Solar Wind Measurements Research Articles

Influence of Intermittency on the Energy Transfer Rate of Solar Wind Turbulence

The intermittency in the solar wind turbulence manifests itself in the anisotropic scaling due to the anisotropic spectral index and the intermittent level based on the extended P model. However, the influence of intermittency on the energy transfer rate remains unclear. Here we apply the partial variance of increments method to identify the intermittency for the magnetic field measurements in the fast solar wind from the Ulysses spacecraft. We distinguish the sampling direction using the angle θ RB between the local magnetic field and radial direction to study the anisotropy. We perform the multiorder structure function analyses and adopt the log-Poisson cascade model to describe the role of intermittency in the cascade process. We find that the anisotropy of the scaling becomes isotropic with a complete removal of intermittency. We compare explicitly the anisotropy of the energy transfer rate before and after removing the intermittency for the same interval for the first time. We find a distinct anisotropy with a cascade enhancement in the direction perpendicular to the local magnetic field. The removal of the intermittency greatly weakens the anisotropy by mainly reducing the perpendicular energy transfer rate. Our findings suggest that the intermittency effectively enhances the energy transfer rate, in particular in the perpendicular direction in the solar wind turbulence.

Using Tianwen-1 Differential One-way Range Signals to Probe Corotating Interaction Regions: Case Studies

The study reports the first detection of corotating interaction regions (CIRs) in the solar wind by the differential one-way range (DOR) signals transmitted by Tianwen-1. Differential phase delay is calculated for the DOR signals. Variations of the total electron content (TEC) along the signal path between Tianwen-1 and the ground stations are then derived from changes in the differential phase delay. Large TEC variations are found for 2021 February 11, 18, and 19 even after the influence from the Earth’s ionosphere has been removed. In situ solar wind measurements and the corresponding simulation results further show that the TEC variations are caused by the CIRs that passed through the signal path on these days. The study demonstrates that CIR structures can be probed using deep-space spacecraft range signals. Such measurements can be used to constrain global solar wind forecast models.

A system science methodology develops a new composite highly predictable index of magnetospheric activity for the community: the whole-Earth index E(1)

For community use, a new composite whole-Earth index E(1) and its matching composite solar wind driving function S(1) are derived. A system science methodology is used based on a time-dependent magnetospheric state vector and a solar wind state vector, with canonical correlation analysis (CCA) used to reduce the two state vectors to the two time-dependent scalars E(1)(t) and S(1)(t). The whole-Earth index E(1) is based on a diversity of measures via six diverse geomagnetic indices that will be readily available in the future: SML, SMU, Ap60, SYMH, ASYM, and PCC. The CCA-derived composite index has several advantages: 1) the new “canonical” geomagnetic index E(1) will provide a more powerful description of magnetospheric activity, a description of the collective behavior of the magnetosphere–ionosphere system. 2) The new index E(1) is much more accurately predictable from upstream solar wind measurements on Earth. 3) Indications are that the new canonical geomagnetic index E(1) will be accurately predictable even when as-yet-unseen extreme solar wind conditions occur. The composite solar wind driver S(1) can also be used as a universal driver function for individual geomagnetic indices or for magnetospheric particle populations. To familiarize the use of the new index E(1), its behavior is examined in different phases of the solar cycle, in different types of solar wind plasma, during high-speed stream-driven storms, during CME sheath-driven storms, and during superstorms. It is suggested that the definition of storms are the times when E(1) >1.

Precision electron measurements in the solar wind at 1 au from NASA’s Wind spacecraft

