Solar Wind Properties Research Articles

Testing the flux tube expansion factor

Context. The properties of the solar wind measured in situ in the heliosphere are largely controlled by energy deposition in the solar corona, which is in turn closely related to the properties of the coronal magnetic field. Previous studies have shown that long-duration and large-scale magnetic structures show an inverse relation between the solar wind velocity measured in situ near 1 au and the expansion factor of the magnetic flux tubes in the solar atmosphere. Aims. The advent of the Solar Orbiter mission offers a new opportunity to analyse the relation between solar wind properties measured in situ in the inner heliosphere and the coronal magnetic field. We exploit this new data in conjunction with models of the coronal magnetic field and the solar wind to evaluate the flux expansion factor and speed relation. Methods. We use a Parker-like solar wind model, the “isopoly” model presented in previous works, to describe the motion of the solar wind plasma in the radial direction and model the tangential plasma motion due to solar rotation with the Weber and Davis equations. Both radial and tangential velocities are used to compute the plasma trajectory and streamline from Solar Orbiter location sunward to the solar ‘source surface’ at rss. We then employed a potential field source surface (PFSS) model to reconstruct the coronal magnetic field below rss to connect wind parcels mapped back to the photosphere. Results. We found a statistically weak anti-correlation between the in situ bulk velocity and the coronal expansion factor, for about 1.5 years of solar data. Classification of the data by source latitude reveals different levels of anticorrelation, which is typically higher when Solar Orbiter magnetically connects to high latitude structures than when it connects to low latitude structures. We show the existence of a fast solar wind that originates in strong magnetic field regions at low latitudes and undergoes large expansion factor. We provide evidence that such winds become supersonic during the super-radial expansion (below rss) and are theoretically governed by a positive v–f correlation. We find that faster winds exhibit, on average, a flux tube expansion at a larger radius than slower winds. Conclusions. An anticorrelation between solar wind speed and expansion factor is present for solar winds originating in high latitude structures in solar minimum activity, typically associated with coronal hole-like structures, but this cannot be generalized to lower latitude sources. We have found extended time intervals of fast solar wind associated with both large expansion factors and strong photospheric magnetic fields. Therefore, the value of the expansion factor alone cannot be used to predict the solar wind speed. Other parameters, such as the height at which the expansion gradient is the strongest, must also be taken into account.

Persistent high-latitude ionospheric response to solar wind forcing

The solar wind continuously transfers energy into the Earth’s thermosphere-ionosphere system and variations in the solar wind properties modify the state of the system. The modifications are best visible during storm conditions when the ingestion of extreme amounts of solar wind energy into the thermosphere-ionosphere system causes global changes in thermosphere as well as large deviations in the ionospheric electron density from its quiet conditions. This study shows that there exists a persistent impact of the solar wind on the high-latitude electron density. A data set of 22 years of Total Electron Content (TEC) and 15 years of ionosonde data (critical frequency foF2 and height of maximum electron density hmF2) at Tromsø (70°N, 19°E) are used for correlation analyses with different solar wind parameters derived from measurements of the Advanced Composition Explorer (ACE). The results show that the ionospheric parameters systematically respond with an increase or decrease depending on local time, season and solar cycle. TEC and foF2 increase with solar wind energy during winter night conditions and decrease with increasing solar wind energy during summer daytime. The summer negative ionospheric response is more intense during solar maximum conditions, while the winter positive ionospheric response is stronger during solar minimum. An anomaly is observed around 10 UT (noon), when TEC and foF2 respond with an increase during solar minimum conditions. Cross polar cap plasma convection, particle precipitation and Joule heating are considered to be the main drivers of the electron density changes at Tromsø. Local time, season and solar cycle changes in the background ionosphere-thermosphere conditions lead to different effects of theses driving processes. The results help to better understand the variability of the high-latitude electron density and show that solar wind forcing causes a systematic and persistent response of the ionosphere which alternates depending on local time, season and solar cycle.

