Solar Wind Data Research Articles

Formation of Multiple Current Sheets in the Heliospheric Plasma Sheet

When spacecraft cross the heliospheric plasma sheet (HPS) that separates large-scale magnetic sectors of opposite directions in the solar wind, multiple rapid fluctuations in the sign of the magnetic radial component are often observed. These fluctuations indicate the change of the sign of the azimuth electric current density within the HPS. Possible mechanisms of formation of the multilayered current structure of the HPS are proposed. Within the context of a stationary magnetohydrodynamic solar wind model, we test one of the most popular hypotheses regarding an extension of multiple current sheets from the streamer belt oriented along the neutral line of the solar magnetic field into the solar wind. Properties of self-consistent distributions of the solar wind key characteristics are investigated as function of the fine structure of streamers. The results show that both single and multiple streamers can be the source of the set of a multilayered structure with alternating azimuthal currents. The significance of the results for the interpretation of solar wind data is discussed.

Time-scale dependence of solar wind-based regression models of ionospheric electrodynamics

The solar wind influence on geospace can be described as the sum of a directly driven component, or dayside reconnection, and an unloading component, associated with the release of magnetic energy via nightside reconnection. The two processes are poorly correlated on short time scales, but exactly equal when averaged over long time windows. Because of this peculiar property, regression models of ionospheric electrodynamics that are based on solar wind data are time scale specific: Models derived from 1 min resolution data will be different from models derived from hourly, daily, or monthly data. We explain and quantify this effect on simple linear regression models of various geomagnetic indices. We also derive a time scale-dependent correction factor that can be used with the Average Magnetic field and Polar current System model. Finally, we show how absolute estimates of the nightside reconnection rate can be calculated from solar wind measurements and geomagnetic indices.

Mars Express Observations of Cold Plasma Structures in the Martian Magnetotail

AbstractWe present observations from five Mars Express (MEX) orbits in September 2016 while the spacecraft passed through the Martian induced magnetotail at altitudes up to 3,500 km. On these orbits, the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) instrument was operated in Active Ionospheric Sounding (AIS) mode at much higher altitude than normal, acting as a local sounder and detecting cold plasma structures in this region. In this paper we combine MARSIS tail measurements with solar wind data from the Solar Wind Ion Analyzer (SWIA) instrument and the Magnetometer (MAG) from Mars Atmosphere and Volatile EvolutioN (MAVEN) in order to investigate possible factors affecting plasma transport from the dayside and through the terminator. MARSIS observed structured cold ionospheric plasma along its trajectory, at all altitudes and solar zenith angles (SZAs). Isolated regions of cold plasma were also observed on each orbit as the spacecraft crossed the terminator, even at high altitudes. We conclude that the variability of plasma seen in the tail results from a multifactorial transport process, the development of which cannot be attributed to a sole parameter influencing it, despite the availability of simultaneous high quality solar wind measurements.

Uncertainty Estimates of Solar Wind Prediction Using HMI Photospheric Vector and Spatial Standard Deviation Synoptic Maps

Current solar wind prediction is based on the Wang & Sheeley empirical relationship between the solar wind speed observed at 1 AU and the rate of magnetic flux tube expansion (FTE) between the photosphere and the inner corona, where FTE is computed by coronal models that take the photospheric flux density synoptic maps as their inner boundary conditions to extrapolate the photospheric magnetic fields to deduce the coronal and the heliospheric magnetic field configuration. Since these synoptic maps are among the most widely-used of all solar magnetic data products, the uncertainties in the model predictions that are caused by the uncertainties in the synoptic maps are worthy of study. However, such an estimate related to synoptic map construction was not available until Bertello et al. (Solar Physics, 289, 2014) obtained the spatial standard deviation synoptic maps; 98 Monte-Carlo realizations of the spatial standard deviation maps for each photospheric synoptic maps. In this paper, we present an estimate of uncertainties in the solar wind speed predicted at 1 AU by the CSSS model due to the uncertainties in the photospheric synoptic maps. We also present a comparison of the coronal hole locations predicted by the models with the STEREO/SECCHI EUV synoptic maps. In order to quantify the extent of the uncertainties involved, we compared the predicted speeds with the OMNI solar wind data during the same period (taking the solar wind transit time into account) and obtained the root mean square error between them. To illustrate the significance of the uncertainty estimate in the solar wind prediction, we carried out the analysis for three Carrington rotations, CR 2102, CR 2137 and CR 2160 at different phases of the solar cycle. The uncertainty estimate is critical information necessary for the current and future efforts of improving the solar wind prediction accuracies.