Context. The non-equilibrium characteristics of electron velocity distribution functions (eVDFs) in the solar wind are key to understanding the overall plasma thermodynamics as well as the origin of the solar wind. More generally, they are important in understanding heat conduction and energy transport in all weakly collisional plasmas. Solar wind electrons are not in local thermodynamic equilibrium, and their multicomponent eVDFs develop various non-thermal characteristics, such as velocity drifts in the proton frame and temperature anisotropies as well as suprathermal tails and heat fluxes along the local magnetic field direction. Aims. This work aims to characterize precisely and systematically the nonthermal characteristics of the eVDF in the solar wind at 1 au using data from the Wind spacecraft. Methods. We present a comprehensive statistical analysis of solar wind electrons at 1 au using the electron analyzers of the 3D-Plasma instrument on board Wind. This work uses a sophisticated algorithm developed to analyze and characterize separately the three populations – core, halo and strahl – of the eVDF up to super-halo energies (2 keV). This algorithm calibrates these electron measurements with independent electron parameters obtained from the quasi-thermal noise around the electron plasma frequency measured by Wind’s Thermal Noise Receiver (TNR). The code determines the respective set of total electron, core, halo, and strahl parameters through non-linear least-square fits to the measured eVDF, properly taking into account spacecraft charging and other instrumental effects, such as the incomplete sampling of the eVDF by particle detectors. Results. We use four years, approximately 280 000 independent measurements, of core, halo, and strahl electron parameters to investigate the statistical properties of these different populations in the slow and fast solar wind. We discuss the distributions of their respective densities, drift velocities, temperature, and temperature anisotropies as functions of solar wind speed. We also show distributions with solar wind speed of the total density, temperature, temperature anisotropy, and heat flux of the total eVDF, as well as those of the proton temperature, proton-to-electron temperature ratio, proton-β and electron-β. Intercorrelations between some of these parameters are also discussed. Conclusions. The present data set represents the largest, high-precision collection of electron measurements in the pristine solar wind at 1 au. It provides a new wealth of information on electron microphysics. Its large volume will enable future statistical studies of parameter combinations and their dependences under different plasma conditions.

Turbulence, Intermittency, and Cross-Scale Energy Transfer in an Interplanetary Coronal Mass Ejection

Solar wind measurements carried out by NASA’s Wind spacecraft before, during, and after the passing of an interplanetary coronal mass ejection (ICME), detected on 12 – 14 September 2014, have been used in order to examine several properties of magnetohydrodynamic (MHD) turbulence. Spectral indices and flatness scaling exponents of magnetic field, velocity, and proton density measurements were obtained, and provided a standard description of the characteristics of turbulence within different sub-regions of the ICME and its surroundings. This analysis was followed by the validation of the third-order moment scaling law for isotropic, incompressible MHD turbulence in the same sub-regions, which confirmed the fully developed nature of turbulence in the ICME plasma. The energy transfer rate was also estimated in each ICME sub-region and in the surrounding solar wind. An exceptionally high value was found within the ICME sheath, accompanied by enhanced intermittency, possibly related to the powerful energy injection associated with the arrival of the ICME.

Innovative technique for separating proton core, proton beam, and alpha particles in solar wind 3D velocity distribution functions

Context.The identification of proton core, proton beam, and alpha particles in solar wind ion measurements is usually performed by applying specific fitting procedures to the particle energy spectra. In many cases, this turns out to be a challenging task due to the overlapping of the curves.Aims.We propose an alternative approach based on the statistical technique of clustering, a standard tool in many data-driven and machine learning applications.Methods.We developed a procedure that adapts clustering to the analysis of solar wind distribution functions. We first tested the method on a synthetic data set and then applied it to a time series of solar wind data.Results.The moments obtained for the different particle populations are in good agreement with the official data set and with the statistical studies available in the literature.Conclusions.Our method is shown to be a very promising technique that can be combined with the traditional fitting algorithms in working out difficult cases that involve the identification of particle species in solar wind measurements.

Observations of Quiescent Solar Wind Regions with Near-f ce Wave Activity

In situ measurements in the near-Sun solar wind from the Parker Solar Probe have revealed the existence of quiescent solar wind regions: extended regions of solar wind with low-amplitude turbulent magnetic field fluctuations compared to adjacent regions. Identified through the study of harmonic waves near the electron cyclotron frequency (f ce), these quiescent regions are shown to host a variety of plasma waves. The near-f ce harmonic waves are observed exclusively in quiescent regions, and as such, they can be used as markers for quiescent regions. A blob-finding algorithm is applied to data from Encounters 1–6 in order to identify near-f ce harmonic wave intervals and thereby locate quiescent regions. We carry out a superposed epoch analysis on the identified quiescent regions, and compare their bulk solar wind properties with adjacent regions of solar wind. Quiescent regions are found to contain relatively weak magnetic field variation and are entirely devoid of magnetic switchbacks. In the quiescent solar wind, the magnetic field closely follows the Parker spiral, while adjacent regions prefer more radial orientations, providing a clear picture of the magnetic geometry of these regions. Quiescent regions show minimal differences in multiple particle plasma parameters relative to the non-quiescent solar wind. The quiescent solar wind regions, studied throughout this work, are thought to represent the underlying solar wind, through which Alfvénic fluctuations propagate. Quantifying the properties of these regions may help to understand the formation/origin of the solar wind, and furthermore, to constrain the role that low-frequency Alfvén waves play in the regulation of solar wind temperature.