Solar Wind With Field Lines and Energetic Particles (SOFIE) Model: Application to Historical Solar Energetic Particle Events

AbstractIn this paper, we demonstrate the applicability of the data‐driven solar energetic particle (SEP) model, SOlar‐wind with FIeld‐lines and Energetic‐particles (SOFIE), to simulate the acceleration and transport processes of SEPs and make forecast of the energetic proton flux at energies ≥10 MeV that will be observed near 1 AU. The SOFIE model is built upon the Space Weather Modeling Framework developed at the University of Michigan. In SOFIE, the background solar wind plasma in the solar corona and interplanetary space is calculated by the Stream‐Aligned Aflvén Wave Solar‐atmosphere Model(‐Realtime) driven by the near‐real‐time hourly updated Global Oscillation Network Group solar magnetograms. In the background solar wind, coronal mass ejections (CMEs) are launched by placing an force‐imbalanced magnetic flux rope on top of the parent active region, using the Eruptive Event Generator using Gibson‐Low model. The acceleration and transport processes are modeled by the Multiple‐Field‐Line Advection Model for Particle Acceleration. In this work, nine SEP events (Solar Heliospheric and INterplanetary Environment challenge/campaign events) are modeled. The three modules in SOFIE are validated and evaluated by comparing with observations, including the steady‐state background solar wind properties, the white‐light image of the CMEs, and the flux of solar energetic protons, at energies of ≥10 MeV.

Automatic Detection of Large-scale Flux Ropes and Their Geoeffectiveness with a Machine-learning Approach

Abstract Detecting large-scale flux ropes (FRs) embedded in interplanetary coronal mass ejections (ICMEs) and assessing their geoeffectiveness are essential, since they can drive severe space weather. At 1 au, these FRs have an average duration of 1 day. Their most common magnetic features are large, smoothly rotating magnetic fields. Their manual detection has become a relatively common practice over decades, although visual detection can be time-consuming and subject to observer bias. Our study proposes a pipeline that utilizes two supervised binary classification machine-learning models trained with solar wind magnetic properties to automatically detect large-scale FRs and additionally determine their geoeffectiveness. The first model is used to generate a list of autodetected FRs. Using the properties of the southward magnetic field, the second model determines the geoeffectiveness of FRs. Our method identifies 88.6% and 80% of large-scale ICMEs (duration ≥ 1 day) observed at 1 au by the Wind and the Solar TErrestrial RElations Observatory missions, respectively. While testing with continuous solar wind data obtained from Wind, our pipeline detected 56 of the 64 large-scale ICMEs during the 2008–2014 period (recall = 0.875), but also many false positives (precision = 0.56), as we do not take into account any additional solar wind properties other than the magnetic properties. We find an accuracy of 0.88 when estimating the geoeffectiveness of the autodetected FRs using our method. Thus, in space-weather nowcasting and forecasting at L1 or any planetary missions, our pipeline can be utilized to offer a first-order detection of large-scale FRs and their geoeffectiveness.

The Differences in the Origination and Properties of the Near-Earth Solar Wind between Solar Cycles 23 and 24

The dependence of the sources and properties of the near-Earth solar wind on solar cycle activity is an important issue in solar and space physics. We use the improved “two-step” mapping procedure that takes into account the initial acceleration processes to trace the near-Earth solar winds back to their source regions from 1999–2020, covering solar cycles (SCs) 23 and 24. Then, the solar wind is categorized into coronal hole (CH), active region (AR), and quiet Sun (QS) solar wind based on the source region type. We find that the proportions of CH and AR (QS) wind during SC 23 are higher (lower) than those during SC 24. During solar maximum and declining phases, the magnetic field strength, speed, helium abundance (A He), and charge states of all three types of solar wind during SC 23 are generally higher than those during SC 24. During solar minimum, these parameters of solar wind are generally lower during SC 23 than those during SC 24. There is a significant decrease in the charge states of all three types of solar wind during the solar minimum of SC 23. The present statistical results demonstrate that the sources and properties of the solar wind are both influenced by solar cycle amplitude. The temperatures of AR, QS, and CH regions exhibit significant differences at low altitudes, whereas they are almost uniform at high altitudes.

