Mission Oriented Support and Theory (MOST) for MMS—the Goddard Space Flight Center/University of California Los Angeles Interdisciplinary Science Program
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The MOST IDS team was tasked with focusing on two general areas: The first was to participate with the Fast Plasma Investigation (FPI) team in the development of virtual detectors that model the instrument responses of the MMS FPI sensors. The virtual instruments can be “flown through” both simulation data (from magnetohydrodynamic, hybrid, and kinetic simulations) and Cluster and THEMIS spacecraft data. The goal is to determine signatures of magnetic reconnection expected during the MMS mission. Such signatures can serve as triggers for selection of burst mode downloads. The chapter contributed by the FPI team covers that effort in detail and, therefore, most of that work has not been included here. The second area of emphasis, and the one detailed in this chapter, was to build on past and present knowledge of magnetic reconnection and its physical signatures. Below we describe intensive analyses of Cluster and THEMIS data together with theoretical models and simulations that delineate the plasma signatures that surround sites of reconnection, including the effects of turbulence as well as the detailed kinetic signatures that indicate proximity to reconnection sites. In particular, we point out that particles are energized in several regions, not only at the actual site of reconnection.
KeywordsMagnetic reconnection Plasma physics Magnetofluid turbulence
The IDS MOST effort has had two primary areas of focus: The first is to work with the Fast Plasma Investigation (FPI) team to develop virtual-MMS FPI detectors to “fly through” both simulation data (from magnetohydrodynamic (MHD), hybrid, and kinetic simulations) and Cluster and THEMIS data to uncover signatures of magnetic reconnection that are expected to be seen during the MMS mission. Consequently, we helped in designing “burst mode triggers” to be used in selecting the highest time resolution data for download to ground. The second focus has been to build on past and present knowledge of magnetic reconnection and its physical signatures by undertaking intensive analyses of Cluster and THEMIS data, together with MHD and kinetic simulations, to delineate the plasma signatures that indicate proximity to reconnection sites. These theoretical and simulation studies have helped to clarify where particle energization that is related to magnetic reconnection is expected to occur in the magnetosphere.
Because the development of the burst mode triggers and the algorithms for computing (fluid) moments from the plasma distribution function are described in detail in the chapter contributed by the Fast Plasma Instrument team, we only very briefly mention that work. In Sect. 3 we describe work done identifying sites of reconnection on the dayside, primarily using a variety of theoretical models, simulations and Cluster data; in Sect. 4 we review similar work for magnetotail events (but now including data obtained from THEMIS). The role of turbulence in enhancing reconnection or in triggering it has been a subject of interest for many years and in Sect. 5 we review observations, simulations, and other analyses related to the relationship between turbulence and reconnection.
2 Modeling the Fast Plasma Instruments
Using simulations and current data from Cluster and THEMIS, in collaboration with the FPI team, we have constructed virtual instrument models of the FPI Dual Electron Spectrometers (DES) and Dual Ion Spectrometers (DIS) responses during encounters with expected reconnection sites in various regions of the magnetosphere. The goal has been: (1) to ensure that detectors are optimized in energy range, angular scan, and time resolution for detection of reconnection signatures; (2) to assist in the development of data analysis software and to assist in developing algorithms for computing accurate phase-space densities and plasma moments; and (3) to help in defining and refining the onboard FPI trigger algorithms needed to choose the most interesting burst mode data intervals for downlink. These activities are essential for identifying the physical processes that give rise to reconnection and that lead to heating and acceleration of ions and electrons. Both day- and night-side regions were included. The Virtual-MMS FPI detectors were designed to “fly through” data obtained from both numerical simulations and spacecraft.
The FPI/DES instrument produces 150 burst sky maps every 4.5 s and the FPI/DIS produces 30 burst sky maps every 4.5 s. One of the primary tasks of the FPI data processing unit is to evaluate in real time the data being collected by the sensors to generate trigger terms. The reader is referred to the FPI chapter for details of that aspect of our work. In addition, the computation of accurate velocity distribution functions and plasma moments requires careful error analysis to both certify the key parameters and to develop optimal schemes for in-flight calibration. The MOST team contributed to that effort, which also is summarized in the FPI chapter (and in a paper submitted to the Journal of Geophysical Research (Gershman et al. 2014)). That work will not be discussed further here.