Forecasting changes of the magnetic field in the United Kingdom from L1 Lagrange solar wind measurements

Extreme space weather events can have large impacts on ground-based infrastructure important to technology-based societies. Machine learning techniques based on interplanetary observations have proven successful as a tool for forecasting global geomagnetic indices, however, few studies have examined local ground magnetic field perturbations. Nowcast and forecast models which predict the magnitude of the horizontal geomagnetic field, |BH|, and its time derivative, dBHdt, at ground level would be valuable for assessing the potential space weather hazard. We attempt to predict the variation of the magnetic field at the three United Kingdom observatories (Eskdalemuir, Hartland and Lerwick) driven by L1 solar wind parameters. The horizontal magnetic field component and its time derivative are predicted from solar wind plasma and interplanetary magnetic field observations using Long Short-Term Memory (LSTM) networks and hybrid Convolutional Neural Network-LSTM models. A 5-fold grid search cross-validation is used for tuning the hyperparameters in each model. Forecasts were made with 5, 15 and 30-min lead times. Models were trained and validated with geomagnetic storm-only data from 1997 to 2016; their outputs were evaluated with the 7–9th September 2017 storms. The forecast models are only able to predict the directly driven parts of geomagnetic storms (not the substorms) and LSTM models generally perform best. We find the |BH| 15- and 30-min forecasts at Lerwick and Eskdalemuir have some predictive power. The 5-min |BH| forecast as well as all the dBHdt models for Eskdalemuir and all the Hartland models were found to have little or no predictive power. This suggests that the machine learning models have better forecasting power at higher latitude (closer to the auroral zones), where the ground magnetic variation field is larger and during storm onset, which is directly driven by changes in the solar wind.

Solar Cycle Variability in Coronal Holes and Their Effects on Solar Wind Sources

AbstractVarious upstream spacecraft have now observed the solar wind conditions affecting the Earth since the 1970s, covering over four solar activity cycles. These measurements provide a long term picture of the related patterns in large scale incident plasma and magnetic field parameters of interest for both interpreting cycles in geospace effects, and understanding how the Sun controls our space environment. This paper focuses on the latter, in part to provide context at the start of the new solar cycle 25, and toward establishing connections between the 1 AU ecliptic solar wind behavior and the unprecedented near‐Sun measurements of heliospheric features on Parker Solar Probe and Solar Orbiter. Magnetograph data‐based potential field source surface models provide a basic picture of how the solar wind sources, including those that give rise to corotating high speed streams in the ecliptic, have changed since the beginning of the record of regular solar wind measurements. In particular, they suggest the contributions from low to mid latitude coronal holes dominate the observed cycles (21–24), especially the weaker cycles (23 and 24), impacting upstream measurement interpretations, modeling, and forecasting considerations. For example, recurring features are affected by differential rotation of the Sun's surface field, which through its effects on the corona, can produce solar wind streams reappearing at ∼25–30 days intervals instead of at the canonical 27.3 days Carrington rotation rate. In addition, the conditions that lead to the corotating stream structure that can dominate periods of low solar activity are seen to be more complicated than suggested by the simple concepts of early studies. The overall results illustrate where in the cycles well‐defined, long‐lived large scale structures can be expected, and the advantages of synoptic displays of 1 AU solar wind parameters for anticipating timings of recurring features.

Peculiarities of the Heliospheric State and the Solar-Wind/Magnetosphere Coupling in the Era of Weakened Solar Activity

Based on the data of the solar wind (SW) measurements of the OMNI database for the period 1976–2019, we investigate the behavior of SW types, as well as plasma and interplanetary magnetic field (IMF) parameters, for 21–24 solar cycles (SCs). Our analysis shows that with the beginning of the period of low solar activity (SC 23), the number of all types of disturbed events in the interplanetary medium decreased, but the proportion of magnetic storms initiated by CIR increased. In addition, a change in the nature of SW interaction with the magnetosphere could occur due to a decrease in the density, temperature, and IMF of solar wind.

