) with a time resolution of 1 h, from 1997 to 2016, covering solar cycles 23 and 24. The Root Mean Square Deviation (RMSD) and correlation coefficient between the GNSS-TEC and model TEC (LTF) was 5.30 TECU and 95 %. The results indicate that solar components, as well as annual and semi-annual variations, have a significant impact on the daily average TEC. Solar activity appears to be the predominant determining factor of TEC during the solar phases of cycles 23 and 24. In contrast, periodic influences primarily outline TEC during periods characterized by minimal solar activity. The geomagnetic component presents an increased influence, particularly during storm periods. The model demonstrates superior performance in Total TEC modeling compared to other state-of-the-art approaches.

An Experimental Study on EUV‐To‐Magnetogram Image Translation Using Conditional Generative Adversarial Networks

AbstractDeep generative models have recently become popular in heliophysics for their capacity to fill in gaps in solar observational data sets, thereby helping mitigating the data scarcity issue faced in space weather forecasting. A particular type of deep generative models, called conditional Generative Adversarial Networks (cGAN), has been used since a few years in the context of image‐to‐image (I2I) translation on solar observations. These algorithms have however hyperparameters whose values might influence the quality of the synthetic image. In this work, we use magnetograms produced by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) and EUV images from the Atmospheric Imaging Assembly (AIA) for the problem of generating Artificial Intelligence (AI) synthetic magnetograms from multiple SDO/AIA channels using cGAN, and more precisely the Pix2PixCC algorithm. We perform a systematic study of the most important hyperparameters to investigate which hyperparameter might generate magnetograms of highest quality with respect to the Structural Similarity Index. We propose a structured way to perform training with various hyperparameter values, and provide diagnostic and visualization tools of the generated versus targeted image. Our results shows that when using a larger number of filters in the convolution blocks of the cGAN, the fine details in the generated magnetogram are better reconstructed. Adding several input channels besides the 304 Å channel does not improve the quality of generated magnetogram, but the hyperparameters controlling the relative importance of the different loss functions in the optimization process have an influence on the quality of the results.

On Generalized Additive Models for Representation of Solar EUV Irradiance

AbstractIn the context of space weather forecasting, solar EUV irradiance specification is needed on multiple time scales, with associated uncertainty quantification for determining the accuracy of downstream parameters. Empirical models of irradiance often rely on parametric fits between irradiance in several bands and various solar indices. We build upon these empirical models by using Generalized Additive Models (GAMs) to represent solar irradiance. We apply the GAM approach in two steps: (a) A GAM is fitted between FISM2 irradiance and solar indices F10.7, Revised Sunspot Number, and the Lyman‐α solar index. (b) A second GAM is fit to model the residuals of the first GAM with respect to FISM2 irradiance. We evaluate the performance of this approach during Solar Cycle 24 using GAMs driven by known solar indices as well as those forecasted 3 days ahead with an autoregressive modeling approach. We demonstrate negligible dependence of performance on solar cycle and season, and we assess the efficacy of the GAM approach across different wavelengths.

A Comparative Analysis of the Solar Ultraviolet Spectral Irradiance Measured from Earth and Mars: Toward a General Empirical Model for the Study of Planetary Aeronomy

Accurate estimation of the solar vacuum ultraviolet irradiance between 0.1 and 200 nm is critical for the study of planetary aeronomy. Previous empirical models have relied on a limited number of reference spectra, or on multiple data sets with various degrees of uncertainty, and on an empirical selection of solar proxies. Here we propose a novel method for the development of empirical models based on Fourier transform and least-squares fitting of the long-term measurements from the Solar EUV Experiment on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission. A Fourier transform analysis is performed to examine a large number of solar proxies, which reveals that the solar radio flux at 10.7 cm and the solar Lyα flux at 121.6 nm are better proxies for solar irradiance below and above ∼120 nm, respectively. Using these two proxies, a nonlinear empirical model is developed through Fourier transform and least-squares fitting of solar irradiance measurements, which can reproduce the solar irradiance with uncertainties of only ∼1%–2% above ∼120 nm, ∼2%–4% within ∼45–120 nm, and ∼4%–8% below ∼45 nm. Comparison with measurements from the Extreme Ultraviolet Monitor on the Mars Atmosphere and Volatile Evolution mission indicates that the solar irradiance at Mars can be predicted with uncertainties of less than ∼8% by geometric extrapolation of the solar irradiance measured from Earth, provided that the measurements from Earth can be calibrated accurately. Our study provides a general method for the development of empirical models using long-term observations in planetary aeronomy.