3 Dayside Signatures of Reconnection
The scientific focus of MMS is to understand the physical processes that facilitate magnetic reconnection both in cases when there is a strong background field that is not reconnecting and in situations when the dominant magnetic field itself is changing direction and undergoing reconnection. The first situation—so-called component reconnection—is most likely to occur at the dayside magnetosheath, which MMS will encounter repeatedly during the first year of the mission. Afterwards, apogee will be increased and MMS will enter the tail plasma sheet in which the second type of geometry is found. We first describe studies focusing on the dayside and then turn to work looking at nightside phenomena.
3.1 Locating Magnetic Nulls in the Magnetosheath
One topological construct associated with magnetic reconnection is the magnetic null (see, e.g., Xiao et al. 2006; He et al. 2008 and references therein). To model an encounter with a magnetic null by MMS, we used four-point Cluster data to test techniques for detecting these three-dimensional structures in the dayside magnetosheath (Wendel and Adrian 2013). Nulls are associated with the filamentary substructure of current sheets where reconnection is occurring. In a 2D analysis, Retinò et al. (2007) found evidence for reconnection at a filamentary current layer, while Sundkvist et al. (2007) determined from structure function analyses that the field was turbulent. Wendel and Adrian (2013) showed that the Poincaré index implied that the spacecraft had encompassed a number of three-dimensional magnetic nulls, many of which were associated with strong small-scale currents. (The Poincaré index is a measure of the number of roots in a volume (Greene 1992). A root in magnetic field space corresponds to a magnetic null point in configuration space.)
3.2 Using Three-Dimensional Particle-in-Cell Simulations to Identify the Location and Rate of Reconnection
To further illustrate how and where E || was distributed along the QSL field lines that did support reconnection, the running sum of the parallel electric field along the field lines was followed. The field lines that are reconnecting carry a relatively steady DC contribution to the reconnection rate that is absent on field lines that are not reconnecting, although both types of field lines have fluctuating positive and negative values of the parallel electric field. The reconnection rate resulted entirely from the DC and linear trends in E ||. Reconnection occurred along a field line wherever the running sum of E || was increasing.
The ramifications for the interpretation of reconnection in three-dimensional turbulence both in simulations and in observations is that the location and rate of reconnection is governed by low-order coherent structures even when fields are highly stochastic and currents are filamented. While it is certainly possible that both fluctuations and double layers contribute to the physics that sustains the average reconnection electric field, it is the average DC field that governs the reconnection rate. The results also affect the inferred location of the site of reconnection and the rate of reconnection as determined from observations. If the medium is not laminar, as is usually the case in the magnetosheath and plasma sheet, then the reconnection rate cannot be inferred from a local parallel electric field measurement, but rather must be estimated from the spatial average along a field line, or by some other means.
4 The Nightside: Studies of Reconnection in the Magnetotail
4.1 Studies of the Electron and Ion Diffusion Regions
The multi-scale nature of reconnection has long been a focus of study in both space and laboratory plasmas. The initiation and reconfiguration of magnetic topology associated with reconnection are thought to arise as a result of demagnetization of electrons within the small electron diffusion region (EDR) that is embedded within the much larger ion diffusion region (IDR) where ions are demagnetized. IDRs, where Hall physics governs the magnetofluid description, have been identified by their magnetic and electric field geometry (see, e.g., Wygant et al. 2005; Vaivads et al. 2006; Eastwood et al. 2010a, 2010b).