Acceleration of Solar Wind Suprathermal Electrons at the Earth’s Bow Shock

We present a statistical study of the in situ acceleration of solar wind suprathermal electrons at the Earth’s bow shock, utilizing the Wind measurements in ambient solar wind and MMS1 measurements around the bow shock from 2015 September to 2017 December. All the selected 74 cases show significant suprathermal electron acceleration at the bow shock. The observed power-law indexes of accelerated electron energy spectra are significantly larger than the first-order Fermi acceleration prediction and the flux enhancement ratio peaks near a 90° pitch angle, suggesting that the shock drift acceleration (SDA) process plays a crucial role in accelerating suprathermal electrons at the bow shock. According to the observed electron spectral characteristics, the 74 cases can be classified into Types 1, 2, 3 and 4. The electron acceleration efficiency roughly increases from Type 1 to Type 4. For the Type 4 cases with strong electron acceleration, the shocked suprathermal electrons show a double-power-law energy spectrum bending downwards at a break near ∼65 keV with a low-energy spectral index of ∼3.1 and high-energy index of ∼7.6. The observed break energy is comparable to a critical electron energy with its cross-shock gyrodiameter equal to the shock’s ramp thickness D ramp. At energies below (above) , the accelerated electrons can be effectively confined into (can easily escape from) the SDA process with a roughly energy-independent (energy-decreasing) drift time and a probably conserved (nonadiabatically reduced) magnetic moment, since their gyrodiameter is less (greater) than D ramp. Therefore, such an SDA process could produce the observed double-power-law spectrum bending downwards at a break energy that is associated with D ramp.

Regression Bias in Using Solar Wind Measurements

Simultaneous solar wind measurements from the solar wind monitors, WIND and ACE, differ due to the spatial and temporal structure of the solar wind. Correlation studies that use these measurements as input may infer an incorrect correlation due to uncertainties arising from this spatial and temporal structure, especially at extreme and rare solar wind values. In particular, regression analysis will lead to a regression function whose slope is biased towards the mean value of the measurement parameter. This article demonstrates this regression bias by comparing simultaneous ACE and WIND solar wind measurements. A non-linear regression analysis between them leads to a perception of underestimation of extreme values of one measurement on average over the other. Using numerical experiments, we show that popular regression analysis techniques such as linear least-squares, orthogonal least-squares, and non-linear regression are not immune to this bias. Hence while using solar wind parameters as an independent variable in a correlation or regression analysis, random uncertainty in the independent variable can create unintended biases in the response of the dependent variable. More generally, the regression to the mean effect can impact both event-based, statistical studies of magnetospheric response to solar wind forcing.

Miniature ion analyzer for applications in space weather monitoring

This article presents the results of development and testing of a simple and compact ion energy-mass analyzer. PICA (Plasma Ion Compact Analyzer) is designed as a solution for solar wind measurements, polar proton precipitation monitoring and as a miniature solution for various space plasma experiments. We introduce general ideas that lead to the development of a simple and low-cost instrument and review several operating plasma instruments. After we address our previous results in modeling a possible scheme of the instrument and indicate improvements based on the results of previous research. We introduce the details of computer modeling of an improved for space application model, the results of prototype tests and flight configuration unit preformance. During the tests we checked the energy and mass resolutions of the laboratory prototype (ΔE/E = 4% M/ΔM = 4–8). All parameters were checked for the energy range of the upper boundary of 5 keV owing to the limitations of our equipment. The analytical characteristics of the instrument allow for distinguishing the fluxes of protons and alpha particles and monitoring the main parameters of the solar wind. The flight configuration of the instrument and can be placed on 3U CubeSATs.

Global Geomagnetic Perturbation Forecasting Using Deep Learning

AbstractGeomagnetically Induced Currents (GICs) arise from spatio‐temporal changes to Earth's magnetic field, which arise from the interaction of the solar wind with Earth's magnetosphere, and drive catastrophic destruction to our technologically dependent society. Hence, computational models to forecast GICs globally with large forecast horizon, high spatial resolution and temporal cadence are of increasing importance to perform prompt necessary mitigation. Since GIC data is proprietary, the time variability of the horizontal component of the magnetic field perturbation (dB/dt) is used as a proxy for GICs. In this work, we develop a fast, global dB/dt forecasting model, which forecasts 30 min into the future using only solar wind measurements as input. The model summarizes 2 hr of solar wind measurement using a Gated Recurrent Unit and generates forecasts of coefficients that are folded with a spherical harmonic basis to enable global forecasts. When deployed, our model produces results in under a second, and generates global forecasts for horizontal magnetic perturbation components at 1 min cadence. We evaluate our model across models in literature for two specific storms of 5 August 2011 and 17 March 2015, while having a self‐consistent benchmark model set. Our model outperforms, or has consistent performance with state‐of‐the‐practice high time cadence local and low time cadence global models, while also outperforming/having comparable performance with the benchmark models. Such quick inferences at high temporal cadence and arbitrary spatial resolutions may ultimately enable accurate forewarning of dB/dt for any place on Earth, resulting in precautionary measures to be taken in an informed manner.