Resolving Some Longstanding Issues in Far Ultraviolet Remote Sensing: A Self‐Consistent Analysis of the GUVI and SEE Observations on the TIMED Mission

AbstractFar Ultraviolet (FUV) remote sensing has been used in aeronomy missions as a powerful means to measure the temperature and compositions in the upper atmospheres of terrestrial planets. However, despite decades of continual development, outstanding challenges remain in this field. Particularly, there is currently a lack of methods for the examination and improvement of the data products in FUV remote sensing. As a result, longstanding issues exist in many of those data products. Here we demonstrate that a self‐consistent analysis of multi‐band airglow observations in the spectral range of ∼120–180 nm can serve as a useful means for examination and improvement of the data products in FUV remote sensing. The Global Ultraviolet Imager (GUVI) and Solar EUV Experiment (SEE) observations on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics mission are used for the demonstration. Through a self‐consistent analysis, we reconcile the thermospheric column O/N2 density ratios that are retrieved respectively from the GUVI limb and disk scans, by numerically correcting a systematic offset between those observations. We also reconcile the models with the observed 121.6 and 130.4 nm emission that have shown large discrepancies in the literature. The self‐consistent analysis indicates that the SEE measurements of the solar spectral irradiance below ∼45 nm need to be scaled down by ∼25%, whereas the SEE measurements of the solar 121.6 and 130.4 nm fluxes are highly accurate, with errors less than ∼3%. Our results achieve unprecedented agreement (better than ∼5%) between models and observations and provide a novel method for data examination and improvement in FUV remote sensing.

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.

GNSS Solar Astronomy in real-time during more than one solar cycle

This work presents a summary of the continuous non-stop (hereinafter 24/7) real-time measurement and warning system for EUV solar activity, which is based on worldwide multifrequency Global Navigation Satellite Systems (GNSS) observations. The system relies on continuous tracking of the intensity of expected global patterns in the Earth’s ionosphere’s free electron distribution, which are associated with solar flares. The paper includes a discussion on the foundations of GNSS Solar Astronomy, along with details on its real-time implementation that began in 2011. Furthermore, a summary of the corresponding validation is provided, comparing it to external and direct solar EUV flux measurements obtained from SOHO-SEM. Finally, there will be a brief mention of the ongoing efforts to extend this technique to detect huge extra-solar sources.

The Variation of Ionospheric O+ and H+ Outflow on Storm Timescales

AbstractGeomagnetic storms are primarily driven by stream interaction regions (SIRs) and coronal mass ejections (CMEs). Since SIR and CME storms have different solar wind and magnetic field characteristics, the magnetospheric response may vary accordingly. Using FAST/TEAMS data, we investigate the variation of ionospheric O+ and H+ outflow as a function of geomagnetic storm phase during SIR and CME magnetic storms. The effects of storm size and solar EUV flux, including solar cycle and seasonal effects, on storm time ionospheric outflow, are also investigated. The results show that for both CME and SIR storms, the O+ and H+ fluences peak during the main phase, and then declines in the recovery phase. However, for CME storms, there is also significant increase during the initial phase. Because the outflow starts during the initial phase in CME storms, there is time for the O+ to reach the plasma sheet before the start of the main phase. Since plasma is convected into the ring current from the plasma sheet during the main phase, this may explain why more O+ is observed in the ring current during CME storms than during SIR storms. We also find that outflow fluence is higher for intense storms than moderate storms and is higher during solar maximum than solar minimum.