Visualizing and Interpreting Unsupervised Solar Wind Classifications

One of the goals of machine learning is to eliminate tedious and arduous repetitive work. The manual and semi-automatic classification of millions of hours of solar wind data from multiple missions can be replaced by automatic algorithms that can discover, in mountains of multi-dimensional data, the real differences in the solar wind properties. In this paper we present how unsupervised clustering techniques can be used to segregate different types of solar wind. We propose the use of advanced data reduction methods to pre-process the data, and we introduce the use of Self-Organizing Maps to visualize and interpret 14 years of ACE data. Finally, we show how these techniques can potentially be used to uncover hidden information, and how they compare with previous manual and automatic categorizations.

Parker Solar Probe observations of suprathermal electron flux enhancements originating from Coronal Hole boundaries

ABSTRACT Reconnection between pairs of solar magnetic flux elements, one open and the other a closed loop, is theorized to be a crucial process for both maintaining the structure of the corona and producing the solar wind. This ‘interchange reconnection’ is expected to be particularly active at the open-closed boundaries of coronal holes (CHs). Previous analysis of solar wind data at 1 au indicated that peaks in the flux of suprathermal electrons at slow–fast stream interfaces may arise from magnetic connection to the CH boundary, rather than dynamic effects such as compression. Further, offsets between the peak and stream interface locations are suggested to be the result of interchange reconnection at the source. As a preliminary test of these suggestions, we analyse two solar wind streams observed during the first Parker Solar Probe (PSP) perihelion encounter, each associated with equatorial CH boundaries (one leading and one trailing with respect to rotation). Each stream features a peak in suprathermal electron flux, the locations and associated plasma properties of which are indicative of a solar origin, in agreement with previous suggestions from 1 au observations. Discrepancies between locations of the flux peaks and other features suggest that these peaks may too be shifted by source region interchange reconnection. Our interpretation of each event is compatible with a global pattern of open flux transport, although random footpoint motions or other explanations remain feasible. These exploratory results highlight future opportunities for statistical studies regarding interchange reconnection and flux transport at CH boundaries with modern near-Sun missions.

Saturn's Nightside Dynamics During Cassini's F Ring and Proximal Orbits: Response to Solar Wind and Planetary Period Oscillation Modulations

AbstractWe examine the final 44 orbits of the Cassini spacecraft traversing the midnight sector of Saturn's magnetosphere to distances of ~21 Saturn radii, to investigate responses to heliospheric conditions inferred from model solar wind and Cassini galactic cosmic ray flux data. Clear storm responses to anticipated magnetospheric compressions are observed in magnetic field and energetic particle data, together with Saturn kilometric radiation (SKR), auroral hiss, and ultraviolet auroral emissions. Most compression events are associated with corotating interaction regions, producing ~2–3.5 day intervals of magnetospheric activity that are recurrent with the ~26 day solar rotation period (one or two such events per rotation), though one on the final pass is related to a nonrecurrent interplanetary shock possibly associated with an earlier X‐class solar flare. The response to compressions is modulated by the concurrent relative phasing of the northern and southern planetary period oscillation (PPO) systems, with long (>1 planetary rotation) SKR low‐frequency extension (LFE) intervals associated with strong field‐aligned coupling currents being favored when the two PPO systems act together to thin and thicken the tail plasma sheet during each PPO cycle. LFE onsets/intensifications are then favored at thin plasma sheet phases most unstable to reconnection, producing energetic nightside particle injections and poleward contractions of dawn‐brightened auroras. Correspondingly, solar rotation recurrent intervals of magnetospheric quiet conditions also occur with weak energetic particle fluxes and auroral emissions, associated with extended solar wind rarefactions. Overall, the results emphasize how strongly activity in Saturn's magnetosphere is modulated by concurrent heliospheric conditions.