Influence of Off‐Sun‐Earth Line Distance on the Accuracy of L1 Solar Wind Monitoring

AbstractUpstream solar wind measurements from near the L1 Lagrangian point are commonly used to investigate solar wind‐magnetosphere coupling. The off‐Sun‐Earth line distance of such solar wind monitors can be large, up to 100 RE. We investigate how the correlation between measurements of the interplanetary magnetic field and associated ionospheric responses deteriorates as the off‐Sun‐Earth line distance increases. Specifically, we use the magnitude and polarity of the dayside region 0 field‐aligned currents (R0 FACs) as a measure of interplanetary magnetic field (IMF) BY‐associated magnetic tension effects on newly‐reconnected field lines, related to the Svalgaard‐Mansurov effect. The R0 FACs are derived from Advanced Magnetosphere and Planetary Electrodynamics Response Experiment measurements by a principal component analysis, for the years 2010–2016. We perform cross‐correlation analyses between time‐series of IMF BY, measured by the Wind spacecraft and propagated to the nose of the bow shock by the OMNI technique, and these R0 FAC measurements. Typically, in the summer hemisphere, cross‐correlation coefficients between 0.6 and 0.9 are found. However, there is a reduction of order 0.1–0.15 in correlation coefficient between periods when Wind is close to (within 45 RE) and distant from (beyond 70 RE) the Sun‐Earth line. We find a time‐lag of around 17 min between predictions of the arrival of IMF features at the bow shock and their effect in the ionosphere, irrespective of the location of Wind.

Near-Earth Sub-Alfvénic Solar Winds: Interplanetary Origins and Geomagnetic Impacts

Abstract The near-Earth solar wind is in general super-Alfvénic and supermagnetosonic. Using all available near-Earth solar wind measurements between 1973 and 2020, we identified 30 intervals with sub-Alfvénic solar winds. The majority (83%) of the events occurred within interplanetary coronal mass ejection magnetic clouds (MCs)/driver gases. These MC sub-Alfvénic events are characterized by exceptionally low plasma densities (N sw) of ∼0.04–1.20 cm−3, low temperatures (T sw) of ∼0.08 × 105 K to 12.46 × 105 K, enhanced magnetic field intensities (B 0) of ∼8.3–53.9 nT, and speeds (V sw) of ∼328–949 km s−1. The resultant high Alfvén wave speeds (V A) ranged from ∼410 to 1471 km s−1. This is consistent with a mechanism of the MC expansions as they propagate radially outward, causing small pockets of sub-Alfvénic wind regions within the MCs. The remainder of the sub-Alfvénic intervals (17%) occurred within the extreme trailing portions of solar wind high-speed streams (HSSs). These HSS sub-Alfvénic winds had low N sw of ∼0.04–0.97 cm−3, low T sw of ∼0.06 × 105 K to 0.46 × 105 K, B 0 of ∼6.3–18.2 nT, V sw of ∼234–388 km s−1, and a V A range of ∼364–626 km s−1. This is consistent with a mechanism of solar wind super-radial expansions in the trailing HSS regions. During sub-Alfvénic solar wind intervals, Earth's bow shock nose exhibited rapid evanescence, and the estimated geocentric magnetopause distance increased by ∼33%–86%. The inner magnetosphere was more or less unaffected by the sub-Alfvénic solar winds. No significant impact was observed in the outer radiation belt relativistic electrons, and no geomagnetic storms or substorms were triggered during the sub-Alfvénic solar wind events.

Tianwen-1 MINPA observations in the solar wind

The Mars Ion and Neutral Particle Analyzer (MINPA) is one of the three scientific instruments onboard the Tianwen-1 orbiter to investigate the Martian space environment. During Tianwen-1’s transfer orbit to Mars, the MINPA was switched on to measure the solar wind ions. Here, we present the first results of the MINPA observations in the solar wind. During cruise, nearly half of the MINPA ion field-of-view (FOV) was blocked by the lander capsule; thus only the solar-wind ions with azimuthal speeds pointing towards the unblocked FOV sectors could be detected. We perform a detailed comparison of the MINPA’s solar wind observations with data from Earth-based missions when MINPA reached its count-rate peak, finding a general consistency of the ion moments between them. The blocking effect due to the lander is evaluated quantitatively under varying solar-wind velocity conditions. Despite the blocking effect, the MINPA’s solar wind measurements during the transfer orbit suggest a good performance.