A New Index to Describe the Relationship between Solar Extreme Ultraviolet Variation and Solar Activity

In this paper, a new solar activity index based on a novel disturbance extraction method, the spectral whitening method (SWM), is introduced to process the solar EUV data on the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. Our research suggests that the spatial information derived by SWM can well reflect the location of disturbance extraction, which is consistent with the location of the solar active region. It indicates that the disturbance extraction is effective. From AIA 094 Å to AIA 335 Å, SWM results are strongly correlated with solar radio flux F107 and the sunspot number (SSN), especially at AIA 211 Å, where the correlation coefficient reaches the maximum, while at AIA 1600 Å and AIA 1700 Å there are no detectable correlations. The proposed new solar activity index, , has the following characteristics: (1) the new index can reflect the main variations of F107 and SSN, indicating that the index is valid; (2) the new index has higher temporal resolution, which is more conducive to the more detailed study of solar activities on short timescales; (3) the new index reveals that the solar atmosphere still has significant variability during solar minimum characterized by low F107 and SSN; (4) the new index can be used in conjunction with the new magnetospheric and ionospheric indices, which are also derived by SWM to deepen the understanding of the causal chain of space weather and promote the improvement of forecasting capabilities.

Exploring sensitivity: Unveiling the impact of input parameters on Venus ionosphere [formula omitted] layer characteristics

This study investigates the impact of model input parameters on the characteristic features of the dayside V2 layer in the Venus ionosphere using an in-house developed one-dimensional photochemical model (1D-PCM) and observations from Venus Express radio science experiments (VeRa). 1D-PCM is simulated for different combinations of neutral density models (VTS3, a global empirical model of the Venus Thermosphere, and VenusGRAM, the Venus Global Reference Atmospheric Model), solar flux models (Solar 2000 (S2K), and observations by SEE (Solar EUV Experiment) onboard the NASA’s TIMED, the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics, satellite). The hmV2 (height of the V2 layer plasma density) is found to be better reproduced in VTS3-SEE and VTS3-S2K pairs of combination, indicating that VTS3 is a more representative model for Venusian neutral density. The nmV2 (peak plasma density of the V2 layer) remains consistently higher when using SEE data for solar fluxes, but the model deviates significantly for Solar Zenith Angles (SZA) between 65∘ and 85∘, possibly due to differences in neutral density at high SZA where the temperature is lower than predicted by the neutral density model. Quantitative analysis reveals that errors in the 1D-PCM, with deviations of 1 to 2 km in hmV2 and 5%–10% difference in nmV2 between the model and observations, could be due to uncertainties in the neutral density and solar flux models. Comparison with the Transplanet model suggests that accounting for input uncertainties can improve the model’s ability to reproduce observations. This study provides insights into the influence of input parameters on the Venus ionosphere and highlights the importance of considering uncertainties in modeling studies.

Dependence of long-term trends in foF2 at middle latitudes on different solar activity proxies

The most studied ionospheric parameter for long-term trends is foF2. The dominant factor of foF2 variability is the solar cycle, which is much stronger than the long-term trends. Therefore its effect in data must be removed. However, several decade long homogeneous measurements of the solar EUV fluxes are not available, so various solar activity proxies (solar activity indices) must be used. The aim of this paper is to study the impact of selection of different solar activity proxies on foF2 long-term trends and to find the best solar activity proxy for foF2 trends at middle latitudes. The results based on yearly average data of six midlatitude stations from four continents (1976–2014) and of six solar activity proxies show that the long-term trends in foF2 depend substantially on the solar activity proxy used, and the only solar proxy, which provides trends of the same sign for all stations and both sub-periods, is F30. Based on results of this paper and that of Laštovička and Burešová (2023), I can recommend F30 as the best solar proxy for studying long-term trends of foF2 at middle latitudes (at least for yearly average values).

