Solar energetic particles are mainly protons and originate from the Sun during solar flares or coronal shock waves. Forecasting the Solar Energetic Protons (SEP) flux is critical for several operational sectors, such as communication and navigation systems, space exploration missions, and aviation flights, as the hazardous radiation may endanger astronauts’, aviation crew and passengers’ health, the delicate electronic components of satellites, space stations, and ground power stations. Therefore, the prediction of the SEP flux is of high importance to our lives and may help mitigate the negative impacts of one of the serious space weather transient phenomena on the near-Earth space environment. Numerous SEP prediction models are being developed with a variety of approaches, such as empirical models, probabilistic models, physics-based models, and AI-based models. In this work, we use the bi-directional long short-term memory (BiLSTM) neural network model architecture to train SEP forecasting models for 3 standard integral GOES channels ($>$10 MeV, $>$30 MeV, $>$60 MeV) with 3 forecast windows (1-day, 2-day, and 3-day ahead) based on daily data obtained from the OMNIWeb database from 1976 to 2019. As the SEP variability is modulated by the solar cycle, we select input parameters that capture the short-term, typically within a span of a few hours, and long-term, typically spanning several days, fluctuations in solar activity. We take the F10.7 index, the sunspot number, the time series of logarithm of the x-ray flux, the solar wind speed, and the average strength of the interplanetary magnetic field as input parameters to our model. The results are validated with an out-of-sample testing set and benchmarked with other types of models.

In this paper, we discuss a novel retrieval of ionospheric electron density profiles using the Radio Occultation (RO) technique applied to measurements captured by the GPS receivers on-board two Geostationary Operational Environmental Satellites (GOES). The GOES satellites operate at ~35800 km altitude and are primarily weather satellites that operationally contribute continuous remote-sensing data for real-time weather forecasting, as well as near Earth environment monitoring and Sun observations. The GPS receivers onboard GOES-16 and GOES-17 satellites can track GPS signals propagated through the Earth’s atmosphere, and although the receivers are primarily designed for navigation and station-keeping maneuvers, these GPS measurements that traverse the Earth’s atmosphere can be used to retrieve the ionospheric electron density profiles. This process poses a range of technical challenges. GOES RO links are different from the traditional low Earth orbit (LEO) RO geometry since the receiver is located in an orbit that is higher in altitude than the GPS constellation of transmitters. Additionally, the GPS receivers onboard GOES satellites provide only single frequency GPS L1 observations and have clocks much less stable than those typically used for RO measurements. The geographical distribution of the retrieved GEO-based RO profiles was found to be uniquely constrained and repeatable based on the relative geo-stationary fixed positions in the Earth Centered Earth Fixed reference frame with respect to the GPS constellation orbiting at lower altitude, and significantly different from the coverage patterns of LEO-based RO missions. We demonstrate the successful application of the proposed RO profiling technique with a statistically significant set of GPS observations from GOES-16 and GOES-17 satellites over several years of data collection. This enabled us to retrieve more than 10K ionospheric electron density profiles with a maximum altitude up to 1000–2000 km, much higher than any existing LEO-based RO mission. We demonstrate good performance of GEO-based RO measurements for properly specifying the vertical distribution of ionospheric plasma density by comparing the profiles dataset from the GOES RO experiment with independent reference observations—ground-based ionosondes and LEO-based RO missions, as well as model simulation results provided by the empirical International Reference Ionosphere model. Over multiple years of observations, statistical analysis of discrepancies between the ionospheric F2 layer peak parameters (peak density and height) derived from geosynchronous GOES observations and reference measurements was conducted. This analysis reveals a very good agreement between GOES RO electron density profiles and independent types of measurements in both the F2 peak and in the profile shape.

Inhomogeneities within the ionospheric plasma density affect trans-ionospheric radio signals, causing radio wave scintillation in the amplitude and phase of the signals. The amount of scintillation induced by ionospheric irregularities typically decreases with the radio wave frequency. As the ionosphere affects a variety of technological systems (e.g., civil aviation, financial operations) as well as low-frequency radio astronomy observations, it is important to detect and monitor iono- spheric effects with higher accuracy than currently available. Here, a novel methodology for the detection and characterization of ionospheric irregularities is established on the basis of LOFAR scintillation measurements at VHF that takes into account of the lack of ergodicity in the intensity fluctuations induced by scintillation. The methodology estimates the S 4 scintillation index originating from irregularities with spatial scales in the inertial sub-range of electron density fluctuations in the ionosphere. The methodology is illustrated by means of observations that were collected through the Polish LOFAR stations located in Bałdy, Borówiec and Łazy: its validation was carried out by comparing LOFAR VHF scintillation observations with independent GNSS observations that were collected through a high-rate receiver located near the LOFAR station in Bałdy as well as through geodetic receivers from the Polish ASG-EUPOS network. Two case stud- ies are presented: 31 March 2017 and 28 September 2017. The comparison between LOFAR S4 observations and independent ionospheric measurements of both scintillation and rate of change of TEC from GNSS reveals that the sensitivity of LOFAR and GNSS to ionospheric structures is different as a consequence of the frequency dependency of radio wave scintillation. Furthermore, it can be noticed that observations of LOFAR VHF scintillation can be utilised to detect plasma structures forming in the mid-latitude ionosphere, including electron density gradients occurring over spatial scales that are not necessarily detected through traditional GNSS measurements: the detection of all spatial scales is important for a correct monitoring and modelling of ionospheric processes. Hence, the different sensitivity of LOFAR to ionospheric structures, in addition to traditional GNSS ionospheric measurements, allows to expand the knowledge of ionospheric processes.