Solar Wind‐Magnetosphere Coupling Efficiency and Its Dependence on Solar Activity During Geomagnetic Storms of 23–24 Solar Cycles

AbstractSpace weather forecasts are of utmost importance in safeguarding navigation, communication, and electric power system operations, satellites from orbital drag, and the astronauts in the International Space Station from hazardous space radiation during extreme space weather conditions. The finest space weather prediction requires a clear understanding of solar wind‐magnetosphere coupling. The in‐situ measurements of the solar wind properties give unique information about the Sun and its activity on smaller to longer timescales. The present work investigates the influence of solar activity on the coupling of solar wind and Earth's magnetosphere during 23–24 solar cycles. The geomagnetic storms with Symmetric H‐component (SYMH) ≤ −85 nT during the 23–24 solar cycles are considered. We present the results of statistical analysis and relationships between the various solar wind parameters such as the total strength of interplanetary magnetic field (B) and its three‐axis components (Bx, By, and Bz), solar wind proton density (Nsw), solar wind speed (Vsw), SYMH indices, the amplitude, duration, and profile of the geomagnetic storms. The integrated electric field and integrated SYMH index during storms show the highest correlation of 0.92, implying that integrated SYMH is a better proxy of the injected solar wind energy in the magnetosphere in the form of the ring current. Moreover, we do see the difference in the solar wind‐magnetosphere coupling efficiency during the phases of 23–24 solar cycles which is intriguing.

Cross-Scale Phase Relationship of the Ca II K Index with Solar Wind Parameters: A Space Climate Focus

The solar wind, representing one of the most impacting phenomena in the circum-terrestrial space, constitutes one of the several manifestations of the magnetic activity of the Sun. With the aim of shedding light on the scales beyond the rotational period of the Sun (i.e., Space Climate scales), this study investigates the phase relationship of a solar activity physical proxy, the Ca II K index, with solar wind properties measured near the Earth, over the whole space era (last five solar cycles). Using a powerful tool such as the Hilbert–Huang transform, we investigate the dependence of their phase coherence on the obtained time scale components. Phase coherence at the same time scales is found between all the components and is also preserved between adjacent components with time scales ≳ 2 yrs. Finally, given the availability of the intrinsic modes of oscillation, we explore how the relationship of Ca II K index with solar wind parameters depends on the time scale considered. According to our results, we hypothesize the presence of a bifurcation in the phase-space Ca II K index vs. solar wind speed (dynamic pressure), where the time scale seems to act as a bifurcation parameter. This concept may be pivotal for unraveling the complex interplay between solar activity and solar wind, bearing implications from the prediction and the interpretation point of view in Space Climate studies.

Evaluation of Scale-dependent Kurtosis with HelioSwarm

Plasma turbulence involves complex, nonlinear interactions of electromagnetic fields and charged particles across multiple scales. Studying these phenomena in space plasmas, like the solar wind, is facilitated by the intrinsic scale separations and the availability of in situ spacecraft observations. However, the single-point or single-scale configurations of current spacecraft limit our understanding of many properties of the turbulent solar wind. To overcome these limitations, multipoint measurements spanning a range of characteristic scales are essential. This Letter prepares for the enhanced measurement capabilities of upcoming multispacecraft missions by demonstrating that higher-order statistics, specifically kurtosis, as a baseline for intermittency can be accurately measured. Using synthetic turbulent fields with adjustable intermittency levels, we achieve scale separations analogous to those in the solar wind and apply these techniques to the planned trajectories of the HelioSwarm mission. This approach promises significant advancements in our understanding of plasma turbulence.

Structure and dynamics of the Hermean magnetosphere revealed by electron observations from the Mercury electron analyzer after the first three Mercury flybys of BepiColombo