The source of unusual coronal upflows with photospheric abundance in a solar active region

Context. Upflows in the corona are of importance, as they may contribute to the solar wind. There has been considerable interest in upflows from active regions (ARs). The coronal upflows that are seen at the edges of active regions have coronal elemental composition and can contribute to the slow solar wind. The sources of the upflows have been challenging to determine because they may be multiple, and the spatial resolution of previous observations is not yet high enough. Aims. In this article, we analyse coronal upflows in AR 12960 that are unusually close to the sunspot umbra. We analyse their properties, and we attempt to determine if it is possible that they feed into the slow solar wind. Methods. We analysed the activity in the upflow region in detail using a combination of Solar Orbiter EUV images at high spatial and temporal resolution, Hinode/EUV Imaging Spectrometer data, and observations from instruments on board the Solar Dynamics Observatory. This combined dataset was acquired during the first Solar Orbiter perihelion of the science phase, which provided a spatial resolution of 356 km for two pixels. Doppler velocity, density, and plasma composition determinations, as well as coronal magnetic field modelling, were carried out to understand the source of the upflows. Results. We observed small magnetic fragments, called moving magnetic features (MMFs), moving away from the sunspot in the active region. Specifically, they moved towards the sunspot from the edge of the penumbra where a small positive polarity connects to the umbra via small-scale and very dynamic coronal loops. At this location, small dark grains are evident and flow along penumbral filaments in continuum images. The magnetic field modelling showed small low-lying loops anchored close to the umbral magnetic field. The high-resolution data of the Solar Orbiter EUV Imagers showed the dynamics of these small loops, which last on time scales of only minutes. The edges of these small loops are the location of the coronal upflow that has photospheric abundance.

Performance of the IRI-2016 and IRI-Plas 2020 considering Mg II as EUV solar proxy

To assess upper atmosphere parameters, current models use different variables to account for solar activity levels. Studies that evaluate the most recent solar cycles have shown that when dealing with the ionospheric F2 layer, and in particular with foF2, the Mg II index is a better choice than other solar activity proxies to account for solar EUV variation. The International Reference Ionosphere, version 2016 (IRI-2016), a model widely used by the scientific community, uses the Ionosonde Global (IG) index to assess foF2. A most recent and expanded version, IRI-Plas, allows selecting a solar activity proxy among 7 options including IG and Mg II. In the present work, the performance of IRI considering Mg II to assess foF2 is analyzed, comparing three modeling cases: IRI-2016 with its default solar activity index (IG), IRI-2016 with Mg II instead of IG, and IRI-Plas choosing Mg II as the solar proxy option. This model comparison was evaluated in terms of their agreement with measured foF2 data from four stations located in Japan (Northern Hemisphere), and four in Australia (Southern Hemisphere). Monthly medians for the 24 h, along two periods of three years were considered: 2000–2002 and 2008–2010, which correspond to epochs of maximum and minimum solar activity levels, respectively. Based on goodness-of-fit statistics, our results show that in the case of IRI-2016, the Mg II implementation does not reveal a significant improvement for foF2 assessment, and the IRI-Plas performance with the Mg II option is only slightly better than the other two options. Dispersion diagrams between measured and modeled foF2 also evince a similar performance between the three models. All models show the same over- and underestimation patterns, except in the nighttime case during the minimum activity level period for both Australian and Japanese stations where IRI-Plas outperforms the other two model options. The comparable performances of the three options might be attributed to a stronger variation in the evaluated periods which could be related to seasonal changes rather than to solar EUV proxies. Future studies considering time series over several years, covering at least a complete solar activity cycle, are required to determine stronger model performance differences.

Study on the Method of Extracting Plasma Lines Based on Sanya Incoherent Scatter Radar

The plasma lines observed by Sanya incoherent scatter radar (SYISR) are dependent on the enhancement of Langmuir waves due to superthermal photoelectrons generated by solar EUV radiation. The plasma line power spectrum can be obtained using long-pulse and alternating-code transmission signals during the period from sunrise to noon almost every day. For the power spectrum of the long pulse, the CLEAN algorithm that has been applied in this field is used to verify the feasibility of this method for SYISR in only a few cases. However, it is difficult to deal with alternating code with such a low SNR using the general deconvolution method. The irreversible-migration filtering (IMF) method has been developed to separate signal noise from the measurements of the alternating code. Some experimental results from the SYISR measurements validate the excellent performance of the IMF method for alternating code. Additionally, an example observation of the electron density with a high time and range resolution is derived. The results show that plasma line detection can be a powerful new observational capability for SYISR as an ionospheric experimental mode for ionospheric calibration, when possible, which can be simultaneously measured with the ion line for constant radar calibration in the standard fitting of the ion line.