Large-density (>50 cm−3) heliospheric plasma sheets recorded by the Wind spacecraft between 1995 and 2017

A survey of previous studies of the heliospheric plasma sheet (HPS) suggests a bimodal distribution for the occurrence of the HPS peak plasma density. While the majority of HPS events have a peak density smaller than ∼30 cm−3, there is evidence that large density (>50 cm−3) HPS events can exist. A bimodal distribution would suggest a two-source scenario for the HPS observed at 1 AU. In this study we focus on large density HPS events. We survey the solar wind data acquired from the Wind spacecraft between 1995 and 2017 and identify 108 large-density HPS events with a distribution peak at 55 cm−3, confirming the bimodal distribution. We also find that 80 (74%) of these large-density HPS events are associated with interplanetary shocks. The yearly occurrence of these large-density HPS events nearly follows the yearly occurrence of interplanetary shock. This result suggests that large-density HPS events are likely caused by compression of interplanetary shocks within 1 AU.

The Value of CME Arrival Time Forecasts for Space Weather Mitigation

AbstractSevere geomagnetic storms are driven by the coronal mass ejections (CMEs). Consequently, there has been a great deal of focus on predicting if and when a CME will arrive in near‐Earth space. However, it is useful to step back and ask, “How valuable is this information, in isolation, for making decisions to mitigate against the adverse effects of space weather?” While all severe geomagnetic storms are triggered by CMEs, not all CMEs trigger severe storms. Thus, even perfect knowledge of CME arrival time will provide “actionable” forecast information only in operational situations where false alarms can be tolerated. Of course, any CME transit model used to predict CME arrival time must also produce an estimate of CME speed at Earth. This can help discriminate between geoeffective and nongeoeffective CMEs, reducing false alarms and expanding the range of operational scenarios under which a forecast provides value. Thus, from an end‐user perspective, CME arrival speed should form part of the standard metric by which CME transit models are evaluated. Looking to the future, even coarse information about the CME magnetic properties would likely provide even greater forecast value. These points are illustrated by a simple analysis of solar wind data.

Interplay between turbulence and waves: large-scale helical transfer, and small-scale dissipation and mixing in fluid and Hall-MHD turbulence

Novel features of turbulent flows have been analyzed recently, for example: (1) the possibility of an ideal invariant, such as the energy, to be transferred both to the small scales and to the large scales, in each case with a constant flux; (2) the existence of non-Gaussian wings in Probability Distribution Functions of kinetic, magnetic, and temperature fluctuations, together with their gradients, thus displaying large-scale as well as small-scale intermittency; and (3) the linear dependence on the control parameter of the effective dissipation in turbulence when non-linear eddies and waves interact. We shall briefly review these results with examples stemming from Solar Wind data, the atmosphere and the ocean with either magnetic fields, stratification, and/or rotation. In a second part, we shall examine numerically the inverse cascades of magnetic and of generalized helicity for Hall-MHD in the presence of forcing. These helical invariants in the ideal non-dissipative case involve various cross-correlations between the velocity and vorticity, the magnetic field, and the magnetic potential. For an ion inertial length larger than the forcing scale, the effect of the waves is significant. It leads to an exponential attenuation of the inverse cascade to large scales, since, through the velocity and vorticity, small scales play an increasing dynamical role for a strong Hall current.

Analyses of residual accelerations for TianQin based on the global MHD simulation

TianQin is a proposed space-based gravitational wave observatory. It is designed to detect the gravitational wave signals in the frequency range of 0.1 mHz–1 Hz. At a geocentric distance of 105 km, the plasma in the Earth magnetosphere will contribute as the main source of environmental noises. Here, we analyze the acceleration noises that are caused by the magnetic field of space plasma for the test mass of TianQin. The real solar wind data observed by the Advanced Composition Explorer are taken as the input of the magnetohydrodynamic simulation. The Space Weather Modeling Framework is used to simulate the global magnetosphere of the Earth, from which we obtain the plasma and magnetic field parameters on the detector’s orbits at φs = 0°, 30°, 60° and 90°, where φs is the acute angle between the line that joins the Sun and the Earth and the projection of the normal of the detector’s plane on the ecliptic plane. We calculate the time series of the residual accelerations and the corresponding amplitude spectral densities on these orbit configurations. We find that the residual acceleration produced by the interaction between the TM’s magnetic moment induced by the space magnetic field and the spacecraft magnetic field (aM1) is the dominant term, which can approach 10−15 m s–2 Hz–1/2 at f ≈ 0.2 mHz for the nominal values of the magnetic susceptibility (χm = 10−5) and the magnetic shielding factor (ξm = 10) of the test mass. The ratios between the amplitude spectral density of the acceleration noise caused by the space magnetic field and the preliminary goal of the inertial sensor are 0.38 and 0.08 at 1 mHz and 10 mHz, respectively. We discuss the further reduction of this acceleration noise by decreasing χm and/or increasing ξm in the future instrumentation development for TianQin.