Geomagnetically induced currents (GIC) driven by geoelectric fields pose a hazard to ground-based infrastructure, such as power grids and pipelines. Here, a new method is presented for modelling geoelectric fields in near real time, to provide valuable information to help mitigate the impact of GIC. The method uses magnetic field measurements from the Magnetometer Network of Ireland (MagIE; https://www.magie.ie), interpolates the geomagnetic field variations between magnetometers using spherical elementary current systems (SECS), and estimates the local electric field using a high-density (< 40 km) network of magnetotelluric transfer functions (MT-TF) encompassing the island. The model was optimised to work in near real time, with a correction curve applied to the geoelectric field time series. This approach was successfully validated with measured electric fields at four sites for a number of geomagnetic storms, providing accurate electric fields up to a 1-minute delay from real time, with high coherence (0.70 – 0.85) and signal-to-noise ratio (SNR; 3.2 – 6.5) relative to measured electric field validation time series. This was comparable to a standard non-real-time geoelectric field model (coherence = 0.80 − 0.89 and SNR = 4.0 − 7.0). The impact of galvanic distortion on the model was also briefly evaluated, with a galvanic distortion correction leading to a more homogeneous representation of the direction of the electric field, at a regional scale.

The plasma in the cusp ionosphere is subject to particle precipitation, which is important for the development of large-scale irregularities in the plasma density. These irregularities can be broken down into smaller scales which have been linked to strong scintillations in the Global Navigation Satellite System (GNSS) signals. We present power spectra for the plasma density irregularities in the cusp ionosphere for regions with and without auroral particle precipitation based on in-situ measurements from the Twin Rockets to Investigate Cusp Electrodynamics-2 (TRICE-2) mission, consisting of two sounding rockets flying simultaneously at different altitudes. The electron density measurements taken from the multi-needle Langmuir probe system (m-NLP) were analyzed for the whole flight duration for both rockets. Due to their high sampling rates, the probes allow for a study of plasma irregularities down to kinetic scales. A steepening of the slope in the power spectra may indicate two regimes, a frequency interval with a shallow slope, where fluid-like processes are dominating, and an interval with a steeper slope which can be addressed with kinetic theory. The steepening occurs at frequencies between 20 Hz and 100 Hz with a median similar to the oxygen gyrofrequency. Additionally, the occurrence of double slopes increases where precipitation starts and throughout the rest of the flight. In addition, strong electron density fluctuations were found in regions poleward of the cusp, thus in regions immediately after precipitation. Furthermore, by investigating the integrated power of the fluctuations within different frequency ranges, we show that at low frequencies (10–100 Hz), the power is pronounced more evenly while the rocket encounters particle precipitation, while at high frequencies (100–1000 Hz) fluctuations essentially coincide with the passing through a flow channel.

Auroral particle precipitation potentially plays the main role in ionospheric plasma structuring. The impact of auroral particle precipitation on plasma structuring is investigated using multi-point measurements from scintillation receivers and all-sky cameras from Longyearbyen, Ny-Ålesund, and Hornsund on Svalbard. This provides us with the unique possibility of studying the spatial and temporal dynamics of the aurora. Here we consider three case studies to investigate how plasma structuring is related to different auroral forms. We demonstrate that plasma structuring impacting the GNSS signals is largest at the edges of auroral forms. Here we studied two stable arcs, two dynamic auroral bands, and a spiral. Specifically for arcs, we find elevated phase scintillation index values at the poleward edge of the aurora. This is observed for auroral oxygen emissions (557.7 nm) at 150 km in the ionospheric E-region. This altitude is also used as the ionospheric piercing point for the GNSS signals as the observations remain the same regardless of different satellite elevations and azimuths. Further, there may be a time delay between the temporal evolution of aurora (e.g., commencement and fading of auroral activity) and observations of elevated phase scintillation index values. The time delay could be explained by the intense influx of particles, which increases the plasma density and causes recombination to carry on longer, which may lead to a persistence of structures – a “memory effect”. High values of phase scintillation index values can be observed even shortly after strong visible aurora and can then remain significant at low intensities of the aurora.