The EDR is difficult to identify in data from current spacecraft (but see Scudder et al. 2012), but current measurements can delineate the substructure of the current sheet where reconnection is occurring. Chen et al. (2008) and Wang et al. (2010) used the observations of temperature anisotropy and variations in electron moments to identify magnetic islands and the scale sizes of an electron current layer. The anisotropic electron pressure with p ||>p ⊥ within the reconnection region was first reported by Øieroset et al. (2002) and the divergence of the electron pressure tensor was first measured using the four Cluster spacecraft by Henderson et al. (2008). The anisotropy was accounted for in a numerical study by Egedal et al. (2005), who found that it caused electron trapping by magnetic mirror forces and parallel electric fields. Egedal et al. (2008) derived an analytical form of the electron distribution function that accounted for the anisotropy. Egedal et al. (2010) compared the analytic result to the anisotropic electron distributions observed by Cluster in the October 1, 2001 event (Chen et al. 2008). Lê et al. (2009) derived new fluid-closure equations to describe the state functions (p || and p ⊥) for magnetized electrons in a collisionless regime in which electron trapping accurately treated the pressure anisotropy. In subsequent fluid simulations using the new fluid closure relationships, Ohia et al. (2012) demonstrated that the pressure anisotropy could drive large-scale elongated electron current layers within the reconnection region.
4.2 Multiple X-line Structures Observed by Cluster
4.3 Dipolarization Fronts and Their Relationship to Reconnection in the Magnetotail
Dipolarization fronts (DFs) are a phenomenon commonly detected near the equatorial plane of the Earth’s tail plasma sheet. Rapid (≪1 minute) increases in the north- to south-directed component of the magnetic field (B Z) have been reported in the near-Earth plasmasheet during magnetospheric substorms (Russell and McPherron 1973; Angelopoulos et al. 1992; Runov et al. 2009b, 2011). They are generally found near the leading edge of the rapid earthward flows (hundreds of km/s) called bursty bulk flows (BBFs) (Baumjohann et al. 1990; Angelopoulos et al. 1992). THEMIS data showed that the dipolarization fronts generally propagate earthward from at least the near-Earth tail. A rapid increase of B Z is preceded by a decrease of smaller amplitude (Ohtani et al. 2004). The front is generally followed by a decrease in both the thermal plasma density and temperature (Wolf et al. 2009, and references therein). Earthward propagating dipolarization fronts and BBFs may be responsible for most of the earthward transport of energy and magnetic flux from the magnetotail to the inner magnetosphere (Angelopoulos et al. 1994).
Common features across each DF are a sharp jump in B z (Fig. 7a), a drop in the plasma density (Fig. 7b), a corresponding decrease in plasma β (Fig. 7i), a decrease in the plasma pressure and an increase in the magnetic pressure (Fig. 7j). These variations across the DFs indicate that DFs carry an entropy-depleted flux tube, or localized “plasma bubble” behind the DFs. Panel Fig. 7k demonstrates a decrease in the entropy, calculated from the ion distribution function (black in Fig. 5k), or the flux-tube entropy parameter (using Wolf et al. 2006’s formula, red in panel Fig. 11k).
Traditionally, dipolarization of stretched tail magnetic field, which is often accompanied by observation of a DF, is believed to be associated with a decrease of the cross-tail current in the near-Earth region that might be caused by a cross-tail current instability (Lui et al. 2006). More recently, DFs are also thought to result from magnetic reconnection in which the exhaust jets and entrained magnetic fluxes from the reconnection region pile up, forming a front of increased current-sheet-normal magnetic field (Hoshino et al. 2001; Hoshino 2005; Nakamura et al. 2009; Sitnov et al. 2009). In kinetic simulations, Sitnov et al. (2009) showed that DFs can form as a result of transient reconnection.
Hwang et al. (2011b) concluded from the example in Fig. 7 that multiple DFs can result either from bursty reconnection events or from continuous reconnection in which the rate fluctuates on the time scale of about 3 minutes, corresponding to the occurrence rate of multiple DFs. They noted that the density ratio of O+ to H+ ions increased from ∼5% before the first DF to ∼20% at the end of the event, indicating that a series of bursty reconnection events evolved from the plasma sheet to the lobe and that the repeated reconnection events might have triggered formation of multiple DFs, which could have arisen from patchy reconnection. Recent studies by Liang et al. (2014), using a global MHD simulation of this event showed numerous simultaneous reconnection sites dispersed over the near Earth current sheet.