Kinetic magnetic holes in the high-speed streams during solar cycle 23

One of the important elements of solar wind turbulence is the so-called “magnetic holes” (MHs), sharp temporary drops in the intensity of the interplanetary magnetic field. Using solar wind data from the ACE and Wind spacecraft, distribution and evolution of kinetic-type MHs are investigated. In particular, in the first part of this study, we examine fifteen high-speed Alfvénic streams with a high helicity value, which are mainly CIR streams. The period from 1997 to 2011 is covered, with one stream per year selected. A total of 207 kinetic MHs with duration of 3–129 ​s were detected in 15 high-speed streams with a total duration of 1004 ​h. The occurrence rate of holes is about 5 events per day (0.2 per hour), which far exceeds the average frequency of MH observation in the slow wind. The median value of the MH depth is 1.52 ​nT, the maximum is 22.5 ​nT. The occurrence rate of holes monotonically increases with decreasing their duration. During the solar cycle, the probability of MH observation increases at minimum and during the early growth phase (1997–1998 and 2008–2010), reaching 0.32 events per hour. In the second part, the dynamics of MHs during their convective transfer by the solar wind was tracked. We used 1-s ACE and Wind magnetometer data during the movement of the Wind SC from the magnetosphere to the libration point L1 against the background of the passage of five high-speed streams. We studied the evolution of MHs observed consistently first on the ACE SC, and then, as a result of their transfer by the wind stream, to the Wind SC. Fifteen MHs were selected whose transfer time between satellites deviated from the calculated one by no more than 15%. Of these, 9 ​MHs are of the linear type, 5 ​MHs are of rotational type, and one more was observed against the background of the chaotic behavior of the magnetic field components. The evolution of the MHs during their convective transfer was diverse: from the full shape retention to its significant change both towards the deepening of the hole and the steepening of its front, and towards its significant spreading. The possible modulation effect of MHs on wave phenomena in the magnetosphere is discussed.

Inherent Length Scales of Periodic Mesoscale Density Structures in the Solar Wind Over Two Solar Cycles

AbstractIt is now well established through multiple event and statistical studies that the solar wind at 1 AU contains contains periodic, mesoscale (L ∼ 100–1,000 Mm) structures in the proton density. Composition variations observed within these structures and remote sensing observations of similar structures in the young solar wind indicate that at least some of these periodic structures originate in the solar atmosphere as a part of solar wind formation. Viall et al. (2008, https://doi.org/10.1029/2007JA012881) analyzed 11 years of data from the Wind spacecraft near L1 and demonstrated a recurrence to the observed length scales of periodic structures in the solar wind proton density. In the time since that study, Wind has collected 14 additional years of solar wind data, new moment analysis of the Wind SWE data is available, and new methods for spectral background approximation have been developed. In this study, we analyze 25 years of Wind data collected near L1 and produce occurrence distributions of statistically significant periodic length scales in proton density. The results significantly expand upon the Viall et al. (2008, https://doi.org/10.1029/2007JA012881) study and further show a possible relation of the length scales to solar “termination” events.

