Pedagogies

EUVS-C is one component of the Extreme Ultraviolet Irradiance Sensor (EUVS) instrument. EUVS together with the X-ray sensor (XRS) comprise the Extreme Ultraviolet and X-ray Irradiances Sensors (EXIS) investigation (Machol et al. 2020) aboard the GOES-R satellite series which includes GOES-16, -17, -18, and -19. From their vantage points in geostationary orbit, the EUVS-C instruments measure the solar Mg II Index, also referred to as the Mg II core-to-wing-ratio, which is a proxy for chromosphere activity and correlates with solar extreme ultraviolet (EUV) emission. Mg II produces two bright chromosphere emission lines appearing in the sun’s spectrum at 279.55 nm and 280.71 nm (Mg II k and h) that appear in the cores of their respective photospheric absorption lines. Measuring the ratio of emission from the core (chromsopheric) to that from the wings (photospheric) provides an index that is relatively insensitive to changes in instrument performance. In 2005, Snow & McClintock used 0.1nm resolution data to show that the intrinsic solar variability in the index (as opposed to instrument noise) is on the order of 0.2% on time scales 5-10 minutes. EUVS-C is designed to exceed these performance requirements. A companion paper describes the instrument design and its pre-flight calibration. This paper describes the operational implementation for the algorithm that produces the Index, flight calibrations, and the initial instrument flight performance. Each EUVS-C currently operating (GOES-16, -17, and -18) is providing high time-cadence (3 seconds), high precision (1 part in 104) Index determinations.  Spectral shifts arising from spacecraft orbital motion introduce a systematic 0.1% diurnal variation in absolute index values.  Additionally, wavelength dependent radiometric responsivity degradation leads to a systematic increase in the reported index on a timescale of years at an average rate of 0.2% per year. These systematic effects can be mitigated with additional post data processing.

EUVS-C is one component of the Extreme Ultraviolet Irradiance Sensor (EUVS) instrument. EUVS together with the X-ray sensor (XRS) comprise the Extreme Ultraviolet and X-ray Irradiances Sensors (EXIS) investigation aboard the GOES-R satellite series which includes GOES-16, -17, -18, and -19. From their vantage points in geostationary orbit, the EUVS-C instruments make high-precision (better than 1 part in 104), high-time-cadence (3 seconds) measurements of the solar Mg II Index with moderate (0.1 nm) spectral resolution. The Index, also referred to as the Mg II core-to-wing-ratio, is a proxy for chromosphere activity that correlates with solar extreme ultraviolet (EUV) irradiance. Mg II produces two bright chromosphere emission lines in the Sun’s spectrum at 279.55 nm and 280.71 nm (Mg II k and h) that appear in the cores of their respective photospheric absorption lines. Measuring the ratio of emission from the core (chromospheric) to that from the wings (photospheric) provides an index that is relatively insensitive to changes in radiometric performance that often occur when scientific instruments observe the Sun. EUVS-C design specifications were informed by earlier research reporting index variability of approximately 0.2% on time scales of 6 – 10 minutes, increasing to approximately 0.3% and approximately 0.55% for 30 and 80 minutes, respectively. This paper describes the EUVS-C instrument design and implementation, its ground calibration and characterization, and anticipated measurement performance. A companion paper describes initial EUVS-C flight measurement performance.