Validation of the use of THEMIS-B and THEMIS-C as a near-Earth solar wind monitor

Two THEMIS (Time History of Events and Macroscale Interactions during Substorms) spacecraft, B and C, began orbiting the Moon in 2011 and have since provided routine measurements of the plasma conditions in the lunar orbit. In this study, we systematically compare these measurements in near-Earth space with solar wind measurements obtained from the Lagrangian 1 (L1) point and propagated to the Earth, including measurements in the OMNI database and from the Wind spacecraft. A statistical comparison between THEMIS data and data from the OMNI database from September 2011 to December 2017 showed that the <em>Y</em> and <em>Z</em> components of the magnetic field and the flow speed are generally consistent between the two data sets. The ion number density and the dynamic pressure measured by THEMIS in near-Earth space are lower than those in the OMNI database, suggesting possible variation in the solar wind environment while propagating from the L1 point to near-Earth space. We further show two examples in which near-Earth solar wind measurements are applied in calculating the magnetopause location and in quantifying the magnetic field response to interplanetary shocks. Both examples suggest that using solar wind data from near-Earth space achieves better results than using solar wind data from the L1 point. These results provide validation of THEMIS-B and THEMIS-C as an alternative monitor of the near-Earth solar wind environment.

Storm time neutral density assimilation in the thermosphere ionosphere with TIDA

To improve Thermosphere–Ionosphere modeling during disturbed conditions, data assimilation schemes that can account for the large and fast-moving gradients moving through the modeled domain are necessary. We argue that this requires a physics based background model with a non-stationary covariance. An added benefit of using physics-based models would be improved forecasting capability over largely persistence-based forecasts of empirical models. As a reference implementation, we have developed an ensemble Kalman Filter (enKF) software called Thermosphere Ionosphere Data Assimilation (TIDA) using the physics-based Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model as the background. In this paper, we present detailed results from experiments during the 2003 Halloween Storm, 27–31 October 2003, under very disturbed (Kp = 9) conditions while assimilating GRACE-A and B, and CHAMP neutral density measurements. TIDA simulates this disturbed period without using the L1 solar wind measurements, which were contaminated by solar energetic protons, by estimating the model drivers from the density measurements. We also briefly present statistical results for two additional storms: September 27 – October 2, 2002, and July 26 – 30, 2004, to show that the improvement in assimilated neutral density specification is not an artifact of the corrupted forcing observations during the 2003 Halloween Storm. By showing statistical results from assimilating one satellite at a time, we show that TIDA produces a coherent global specification for neutral density throughout the storm – a critical capability in calculating satellite drag and debris collision avoidance for space traffic management.

Magnetic and Velocity Fluctuations in the Near-Sun Region from 0.1−0.3 au Observed by Parker Solar Probe

Abstract The fluctuations observed in the slow solar wind at 1 au by the WIND spacecraft are shown by recent studies to consist of mainly magnetic-field directional turning and magnetic-velocity alignment structure (MVAS). How these structures are created has been a question because the nature of the fluctuations in the near-Sun region remains unknown. Here, we present an analysis of the measurements in the slow solar wind from 0.1−0.3 au by Parker Solar Probe during its first six orbits. We present the distributions in the C vb ′ – σ r plane of both the occurrence and average amplitudes of the fluctuations, including the magnetic field, the velocity, and the Elsässer variables, where C vb ′ is the correlation coefficient between the magnetic and velocity fluctuations multiplied by the opposite sign of the radial component of the mean magnetic field and σ r is the normalized residual energy. We find that the dominant composition is the outward-propagating Alfvénic fluctuations. We find Alfvénic fluctuations with C vb ′ &gt; 0.95 , in which the amplitudes of z + reach 60 km s−1 and those of z − are close to the observational uncertainty. We also find a region with high C vb ′ and moderate minus σ r in which the fluctuations are considered MVAS being magnetic dominated with the amplitude of magnetic fluctuations reaching 60 km s−1. We provide empirical relations between the velocity fluctuation amplitude and C vb ′ . The comparison between these results and those observed at 1 au may provide some clues as to the nature and evolution of the fluctuations.