The Mercury electron analyzer (MEA) obtained new electron observations during the first three Mercury flybys by BepiColombo on October 1, 2021 (MFB1), June 23, 2022 (MFB2), and June 19, 2023 (MFB3). BepiColombo entered the dusk side magnetotail from the flank magnetosheath in the northern hemisphere, crossed the Mercury solar orbital equator around midnight in the magnetotail, traveled from midnight to dawn in the southern hemisphere near the closest approach, and exited from the post-dawn magnetosphere into the dayside magnetosheath. We aim to identify the magnetospheric boundaries and describe the structure and dynamics of the electron populations observed in the various regions explored along the flyby trajectories. We derive 4s time resolution electron densities and temperatures from MEA observations. We compare and contrast our new BepiColombo electron observations with those obtained from the Mariner 10 scanning electron spectrometer (SES) 49 years ago. A comparison to the averaged magnetospheric boundary crossings of MESSENGER indicates that the magnetosphere of Mercury was compressed during MFB1, close to its average state during MFB2, and highly compressed during MFB3. Our new MEA observations reveal the presence of a wake effect very close behind Mercury when BepiColombo entered the shadow region, a significant dusk-dawn asymmetry in electron fluxes in the nightside magnetosphere, and strongly fluctuating electrons with energies above 100s eV in the dawnside magnetosphere. Magnetospheric electron densities and temperatures are in the range of 10-30 cm$^ $ and above a few 100s eV in the pre-midnight-sector, and in the range of 1-100 cm$^ $ and well below 100 eV in the post-midnight sector, respectively. The MEA electron observations of different solar wind properties encountered during the first three Mercury flybys reveal the highly dynamic response and variability of the solar wind-magnetosphere interactions at Mercury. A good match is found between the electron plasma parameters derived by MEA in the various regions of the Hermean environment and similar ones derived in a few cases from other instruments on board BepiColombo.

Origin and Properties of the Near-subsonic Solar Wind Observed by Parker Solar Probe

We identify and examine the solar wind intervals near the sonic critical point (i.e., M S ∼ 1) observed by the Parker Solar Probe. The near-subsonic wind intervals show similar properties: a low density, an extremely low velocity, a low proton temperature, and essentially no magnetic field deflections compared with the surrounding solar wind. The extremely low velocity is the primary contributor to the near crossing of the sonic critical point rather than the sound speed, which is roughly constant in these intervals. Source tracing with a potential-field source-surface model suggests that the near subsonic intervals all connect to the boundaries inside coronal holes. Heliospheric current sheet (HCS) and partial HCS crossings around the near subsonic intervals indicate that the near subsonic wind is a transition layer between the slow and fast winds. The above scenario is consistent with the nature of the near-subsonic wind as a low-Mach-number boundary layer, which facilitates the crossing of the sonic critical point at 15–20 R S . Moreover, we find a dependence of the amplitude of switchbacks on the radial sonic Mach number. Magnetic field deflections essentially disappear near the sonic critical point, which suggests that switchbacks originate from above the sonic critical point.

Combining Empirical and Physics-Based Models for Solar Wind Prediction

Solar wind modeling is classified into two main types: empirical models and physics-based models, each designed to forecast solar wind properties in various regions of the heliosphere. Empirical models, which are cost-effective, have demonstrated significant accuracy in predicting solar wind at the L1 Lagrange point. On the other hand, physics-based models rely on magnetohydrodynamics (MHD) principles and demand more computational resources. In this research paper, we build upon our recent novel approach that merges empirical and physics-based models. Our recent proposal involves the creation of a new physics-informed neural network that leverages time series data from solar wind predictors to enhance solar wind prediction. This innovative method aims to combine the strengths of both modeling approaches to achieve more accurate and efficient solar wind predictions. In this work, we show the variability of the proposed physics-informed loss across multiple deep learning models. We also study the effect of training the models on different solar cycles on the model’s performance. This work represents the first effort to predict solar wind by integrating deep learning approaches with physics constraints and analyzing the results across three solar cycles. Our findings demonstrate the superiority of our physics-constrained model over other unconstrained deep learning predictive models.

An updated catalog of IPS radio sources observed by MEXART at 140 MHz for space weather studies

The Mexican Array Radio Telescope (MEXART) is an instrument dedicated to performing interplanetary scintillation (IPS) observations at 140 MHz. After the MEXART backend’s digitization, the array’s technical capabilities have improved substantially, and we observe new IPS sources. By analyzing observations recorded from June 2020 to June 2022, we present an updated catalog of radio sources observed with an IPS signature by MEXART. First, we implemented an algorithm to treat the noise presented by some channels in the frequency. Next, we obtained the spectra of the observations to get the frequency of the Fresnel’s knee and determine whether each radio source exhibited IPS. We then estimated the source’s flux at 140 MHz by interpolating flux density data to different frequencies using the NASA/IPAC Extragalactic Database. Finally, we present a list of 38 radio sources showing IPS signatures. The source list presents declination, right ascension, and flux at 140 MHz. This updated catalog will allow studies of solar wind properties in the inner heliosphere using MEXART data.