The rapid increase in X-ray and extreme ultraviolet (EUV) emissions owing to solar flares enhances ionization in the ionosphere, increasing radio wave attenuation. Among these phenomena, the shortwave communication disturbance caused by the increased electron density in the ionospheric D region is known as the shortwave fadeout (SWF). We investigated the relationship between SWF's magnitude and solar flare emission, and evaluated the electron density variation in the ionospheric D region associated with flare. We defined the minimum frequency (fmin) observed in Japan’s ionograms as the SWF’s magnitude. We analyzed ionosonde data for 38 SWF events observed during daytime in Japan between May 2010 and May 2014. To investigate the relationship between flares and SWF, we compared the observed X-ray and EUV emissions during flares with the dfmin (background subtracted fmin). X-ray (0.1-0.8 nm) and EUV (11-14 nm) emissions correlate with dfmin. Then, using the GAIA model, a numerical model that treats the entire Earth’s atmosphere, we investigated the effect of the ray and EUV solar flare emissions on the ionosphere, which affects the SWF. The results showed that the main ionization source in the ionospheric D region was X-ray emission, and shortwaves were attenuated by ∼90 %. In contrast, in the ionospheric E and F regions, the primary ionization source was EUV emission, with only ∼10 % shortwave attenuation. Finally, we estimated the fmin values and blackout (total fadeout of the ionospheric echo observed in ionograms) and compared the simulated and observed fmin values. The hit rate of blackouts was 35 % when we only used the GAIA calculations. Therefore, we estimated fmin using the electron density variation in the ionospheric D region corresponding to X-ray solar emission. As a result, the hit rate of the blackout was 68 %, and the linear correlation coefficient between the simulated and observed fmin values was 0.85. The estimated magnitude of the SWF was improved by incorporating the effects of X-ray emissions into the ionospheric D region of GAIA. We are the first to implement a method for evaluating the electron density in the ionospheric D region using the fmin value.

In December 2019, the Space Weather Prediction Center (SWPC) started using the GOES -16 satellite as its primary input for the solar x-ray flux monitoring. As such, it stopped applying a scaling factor that had been applied since the GOES-8 came in operation. This has an important impact on the number of flares that can be expected, and on the flare rates associated with the McIntosh classifications, often used to help forecast flaring activity. To quantify the effects, the flare intensities for the period covering 1976-2019 have all been recalculated. An increase of respectively 55% and 52% in the total number of M-class and X-class events has been observed. Also, for the same period, McIntosh classifications have been redone by visually evaluating 4720 Kanzelhöhe solar drawings (about 1 drawing every 3 days) and determining the McIntosh type of 22232 sunspot regions. There's an excellent agreement with the values originally reported by McIntosh (1990), but some deviations from the SWPC data are found. For a majority of the McIntosh classes, an increase in the flare rates is observed, which translates into increased flare probabilities assuming a Poisson distribution for the flare occurrence. This is an important given for space weather forecasters when making solar flare forecasts. The McIntosh classification is successful in distinguishing flare active from flare inactive regions: Considering only the “p” and “c” component of the McIntosh classification and linking them to the number of flares associated with the corresponding sunspot groups, we find that 48% of all M- and X-class flares in our study are produced by only 8% of all sunspot groups, belonging to the McIntosh subclasses -ai, -kc, and -ki corresponding to sunspot groups with an asymmetric main spot and a more complex (intermediate or compact) internal sunspot distribution. About 57% of all classified sunspot groups produce only 12% of all M- and X-class flares. They belong to the McIntosh subclasses -so, -sx, -xo and -xx, which correspond to the smallest and simplest sunspot regions, and the phases marking the emergence and final decay of sunspot groups (Axx, Bxo, Hsx). Though the McIntosh classification is a great tool to forecast flaring activity, there remain large differences in the actual flaring behaviour of individual sunspot groups within the same McIntosh class.

The Geostationary Environmental Operational Satellites R series (GOES-R) includes an instrument that measures visible light from the Sun at high cadence: the Solar Position Sensor (SPS).   SPS is part of the Extreme ultraviolet and X-ray Irradiance Sensors (EXIS) instrument package. The visible wavelength range observed by SPS includes the peak power of the solar spectrum.  Tracking the solar input to the  climate system is important at all timescales. This article is the first in a series that will describe using the SPS data as a high-cadence proxy for Total Solar Irradiance (TSI), and as an input to the spectral model used in  the NOAA Climate Data Record for solar irradiance.    We describe the design of the SPS instrument and create a model of its output using the solar spectrum measured by the  Total and Spectral Irradiance Sensor-1 (TSIS-1) on the International Space Station. We apply the bandpasses of the SPS components to the daily TSIS-1  Solar Irradiance Monitor (SIM) spectrum and integrate over wavelength to simulate the SPS measurement. After applying the appropriate SPS filter transmittances and diode responsivity to the  TSIS-1/SIM spectrum, we compare the integrated irradiances from the full SIM spectrum and the SPS model to the TSI measurement from TSIS-1.   These comparisons of daily averages show that the integrated SPS model reproduces TSI with an uncertainty of 53 parts per million. We also show a preliminary comparison of the SPS data to the high-cadence TSI measurements from the Digital Absolute RAdiometer (DARA) on the FY-3E satellite.   The modeled SPS spectrum shows excellent agreement with TSI on a daily cadence. Once all the instrument calibrations have been established, the SPS data will be a viable operational high-cadence proxy for TSI.