Magnetometer in-flight offset accuracy for the BepiColombo spacecraft

Abstract. Recently the two-spacecraft mission BepiColombo launched to explore the plasma and magnetic field environment of Mercury. Both spacecraft, the Mercury Planetary Orbiter (MPO) and the Mercury Magnetospheric Orbiter (MMO, also referred to as Mio), are equipped with fluxgate magnetometers, which have proven to be well-suited to measure the magnetic field in space with high precision. Nevertheless, accurate magnetic field measurements require proper in-flight calibration. In particular the magnetometer offset, which relates relative fluxgate readings into an absolute value, needs to be determined with high accuracy. Usually, the offsets are evaluated from observations of Alfvénic fluctuations in the pristine solar wind, if those are available. An alternative offset determination method, which is based on the observation of highly compressional fluctuations instead of incompressible Alfvénic fluctuations, is the so-called mirror mode technique. To evaluate the method performance in the Hermean environment, we analyze four years of MESSENGER (MErcury Surface, Space ENvironment, GEophysics and Ranging) magnetometer data, which are calibrated by the Alfvénic fluctuation method, and compare it with the accuracy and error of the offsets determined by the mirror mode method in different plasma environments around Mercury. We show that the mirror mode method yields the same offset estimates and thereby confirms its applicability. Furthermore, we evaluate the spacecraft observation time within different regions necessary to obtain reliable offset estimates. Although the lowest percentage of strong compressional fluctuations are observed in the solar wind, this region is most suitable for an accurate offset determination with the mirror mode method. 132 h of solar wind data are sufficient to determine the offset to within 0.5 nT, while thousands of hours are necessary to reach this accuracy in the magnetosheath or within the magnetosphere. We conclude that in the solar wind the mirror mode method might be a good complementary approach to the Alfvénic fluctuation method to determine the (spin-axis) offset of the Mio magnetometer.

Forecasting GOES 15 >2 MeV Electron Fluxes From Solar Wind Data and Geomagnetic Indices

AbstractThe flux of > 2 MeV electrons at geosynchronous orbit is used by space weather forecasters as a key indicator of enhanced risk of damage to spacecraft in low, medium, or geosynchronous Earth orbits. We present a methodology that uses the amount of time a single input data set (solar wind data or geomagnetic indices) exceeds a given threshold to produce deterministic and probabilistic forecasts of the >2 MeV flux at GEO exceeding 1,000 or 10,000 cm−2 s−1 sr−1 within up to 10 days. By comparing our forecasts with measured fluxes from GOES 15 between 2014 and 2016, we determine the optimum forecast thresholds for deterministic and probabilistic forecasts by maximizing the receiver‐operating characteristic (ROC) and Brier skill scores, respectively. The training data set gives peak ROC scores of 0.71 to 0.87 and peak Brier skill scores of −0.03 to 0.32. Forecasts from AL give the highest skill scores for forecasts of up to 6 days. AL, solar wind pressure, or SYM‐H give the highest skill scores over 7–10 days. Hit rates range over 56–89% with false alarm rates of 11–53%. Applied to 2012, 2013, and 2017, our best forecasts have hit rates of 56–83% and false alarm rates of 10–20%. Further tuning of the forecasts may improve these. Our hit rates are comparable to those from operational fluence forecasts, that incorporate fluence measurements, but our false alarm rates are higher. This proof‐of‐concept shows that the geosynchronous electron flux can be forecast with a degree of success without incorporating a persistence element into the forecasts.

Simultaneous Observations of Poleward‐Moving Auroral Forms at the Equatorward and Poleward Boundaries of the Auroral Oval in Antarctica

AbstractPoleward‐moving auroral form (PMAF) is a type of dayside auroral pattern. The distinguishing characteristic of a PMAF is its separation from the auroral oval and subsequent poleward motion. It has been reported and widely accepted that PMAFs occur more frequently during periods with dominant southward interplanetary magnetic field (IMF). However, most ground‐based optical observations were made near magnetic latitudes of 75°, close to the equatorward boundary of the dayside auroral oval; therefore, PMAFs occurring at the poleward boundary were likely missed easily. Using all‐sky images from two stations located on the similar magnetic meridian in Antarctica at 80° and 75° magnetic latitude, and taking solar wind data close to the magnetosphere by the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft, we demonstrate that unlike the result from prior low‐latitude single‐station observations, the combined observations from both stations show an insignificant difference in the PMAF occurrence rate in the northward and southward IMF conditions and no clear sign suggesting that the southward IMF or southward turning of the IMF triggers PMAFs. With good agreements between PMAF occurrence rate and the intensity of the poleward drift, we suggest that PMAFs are more likely to be plasma patches torn away from the dayside auroral oval convecting antisunward and rather than direct foot points of reconnecting flux tubes.