4.4 Reconnection, Dipolarization Fronts and Particle Acceleration
The most commonly posited cause for dipolarization fronts, BBFs and depleted flux tubes, is sporadic and spatial localized reconnection (Sergeev et al. 1992, and other references). Dipolarization fronts generated by reconnection have been found in both quasi-local and global MHD simulations (Wiltberger et al. 2000; Birn et al. 2004; Ashour-Abdalla et al. 2011; Birn et al. 2011), hybrid simulations (Krauss-Varban and Karimabadi 2003) and two-dimensional particle-in-cell kinetic simulations (Sitnov et al. 2009; Sitnov and Swisdak 2011). However, other mechanisms, including the ballooning interchange instability (Hurricane et al. 1996; Pritchett and Coroniti 2010; Lyatsky and Goldstein 2013), may also be important for forming dipolarization fronts and for determining their azimuthal extent.
At the passage of DFs. the thermal plasma density decreases, fluxes of energetic ions and electrons increase dramatically to hundreds of keV (Runov et al. 2009a, 2009b, 2011; Sergeev et al. 2009; Ashour-Abdalla et al. 2011; Hwang et al. 2011a). But exactly how and where these energetic electrons are accelerated is not well understood. Work to date has concentrated on two areas: acceleration at or near the reconnection region and acceleration as the particles propagate earthward. There are many recent reviews that have summarized our present understanding (see, e.g., Birn and Priest 2007). An important result is that when kinetic effects are included, reconnection progresses at a faster pace than it does in MHD and there are two regions associated with the reconnection process that are the sites of intense energy exchange: separatrix regions and electron jets.
The regions around the separatrices (the separatrices are the boundary between open and closed field lines associated with x-points in 2D and, as pointed out above, magnetic surfaces in 3D) in kinetic reconnection generate intense electron flows that lead to a variety of waves and instabilities. At scales approaching the ion Larmor radius, localized electric fields with Hall physics signatures appear. These fields extend a great distance away from the reconnection x-point, transferring sizeable amounts of energy (Shay et al. 2011). The Hall electric field has a significant electrostatic component due to the local breakdown of charge neutrality (Huang et al. 2006). In addition, the differences in the electron and ion speeds lead to localized (on the electron skin depth scale) electron jets that emerge from the reconnection region (Fujimoto 2006; Karimabadi et al. 2007). Both the Hall region along the separatrices and the electron jets extend for long distances (Phan et al. 2011; Shay et al. 2011), carrying significant amounts of energy. The separatrices are characterized by strong perpendicular and parallel electric fields that lead to strong electron energization (Egedal et al. 2012).
Separatrix regions and electron jets are both sensitive to the specific conditions of the reconnecting plasma. At the separatrices, the Hall physics and the formation of electron cavities (regions of depleted electron density) are affected in strength by the presence of a guide field (Lapenta et al. 2010, 2011), which, although typically weak in the magnetotail, nevertheless can have amplitudes of up to 20% of the reconnecting field. The electron jets emerging from the reconnection region also are affected by those guide fields (Goldman et al. 2011), leading to the possibility that typical magnetotail values of the guide field can either suppress or enable the electron jets (Lê et al. 2013).
An additional, or alternative, location for acceleration of particles is the magnetic pile-up region formed as dipolarization fronts impinge on the inner magnetosphere (Kivelson 1980; Birn et al. 2004; Asano et al. 2010; Birn et al. 2011). Kinetic simulations (Sitnov et al. 2009) showed that electrons do not necessarily need to be energized at the x-line and that energy dissipation is stronger at the dipolarization front than it is at the initial reconnection region. Strong electron energization at dipolarization fronts has been well established by observations in the magnetotail (Runov et al. 2009a, 2009b; Sitnov et al. 2009; Zhou et al. 2009).
For the February 15, 2008 substorm the observations by THEMIS were near the dipolarization front (x∼−10R E), and for the August 15, 2001 substorm the observations were near the reconnection site (X∼−17R E). Pan et al. (2014) examined another event on March 11, 2008, that was observed by THEMIS spacecraft P3 and P4 from near the dipolarization front (P4, x∼−10R E) and by THEMIS P2 nearer the putative location of the neutral line (x∼−15R E). These multi-point measurements not only put rather strict constraints on the global MHD and LSK simulations, but also enabled them to quantify the electron energization in different regions.