The Carrington event of September 1859 is the best known example of an extreme geomagnetic storm, often cited when discussing space weather risks for modern infrastructure. Historic observations including auroral sightings, magnetometer records and anecdotes of impacts on telegraph systems have been widely shared before, but none of these have included observations from the Netherlands. Geomagnetic observations taken in Utrecht and Den Helder during the Carrington event were digitised from the Royal Netherlands Meteorological Institute’s (KNMI) yearbook of 1859, and compared to much more detailed magnetograms from London. This combined analysis, beyond its application in communication with Dutch stakeholders, contributes to a better understanding of the interpretation, limitations, and uses of such archived measurements, of which more examples might be available in archives internationally. The observations consist of spot measurements taken three times per day. The Den Helder data only partially record the Carrington storm. Conversion factors from Den Helder have been used to estimate missing conversion factors of the Utrecht data. The correlation between the Dutch declination measurements and those made in London is strong with correlation coefficients larger than 0.7 for the Utrecht data and larger than 0.9 for the Den Helder data. However, there is very little correlation between the Dutch and British inclination measurements. The London horizontal intensity measurements compared to Den Helder data give correlation values larger than 0.8 but the observations from Utrecht match less well. There is a significant deviation between the British data and the Utrecht declination and horizontal intensity measurements during the quiet period between 30 August and 2 September. It is unclear what causes this deviation. Given the proximity of the locations and similarity in latitude, and based on the coherent registration of the measurements, it is reasonable to assume that the magnetic traces captured in London provide a good approximation of the magnetic field variations in the Netherlands during the storm, indicating that these may be used for impact assessment studies for Dutch vital infrastructure.

A climatology of Travelling Ionospheric Disturbances (TIDs) observed using the LOw Frequency ARray (LOFAR) has been created based on 2,723 hours of astronomical observations. Radio telescopes such as LOFAR must contend with many causes of signal distortions, including the ionosphere. To produce accurate astronomical images, calibration solutions are derived to mitigate these distortions as much as possible. These calibration solutions provide extremely precise measurements of ionospheric variations across the LOFAR network, enabling TIDs to be detected which may be inaccessible to more traditional techniques. Waves are detected by LOFAR under all observing conditions, with no clear dependence on solar or geomagnetic activity. The vast majority of the observed waves travel in the opposite direction to the climatological thermospheric winds, suggesting that they are caused by upward propagating atmospheric gravity waves which are filtered by the wind. Waves of different periods display slightly different propagation directions, with waves of shorter periods consistent with the winds at lower altitudes within the thermosphere ($\SI{180}{\kilo\metre}$ for $10-\SI{15}{\minute}$ periods compared to $\SI{220}{\kilo\metre}$ for $20-\SI{27}{\minute}$ periods). This suggests that either the shorter period waves are being detected at lower altitudes or that they are simply more sensitive to the winds at lower altitudes. This indicates that observations made using LOFAR may enable the investigation of vertical coupling within the neutral atmosphere. The shortest period waves in the dataset ($<\sim\SI{10}{\minute}$) display distinct characteristics, suggesting they may be from a distinct population such as previously reported disturbances in the plasmasphere. The short period waves are compared to previous observations using other radio telescopes, showing that plasmaspheric disturbances likely account for some of the shortest period waves ($<\sim\SI{5}{\min}$) but there are still a large number of waves at these periods which are of uncertain origin.