We present a new 3D magnetohydrodynamic (MHD) heliospheric model for space-weather forecasting driven by boundary conditions defined from white-light observations of the solar corona. The model is based on the MHD code PLUTO, constrained by an empirical derivation of the solar wind background properties at 0.1 au. This empirical method uses white-light observations to estimate the position of the heliospheric current sheet (HCS). The boundary conditions necessary to run HelioCast are then defined from pre-defined relations between the necessary MHD properties (speed, density, and temperature) and the distance to the current sheet. We assess the accuracy of the model over six Carrington rotations during the first semester of 2018. Using point-by-point metrics and event-based analyses, we evaluate the performances of our model varying the angular width of the slow solar wind layer surrounding the HCS. We also compare our empirical technique with two well-tested models of the corona: Multi-VP and WindPredict-AW. We find that our method is well-suited to reproduce high-speed streams, and does – for well-chosen parameters – better than full MHD models. The model shows, nonetheless, limitations that could worsen for rising and maximum solar activity.

Context: The main challenge in atmospheric ionisation modelling is that sparse measurements are used to derive a global precipitation pattern. Typically this requires intense interpolation or scaling of long-term average maps. In some regions however, the particle flux might be similar and a combination of these regions would not limit the results even though it would dramatically improve the spatial and temporal data coverage. Aims: The paper intends to statistically analyse the particle flux distribution close to the geomagnetic poles labelled as Polar Particle Flux Distribution (PPFD) and identify similar distributions in neighbouring bins. Those bins are grouped and the size of the PPFD area is estimated. The benefit is that single measurements within the PPFD area should be able to represent the particle flux for the whole area at a given time. Methods: We use spatially binned energetic particle flux distributions measured by POES and Metop spacecraft during 2001–2018 to identify a Kp-dependent area with a similar flux distribution as the one found close to the geomagnetic poles (|magn.lat| > 86°). First, the particle flux is mapped on a magnetic local time (MLT) vs. magnetic latitude grid. In the second step, the gridded data is split up according to Kp levels (forming the final bins). Third, the particle flux in every bin has been recalculated in order to replace zero-count rates with rates based on longer measurement periods which results in a more realistic low flux end of the particle distribution. Then the binned flux distributions are compared to the PPFD. A “Δ-test” indicates the similarity. A threshold for the Δ-test is defined using the standard deviation of Δ-test values inside the (|magn.lat| > 86°) area. Bins that meet the threshold are attributed as PPFD area. Results: PPFDs and the corresponding PPFD areas have been determined for all investigated particle channels, covering an energy range of 154 eV–300 keV for electrons and 154 eV–2.5 MeV for protons. Concerning low energy channels a gradual flux increase with rising Kp has been identified. High energy channels show a combination of background population and solar particle event (SPE) population that adds up with increasing Kp. The size of the PPFD area depends on particle species, energy and geomagnetic disturbance, as well as MLT. The main findings are: a) There are small but characteristic hemispheric differences. b) Only above a certain energy threshold do the PPFD areas increase with particle energy. c) A clear enlargement with rising Kp is identified – with exceptions for very low Kp. d) The centre of the PPFD area is shifted towards midnight and moves with Kp. Asymmetries of the boundaries could be explained by auroral intensity. e) For low-energy particles the main restriction of the PPFD area seems to be the auroral precipitation.

We present new neutral mass density and crosswind observations for the CHAMP, GRACE, and GRACE-FO missions, filling the last gaps in our database of accelerometer-derived thermosphere observations. For consistency, we processed the data over the entire lifetime of these missions, noting that the results for GRACE in 2011–2017 and GRACE-FO are entirely new. All accelerometer data are newly calibrated. We modeled the temperature-induced bias variations for the GRACE accelerometer data to counter the detrimental effects of the accelerometer thermal control deactivation in April 2011. Further, we developed a new radiation pressure model, which uses ray tracing to account for shadowing and multiple reflections and calculates the satellite’s thermal emissions based on the illumination history. The advances in calibration and radiation pressure modeling are essential when the radiation pressure acceleration is significant compared to the aerodynamic one above 450 km  altitude during low solar activity, where the GRACE and GRACE-FO satellites spent a considerable fraction of their mission lifetime. The mean of the new density observations changes only marginally, but their standard deviation shows a substantial reduction compared to thermosphere models, up to 15% for GRACE in 2009. The mean and standard deviation of the new GRACE-FO density observations are in good agreement with the GRACE observations. The GRACE and CHAMP crosswind observations agree well with the physics-based TIE-GCM winds, particularly the polar wind patterns. The mean observed crosswind is a few tens of m·s−1 larger than the model one, which we attribute primarily to the crosswind errors being positive by the definition of the retrieval algorithm. The correlation between observed and model crosswind is about 60%, except for GRACE in 2004–2011 when the signal was too small to retrieve crosswinds reliably.

The radiation environment over the African continent, at aviation altitudes, remains mostly uncharacterized and unregulated. In this paper, we present initial measurements made by a newly developed active dosimeter onboard long-haul flights between South Africa and Germany. Based on these initial tests, we believe that this low-cost and open-source dosimeter is suitable for continued operation over the African continent and can provide valuable long-term measurements to test dosimetric models and inform aviation policy.