Alfvénic fluctuations in the expanding solar wind: Formation and radial evolution of spherical polarization

We investigate properties of large-scale solar wind Alfvénic fluctuations and their evolution during radial expansion. We assume a strictly radial background magnetic field B∥R, and we use two-dimensional hybrid (fluid electrons, kinetic ions) simulations of balanced Alfvénic turbulence in the plane orthogonal to B; the simulated plasma evolves in a system comoving with the solar wind (i.e., in the expanding box approximation). Despite some model limitations, simulations exhibit important properties observed in the solar wind plasma: Magnetic field fluctuations evolve toward a state with low-amplitude variations in the amplitude B=|B| and tend to a spherical polarization. This is achieved in the plasma by spontaneously generating field aligned, radial fluctuations that suppress local variations of B, maintaining B∼ const. spatially in the plasma. We show that within the constraint of spherical polarization, variations in the radial component of the magnetic field, BR lead to a simple relation between δBR and δB=|δB| as δBR∼δB2/(2B), which correctly describes the observed evolution of the rms of radial fluctuations in the solar wind. During expansion, the background magnetic field amplitude decreases faster than that of fluctuations so that their the relative amplitude increases. In the regime of strong fluctuations, δB∼B, this causes local magnetic field reversals, consistent with solar wind switchbacks.

Tracking solar radio bursts using Bayesian multilateration

Solar radio bursts (SRBs), such as Type IIs and IIIs, are emitted by electrons propagating through the corona and interplanetary space. Tracking such bursts is key to understanding the properties of accelerated electrons and radio wave propagation as well as the local plasma environment that they propagate through. In this work, we present a novel multilateration algorithm called BayEsian LocaLisation Algorithm (BELLA) and validate the algorithm using simulated and observed SRBs. In addition, apparent SRB positions from BELLA are compared with comparable localisation methods and the predictions of solar wind models. BELLA uses Bayesian inference to create probabilistic distributions of source positions and their uncertainties. This facilitates the estimation of algorithmic, instrumental, and physical uncertainties in a quantitative manner. We validated BELLA using simulations and a Type III SRB observed by STEREO A and STEREO B at pm 116 degr from the Sun-Earth line and by Wind at L1. BELLA tracked the Type III source from sim 10--150 $R_ (2--0.15 MHz) along a spiral trajectory. This allowed for an estimate of an apparent solar wind speed of sw 400 km $ and a source longitude of $ 30degr . We compared these results with well-established methods of positioning: Goniopolarimetric (GP), analytical time-difference-of-arrival (TDOA), and Solar radio burst Electron Motion Tracker (SEMP). We found them to be in agreement with the results obtained by BELLA. Additionally, the results aligned with solar wind properties assimilated by the Heliospheric Upwind Extrapolation with time dependence (HUXt) model. We have validated BELLA and used it to identify apparent source positions as well as velocities and densities of the solar wind. Furthermore, we identified higher than expected electron densities, suggesting that the true emission sources were at lower altitudes than those identified by BELLA, an effect that may be due to appreciable scattering of electromagnetic waves by electrons in interplanetary space.

Magnetohydrodynamic Perspective on the Disappearance of Mercury’s Bow Shock by Helios Data Exploration

In the magnetohydrodynamic (MHD) perspective, the planet’s bow shock would disappear when the fast-mode Mach number (M F) of the solar wind is less than one. Compared to Earth, Mercury is subject to a lower M F solar wind due to its proximity to the Sun, resulting in a higher possibility of the disappearance of its bow shock. To examine the variability of Mercury’s bow shock in response to the solar wind properties, analyses of the observations by the Helios spacecraft at 0.30–0.50 au during 1975–1983, covering solar cycle 21, together with the theoretical solutions and MHD simulations are conducted in this study. Our observational analyses show that more solar wind data with extremely low fast-mode Mach numbers (say, M F ≤ 1.5) are observed during the rising and maximum phases and are characterized by a significantly low proton number density. It is also found that approximately 35% of the extremely low fast-mode Mach number solar wind events (M F ≤ 1.5) occur within the main body of interplanetary coronal mass ejections (ICMEs), while about 58% of them are unrelated to ICMEs. Three of these events are selected to demonstrate that the occurrences of the solar wind with M F ≤ 1.5 may not be necessarily affected by ICMEs. Our theoretical and numerical results indicate that when Mercury encounters the solar wind with M F ≤ 1.5, its bow shock would move farther away, become flattened, and even disappear. Furthermore, our calculations suggest that Mercury’s bow shock would become a slow-mode shock with a concave-upward structure under such extreme solar wind conditions.