This study’s objective is to better specify the rare occurrence of super equatorial plasma bubbles in particular in the European longitude sector, detailing their spatio-temporal evolution, and better understanding pre-conditions for their development. Our comprehensive multi-instrument analysis combined ground-based and space observations from GNSS, ionosondes, and several satellite missions (COSMIC-2, GOLD, Swarm). We have investigated the ionospheric response to the 23–24 April 2023 severe geomagnetic storm and have shown the formation of super plasma bubbles expanding from equatorial latitudes to middle latitudes in the European/African sector during the main phase of the storm. Formation of these super bubbles was associated with storm-induced prompt penetration electric fields. We found that the area affected by the formation of numerous plasma bubbles covered more than 5000 km ranging from 30°W to 30°E in the Atlantic/African sector. The bubbles also had an impressive north-south extension, reaching as far poleward as ~30°–35° latitude in both hemispheres. After 20 UT on 23 April 2023, the zone with equatorial ionospheric irregularities reached Northern Africa, the Iberian Peninsula (Spain, Portugal) and the Mediterranean Sea in southern Europe, including areas of the Canary Islands (Spain) and the Azores and Madeira Islands (Portugal) in the Atlantic Ocean. The ionospheric irregularities persisted for 5–6 hours and began to fade after ~01 UT on 24 April 2023. COSMIC-2 scintillation measurements showed intense amplitude scintillations (S4 above 0.8) across this entire region, indicating presence of small-scale ionospheric irregularities inside the extended plasma bubbles. During this storm, EGNOS (European Geostationary Navigation Overlay Service) experienced degraded performance, with significant navigation errors recorded at its southernmost stations in Northern Africa, Spain, Portugal, and their territories, which were affected by super plasma bubbles. This paper presents conclusive observational evidence showing development of the super plasma bubbles significantly expanding into the southern Europe and northern Africa region under geomagnetically disturbed conditions in April 2023.

On 3 February 2022 49 SpaceX Starlink satellites were launched at the orbits with altitudes between 210 and 320 km and 38 of them were lost due to enhanced neutral density associated with two moderate geomagnetic storms. To investigate the impact of these geomagnetic storms on the Thermosphere-Ionosphere system F-layer Ne(h) profiles from ground-based ionosondes, located in different longitudinal sectors of both Hemispheres, and Swarm-C neutral density observations were analysed using an original method, THERION. Day-time mid-latitude thermosphere has manifested very moderate < 50% neutral density perturbations at 250 km height. The largest perturbations of thermospheric and related ionospheric parameters took place in American and Australian ‘near-pole’ longitudinal sectors. The largest (30-50)% atomic oxygen [O] increase took place in the Northern winter Hemisphere where [O] provided the main contribution to the neutral density ρ250 increase. On the contrary, [O] manifested a strong down to -(20-40)% storm depression in the summer Hemisphere and ρ250 increase was due to molecular nitrogen [N2] increase related to elevated neutral temperature Tex. Downwelling of [O] and the increase of [N2] due to elevated Tex work in parallel in the Northern winter Hemisphere resulting in (35-45)% increase of ρ250. On the contrary, [O] and [N2] work in opposite directions compensating to a great extent the contribution of each other to ρ250 in the Southern summer Hemisphere. The European longitudinal sector manifested same features as ‘near-pole’ ones but with less magnitude, so a (16-35)% storm-time increase of ρ250 in the winter European sector was mainly due to the [O] increase. The ‘far-from-pole’ winter Japanese sector manifested very moderate < 21% neutral density perturbations mainly related to Tex increase. The obtained results have shown a moderate impact on the Thermosphere-Ionosphere system produced by two geomagnetic storms in February 2022 but this impact was sufficient to result in loss of 38 satellites highlighting a necessity to conduct the routine monitoring of the thermosphere.