It is not surprising that the inclusion of high-energy electrons provides a better comparison between the simulations and observations since P2 is not far from the source region where the electrons were launched, and the observed electron flux at P2 has a high-energy tail. These comparisons show that the simulations need to include high-energy electrons with a power law distribution. The addition of the power law to the source distribution also improved the agreement at P3 and P4 nearer the Earth (Pan et al. 2014). The distribution function with the power law dependence adds a free parameter to the analysis that enhances the ability of obtaining a better fit to the observations. However, that the improvement is so dramatic, suggests strongly that for this event the physics near the neutral line is very important for understanding the electron dynamics.
4.5 Dipolarization Fronts, Reconnection and MMS
Neither the LSK simulations nor the PIC simulations give a complete picture of the physics of reconnection in the magnetotail. The LSK simulations use the electric and magnetic fields from global MHD simulation. And while the MHD simulations are self-consistent, the resistivity that allows reconnection to occur is arbitrary. In addition, the LSK particle calculations are not self-consistently tied to the MHD results. PIC simulations contain the full physics of reconnection but are very expensive to run and therefore are generally limited to idealized calculations over small spatial domains. In reality the reconnection in the magnetosphere is determined by the overall changes in the solar wind and magnetosphere interaction that occur on magnetospheric scales. In support of MMS we have developed a simulation approach in which the UCLA global MHD simulation is coupled with an implicit particle in cell simulation (Markidis et al. 2010; Ashour-Abdalla et al. 2014). The work is motivated by the solar physics work of Baumann et al. (2013). In the first study, the new system was used to model the February 15, 2008 substorm discussed above. A two-dimensional version of the iPIC3D code (modeling the XZ plane) was run in the magnetic field and plasma configuration from the MHD code just prior to the onset of reconnection in the tail. The ion temperature was taken from the MHD results and the initial electron temperature was one fifth of the ion temperature. During the iPIC3D simulation the boundary conditions at the north and south boundaries were set by using values from the MHD simulation, while those at the earthward and tail boundaries used free boundary conditions. The coupling is in one direction only, the PIC results do not feed back into the MHD calculation.
5 Reconnection and Turbulence
The role of turbulence is a recurring theme in studies of reconnection. In trying to anticipate where MMS will observe reconnection there are at least three aspects of such an investigation that appear to be important (Matthaeus and Velli 2011). First, even when starting from quiet equilibrium initial conditions, simulations of reconnection show clearly that turbulence is generated during the nonlinear evolution of the reconnection event. One such three-dimensional kinetic simulation is described in Daughton et al. (2011) and the argument that the simulation reflects the generation of intermittent cascading turbulence is discussed in Leonardis et al. (2013). Second, magnetofluid turbulence itself can give rise to reconnection (Matthaeus and Montgomery 1980; Matthaeus and Lamkin 1985; Servidio et al. 2011; Lazarian et al. 2012; Donato et al. 2013). The third way in which turbulence and reconnection are related occurs when the background within which reconnection is initiated is permeated by turbulence. In that situation, estimates of reconnection rates and classical pictures involving slow shock waves are likely to be modified dramatically by the background turbulence (Matthaeus and Lamkin 1985; Lazarian and Vishniac 1999; Kowal et al. 2009; Eyink et al. 2011; Lazarian et al. 2012). The turbulence can nudge fluid elements into thin current sheets and initiate reconnection. In addition, strong stochasticity is itself thought capable of effectively demagnetizing particle orbits, thus allowing the magnetic topology to change (i.e., reconnect) independent of the local resistivity (see, e.g., Eyink et al. 2011).