Analysis of the Motion of Solar Wind (SW) and Other Solar Activities Impacts on the Earth

Solar wind (SW), the powerful outflow of charged particles from the Sun, has a significant impact on Earth's magnetosphere, ionosphere, and atmospheric processes. This paper examines the motion of SW and its effects on Earth, focusing on changes such as slow and fast SWs and their impacts on geomagnetic storms, ionospheric disturbances, and precipitation patterns. Observations from spacecraft, including the Solar and Heliospheric Observatory (SOHO), the Advanced Composition Explorer (ACE), and the Wind spacecraft, have provided valuable data on solar wind properties. However, there are limitations in spatial coverage and the measurement of internal SW properties. Accurately predicting SW behavior remains a challenge. Future research should focus on developing advanced observational techniques, utilizing multiple spacecraft, and improving modeling and data analysis approaches. The forthcoming expeditions, specifically the Solar Orbiter and Parker Solar Probe, are predicted to provide novel understandings into solar activity. Enhancing our understanding of solar activity and improving space weather predictions are crucial for mitigating the potential adverse effects of SW on electricity, communication, and other human activities. This research contributes to advancements in space weather forecasting and the reliable and safe operation of our technological infrastructure.

Relating Intermittency and Inverse Cascade to Stochastic Entropy in Solar Wind Turbulence

Turbulent energy transfer in nearly collisionless plasmas can be conceptualized as a scale-to-scale Langevin process. Hence, the statistics of magnetic field fluctuations can be embedded in the framework of stochastic process theory. In this work, we investigate the statistical properties of the pristine solar wind as observed by Parker Solar Probe by defining the cascade trajectories of magnetic field increments and by estimating the stochastic entropy variation along them. Through the stochastic entropy, we can identify two regimes where fluctuations exhibit contrasting statistical properties. In the inertial range, the entropy production is associated with an increase of the flatness indicating the occurrence of intermittency. Otherwise, trajectories associated with an entropy consumption exhibit global scale invariance. In the transition region toward ion scales, the phenomenology switches: entropy-consuming trajectories exhibit a sudden flatness increase, associated with the presence of small-scale intermittency, while entropy-producing trajectories display a nearly constant flatness. Results are interpreted in terms of physical processes consistent with an accumulation of energy at ion scales.

Global MHD Simulations of the Time-dependent Corona

We describe, test, and apply a technique to incorporate full-Sun, surface flux evolution into an MHD model of the global solar corona. Requiring only maps of the evolving surface flux, our method is similar to that of Lionello et al., but we introduce two ways to correct the electric field at the lower boundary to mitigate spurious currents. We verify the accuracy of our procedures by comparing to a reference simulation, driven with known flows and electric fields. We then present a thermodynamic MHD calculation lasting one solar rotation driven by maps from the magnetic flux evolution model of Schrijver & DeRosa. The dynamic, time-dependent nature of the model corona is illustrated by examining the evolution of the open flux boundaries and forward-modeled EUV emission, which evolve in response to surface flows and the emergence and cancellation flux. Although our main goal is to present the method, we briefly investigate the relevance of this evolution to properties of the slow solar wind, examining the mapping of dipped field lines to the topological signatures of the “S-Web” and comparing charge state ratios computed in the time-dependently driven run to a steady-state equivalent. Interestingly, we find that driving on its own does not significantly improve the charge state ratios, at least in this modest resolution run that injects minimal helicity. Still, many aspects of the time-dependently driven model cannot be captured with traditional steady-state methods, and such a technique may be particularly relevant for the next generation of solar wind and coronal mass ejection models.