As large solar energetic particle (SEP) events can add significant radiation dose to astronauts in a short period of time and even induce acute clinical responses during missions, they present a concern for manned space flight operation. To assist the operations team in modeling and monitoring organ doses and any possible acute radiation-induced risks to astronauts during SEP events in real time, ARRT (Acute Radiation Risks Tool) 1.0 has been developed and successfully tested for Artemis I mission. The ARRT 2.0 described in this work integrates an established SEP forecasting model – UMASEP-100, further enabling real-time dose prediction for the upcoming Artemis II and following missions. With the new module linking with UMASEP-100 outputs in real time, the total BFO doses of most significant events can be communicated at the time of onset and hours before the peak. This is based on a flux-dose formula identified from comparing UMASEP-100 results with transport calculation for the events during 1994-2013 and validated with events outside that period. ARRT 2.0 also shows capability to distinguish minor events from significant ones to screen false alarms that will cause disruptions for space activities. This improvement provides additional information for operational teams to make timely decisions in contingent scenarios of severe SEP events to mitigate radiation exposure.

Equatorial Plasma Bubbles (EPBs) play a crucial role in modulating plasma density and electron content within the equatorial ionosphere. In this work, we present an advanced and more robust version of the method developed by Blanch E et al. (2018, J Space Weather Space Clim., 8, 38–32) for detecting EPBs using data from the Global Navigation Satellite System (GNSS). The enhancements introduced in this version significantly improve the EPB detection process, achieving a notable reduction in the false positive rate compared to the previous approach. These refinements include the application of more rigorous statistical techniques to achieve a more accurate fit for the background Total Electron Content (TEC), leading to better characterization of EPBs through improved estimation of disturbance shapes. Applying the capabilities of this new method in a dense network of GNSS sensors, we have developed an interferometric procedure for estimating EPB drift velocities, including both speed and direction. This procedure provides valuable insights into the dynamic behavior of EPBs in the Caribbean region during 2014. Our analysis reveals a predominant eastward propagation pattern of EPBs, closely aligned with modified dip isolines. Furthermore, by integrating the results from the GNSS-based method with quasi co-located digisondes, we applied a conceptual model to estimate EPB velocities along their drift direction. This model has been tested across different geographical sectors and validated through comparisons with results from other independent studies. This cross-verification confirms the reliability of the methods for capturing EPB characteristics. This approach improves the precision of EPB detection and contributes to a deeper understanding of their spatiotemporal dynamics and behavior, providing a valuable framework for characterizing these phenomena in the equatorial ionosphere.

Gradual solar energetic particle (SEP) events are generally attributed to the particle acceleration in shock waves driven by coronal mass ejections (CMEs). Space-weather effects of such events are important, so there has been continuous effort to develop models able to forecast their various characteristics. Here we present the first version of a new such model with the primary goal to address energetic storm particle (ESP) events. The model, PARASOL, is built upon the PArticle Radiation Asset Directed at Interplanetary Space Exploration (PARADISE) test-particle simulation model of SEP transport, but includes a semi-analytical description of an inner (i.e., near the shock) part of the foreshock region. The semi-analytical foreshock description is constructed using simulations with the SOLar Particle Acceleration in Coronal Shocks (SOLPACS) model, which simulates proton acceleration self-consistently coupled with Alfvén wave generation upstream of the shock, and subsequent fitting of the simulation results with suitable analytical functions. PARASOL requires input of solar wind and shock magnetohydrodynamic (MHD) parameters. We evaluate the performance of PARASOL by simulating the 12 July 2012 SEP event, using the EUropean Heliospheric FORecasting Information Asset (EUHFORIA) MHD simulation of the solar wind and CME in this event. The PARASOL simulation has reproduced the observed ESP event (E ≲ 5 MeV) in the close vicinity of the shock within one order of magnitude in intensity.