Evolution of High‐Speed Jets and Plasmoids Downstream of the Quasi‐Perpendicular Bow Shock

AbstractPlasma structures with enhanced dynamic pressure, density, or speed are often observed in Earth's magnetosheath. We present a statistical study of these structures, known as jets and fast plasmoids, in the magnetosheath, downstream of both the quasi‐perpendicular and quasi‐parallel bow shocks. Using measurements from the four Magnetospheric Multiscale (MMS) spacecraft and OMNI solar wind data from 2015–2017, we present observations of jets during different upstream conditions and in the wide range of distances from the bow shock. Jets observed downstream of the quasi‐parallel bow shock are seen to propagate deeper and faster into the magnetosheath and on toward the magnetopause. We estimate the shape of the structures by treating the leading edge as a shock surface, and the result is that the jets are elongated in the direction of propagation but also that they expand more quickly in the perpendicular direction as they propagate through the magnetosheath.

Linear analysis of bump on tail instability with non-Maxwellian distribution function

The growth rate of bump on tail instability propagating in unmagnetized plasma has been derived. The dispersion relation has been characterized for (r, q) distribution function with spectral indices r and q which ultimately contributes towards tails and shoulder of distribution function. The growth rate of the bump on tail instability has been estimated numerically for different ratios of temperature and number density using solar wind data and also by varying values of indices r and q . The higher value of q play the role towards decreasing the growth rate where the instability has the higher value when the number density of the superthermal electrons in the bump is higher and the temperature is low. The maximum growth rate increases with the increase in number density of electrons and decreases with the increasing temperature in the bump.

Machine Learning Approach for Solar Wind Categorization

AbstractSolar wind classification is conducive to understanding the ongoing physical processes at the Sun and in solar wind evolution in interplanetary space, and, furthermore, it is helpful for early warning of space weather events. With rapid developments in the field of artificial intelligence, machine learning approaches are increasingly being used for pattern recognition. In this study, an approach from machine learning perspectives is developed to automatically classify the solar wind at 1 AU into four types: coronal‐hole‐origin plasma, streamer‐belt‐origin plasma, sector‐reversal‐region plasma, and ejecta. By exhaustive enumeration, an eight‐dimensional scheme (BT, NP, TP, VP, Nαp, Texp/TP, Sp, and Mf) is found to perform the best among 8,191 combinations of 13 solar wind parameters. Ten popular supervised machine learning models, namely, k‐nearest neighbors (KNN), Support Vector Machines with linear and radial basic function kernels, Decision Tree, Random Forest, Adaptive Boosting, Neural Network, Gaussian Naive Bayes, Quadratic Discriminant Analysis, and eXtreme Gradient Boosting, are applied to the labeled solar wind data sets. Among them, KNN classifier obtains the highest overall classification accuracy, 92.8%. Although the accuracy can be improved by 1.5% when O7+/O6+ information is additionally considered, our scheme without composition measurements is still good enough for solar wind classification. In addition, two application examples indicate that solar wind classification is helpful for the risk evaluation of predicted magnetic storms and surface charging of geosynchronous spacecraft.

Study of the fractality in a magnetohydrodynamic shell model forced by solar wind fluctuations

Abstract. The description of the relationship between interplanetary plasma and geomagnetic activity requires complex models. Drastically reducing the ambition of describing this detailed complex interaction and, if we are interested only in the fractality properties of the time series of its characteristic parameters, a magnetohydrodynamic (MHD) shell model forced using solar wind data might provide a possible novel approach. In this paper we study the relation between the activity of the magnetic energy dissipation rate obtained in one such model, which may describe geomagnetic activity, and the fractal dimension of the forcing. In different shell model simulations, the forcing is provided by the solution of a Langevin equation where a white noise is implemented. This forcing, however, has been shown to be unsuitable for describing the solar wind action on the model. Thus, we propose to consider the fluctuations of the product between the velocity and the magnetic field solar wind data as the noise in the Langevin equation, the solution of which provides the forcing in the magnetic field equation. We compare the fractal dimension of the magnetic energy dissipation rate obtained, of the magnetic forcing term, and of the fluctuations of v⋅bz, with the activity of the magnetic energy dissipation rate. We examine the dependence of these fractal dimensions on the solar cycle. We show that all measures of activity have a peak near solar maximum. Moreover, both the fractal dimension computed for the fluctuations of v⋅bz time series and the fractal dimension of the magnetic forcing have a minimum near solar maximum. This suggests that the complexity of the noise term in the Langevin equation may have a strong effect on the activity of the magnetic energy dissipation rate.