Ion kinetic effects linked to magnetic field discontinuities in the slow Alfvénic wind observed by Solar Orbiter in the inner heliosphere

Slow solar wind, sharing magnetic and plasma properties typical of fast wind, the so-called slow Alfvénic wind, has been widely observed in the heliosphere. Here, we report an analysis of the turbulent properties of a slow Alfvénic stream observed by Solar Orbiter at 0.64 AU. This solar wind stream is characterized by well distinguishable regions, namely, a main portion, an intermediate region, and a rarefaction region. Each of those intervals have been studied separately, in order to enhance similarities and differences in their turbulence properties. Coherent structures naturally emerge over different time/spatial scales and their characteristics at ion scales have been investigated. The presence of these intermittent events have been found to be closely related to kinetic features in the ion (both proton and alpha particles) velocity distribution functions, suggesting a fundamental role in the kinetic physical processes that mediate the sub-ion turbulence cascade.

Scope and limitations of ad hoc neural network reconstructions of solar wind parameters

Context.Solar wind properties are determined by the conditions of their solar source region and transport history. Solar wind parameters, such as proton speed, proton density, proton temperature, magnetic field strength, and the charge state composition of oxygen, are used as proxies to investigate the solar source region of the solar wind. The solar source region of the solar wind is relevant to both the interaction of this latter with the Earth’s magnetosphere and to our understanding of the underlying plasma processes, but the effect of the transport history of the wind is also important. The transport and conditions in the solar source region affect several solar wind parameters simultaneously. Therefore, the typically considered solar wind properties (e.g., proton density and oxygen charge-state composition) carry redundant information. Here, we are interested in exploring this redundancy.Aims.The observed redundancy could be caused by a set of hidden variables that determine the solar wind properties. We test this assumption by determining how well a (arbitrary, non-linear) function of four of the selected solar wind parameters can model the fifth solar wind parameter. If such a function provided a perfect model, then this solar wind parameter would be uniquely determined from hidden variables of the other four parameters and would therefore be redundant. If no reconstruction were possible, this parameter would be likely to contain information unique to the parameters evaluated here. In addition, isolating redundant or unique information contained in these properties guides requirements for in situ measurements and development of computer models. Sufficiently accurate measurements are necessary to understand the solar wind and its origin, to meaningfully classify solar wind types, and to predict space weather effects.Methods.We employed a neural network as a function approximator to model unknown, arbitrary, non-linear relations between the considered solar wind parameters. This approach is not designed to reconstruct the temporal structure of the observations. Instead a time-stable model is assumed and each point of measurement is treated separately. This approach is applied to solar wind data from the Advanced Composition Explorer (ACE). The neural network reconstructions are evaluated in comparison to observations, and the resulting reconstruction accuracies for each reconstructed solar wind parameter are compared while differentiating between different solar wind conditions (i.e., different solar wind types) and between different phases in the solar activity cycle. Therein, solar wind types are identified according to two solar-wind classification schemes based on proton plasma properties.Results.Within the limits defined by the measurement uncertainties, the proton density and proton temperature can be reconstructed well. Each parameter was evaluated with multiple criteria. Overall proton speed was the parameter with the most accurate reconstruction, while the oxygen charge-state ratio and magnetic field strength were most difficult to recover. We also analysed the results for different solar wind types separately and found that the reconstruction is most difficult for solar wind streams preceding and following stream interfaces.Conclusions.For all considered solar wind parameters, but in particular the proton density, proton temperature, and the oxygen charge-state ratio, parameter reconstruction is hindered by measurement uncertainties. The proton speed, while being one of the easiest to measure, also seems to carry the highest degree of redundancy with the combination of the four other solar wind parameters. Nevertheless, the reconstruction accuracy for the proton speed is limited by the large measurement uncertainties on the respective input parameters. The reconstruction accuracy of sector reversal plasma is noticeably lower than that of streamer belt or coronal hole plasma. We suspect that this is a result of the effect of stream interaction regions, which strongly influence the proton plasma properties and are typically assigned to sector reversal plasma. The fact that the oxygen charge-state ratio –a non-transport-affected property– is difficult to reconstruct may imply that recovering source-specific information from the transport-affected proton plasma properties is challenging. This underlines the importance of measuring the heavy ion charge-state composition.