The nature of the long-term changes in the upper atmosphere morphology at mid-latitude remains a subject of debate, particularly regarding whether these changes are purely driven by geomagnetic and solar activities or whether forcing from the lower atmosphere, such as CO2 variations, may play a role. To contribute to this debate, we investigate the nature of the long-term trends of the ionospheric and thermospheric parameters by leveraging on ionosonde data digitally recorded at the Rome Observatory since 1976. The following parameters have been investigated under sunlit conditions (12:00 Local Time): critical frequency of the F1 layer (foF1); critical frequency of the F2 layer (foF2), atomic oxygen concentration at 300 km ([O]); ratio between atomic oxygen and molecular nitrogen concentrations at 300 km altitude ([O]/[N2]); exospheric temperature (Tex); thermospheric density at 300 km (ρ). The ionospheric parameters are manually scaled from digital ionograms, whereas thermospheric parameters are retrieved using the THERmospheric parameters from IONosonde observations (THERION) method, which utilises ionosonde observations and a physical model of the ionospheric F region. To investigate the influence of the solar and geomagnetic activity on long term variations, we consider the solar radio flux at 10.7 cm (F10.7) and the geomagnetic disturbance index Ap. To identify the various frequency/period components of the time series under consideration and identify the trends, we leverage the high scale/time resolution offered by the Fast Iterative Filtering (FIF) algorithm. A regression analysis of thermosphere/ionosphere parameters against geomagnetic/solar activity indices has then been conducted to investigate the drivers of long-term variability. Our findings reveal that the identified trends are predominantly controlled by external drivers, particularly long-term solar and geomagnetic activity variations.. The adopted methodology, based on regression modelling, demonstrates that variability in F10.7 and Ap accounts for nearly all of the observed changes, with the exception of atomic oxygen ([O]), which displays a slightly higher unexplained variability (~7%). The inclusion of CO2 concentration as an additional driver improves the regression model for [O]. However, the effect remains statistically limited, indicating that the impact of CO2 on thermospheric cooling might be of little significance. Further studies with extended time series are necessary to better quantify this relationship and evaluate its importance. These results highlight the predominant influence of solar and geomagnetic activity in determining upper atmosphere long-term trends at mid-latitudes.

This study explores the meteorological source and vertical propagation of gravity waves (GWs) that drive daytime traveling ionospheric disturbances (TIDs), using the specified dynamics version of the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (SD-WACCM-X) and the Sami3 is Also a Model of the Ionosphere (SAMI3) simulations driven by SD-WACCM-X neutral wind and composition. A cold weather front moved over the northern-central U.S.A. (90-100W, 35-45N) during the daytime of 20 October 2020, with strong upward airflow. GWs with ~500-700 km horizontal wavelengths propagated southward and northward in the thermosphere over the north-central U.S.A. Also, the perturbations were coherent from the surface to the thermosphere; therefore, the GWs were likely generated by vertical acceleration associated with the cold front over Minnesota and South Dakota. The convectively generated GWs had almost infinite vertical wavelength below ~100 km due to being evanescent. This implies that the GWs tunneled through their evanescent region in the middle atmosphere (where a squared vertical wavenumber is equal to/smaller than 0) and became freely propagating in the thermosphere and ionosphere. Medium-scale TIDs (MSTIDs) also propagated southward with the GWs, suggesting that the convectively generated GWs created MSTIDs.

We explore the use of space-based UV images as a substitute for ground-based Ca II K-line images in modeling Total Solar Irradiance (TSI) variability. The sunspot signal for all 2-component models used here is determined from SFO red continuum images at 672.3 nm. The facular signal is determined from either Ca II K-line images at 393.4 nm or space-based UV images from the Solar Dynamics Observatory AIA experiment at 160 nm and 170 nm wavelengths. Images at both AIA wavelengths are processed with the standard SFO algorithms. The results show good agreement between the fits to Total Solar Irradiance (TSI) variations using ground-based Ca K-line images and the fits to space-based UV images. However, AIA 170 nm images were superior to 160 nm images. The best 2-component fit using ground-based Ca II K-line data was R2 = 0.873; AIA 170 nm produced R2 = 0.896, better than AIA 160 nm’s R2 = 0.793.