At present it is difficult to use existing spacecraft to study the question of whether or not turbulence is generated at sites of reconnection in geospace. The orbital separation of Cluster is generally too large to determine the three-dimensional statistical properties of the local magnetic fields. That situation will change with the MMS, which will have much closer separations and much higher time resolutions. What is clear, however, is that flows near presumed sites of reconnection are often populated by discontinuities and other fluctuations. Such discontinuities can result from turbulence generated by reconnection as explored in the three-dimensional PIC simulation by Daughton et al. (2011) and Leonardis et al. (2013) and, as noted in the analyses of Cluster data, by Retinò et al. (2007) and Wendel and Adrian (2013). More easily addressed is the third aspect of the role of turbulence in magnetic reconnection, viz., the ubiquity of turbulence in many regions that show evidence of magnetic reconnection. The widespread presence of turbulence suggests that simple laminar initial conditions often employed in numerical studies of reconnection might not reflect accurately actual conditions to be encountered by MMS. The presence of turbulence in the magnetosheath results naturally from velocity shears and the convection of turbulence through the bow shock from the (turbulent) solar wind. The presence of that turbulence has been accounted for in the analyses of Cluster data discussed above. The situation in the magnetotail is more complex and less clear as most global simulations of the magnetosphere do not include turbulence in the initial conditions and, generally, do not generate turbulence as they evolve. However, there have been several analyses of magnetotail data and simulations of the magnetotail that have demonstrated the excitation of turbulence. We describe below some of our investigations of turbulence in the magnetotail using global MHD simulations.
The transport of magnetic flux, energy, and momentum in the magnetotail can be complex and variable even during quiet and steady magnetospheric conditions and is even more complex when the solar wind conditions are changing and the magnetosphere is in a disturbed state. The average convection in the plasma sheet is directed sunward on the earthward side of the reconnection region and tailward on the anti-sunward side of the reconnection region. Several studies (Borovsky et al. 1997; Angelopoulos et al. 1999; Chang et al. 1999a, 1999b; Klimas et al. 2000; Borovsky and Funsten 2003; Weygand et al. 2007) have presented evidence that turbulence in the plasma sheet plays a major role in the physics of the magnetotail.
At small scales, turbulence can contribute intermittently to the effective resistivity of the local plasma. At larger scales, turbulence can lead to the formation of multiple reconnection sites and flux tubes within current layers. Turbulence can significantly modify plasma transport properties, thereby altering the more global plasma dynamics involved in driving reconnection as well as provide a means by which particles can be accelerated to suprathermal energies. Boundary layers generated during reconnection produce turbulence that can then feed back on the reconnection process. At large scales in the plasma sheet, eddy turbulence is most likely generated in the sheared flows associated with localized fast flows driven by reconnection as described by Borovsky et al. (1997), Borovsky and Funsten (2003) (also see Weygand et al. 2005).
Reconnection in the plasma sheet has been described as an avalanching or cascading process (Uritsky et al. 2002, 2003; Klimas et al. 2004; Kozelov et al. 2004). A direct consequence of this is that reconnection in the plasma sheet at one position and time must be able to induce reconnection at a nearby site at a later time, which is the essence of an avalanche. Therefore plasma turbulence can be a link between reconnection sites. To help in understanding the specifics of reconnection onset and how this very local electron skin-depth phenomenon evolves to affect the plasma sheet, we have undertaken a series of global MHD simulations driven by constant or simplified solar wind/IMF conditions. These simulations produce magnetotail fluctuations with spectral properties similar to observations (El-Alaoui et al. 2010, 2011a, 2012). El-Alaoui et al. (2010, 2012) found power spectral densities (PSDs) and probability distribution functions (PDFs) that are consistent with in-situ observations and with theory. We found that localized reconnection was the main process driving turbulence.
In another global magnetohydrodynamic (MHD) simulation, El-Alaoui et al. (2009) found near-Earth flow vortices at the driving scale that agreed with magnetospheric observations taken at THEMIS P3 and P4. Around the time of substorm onset, flow vortices formed in the simulation near the locations of the two spacecraft, but the output was too sparse in space and time to resolve fully the turbulent spectrum. To verify that the flows were actually turbulent, El-Alaoui et al. (2010, 2011b, 2012) extended the study via an event simulation driven by upstream solar wind observations with both high temporal and spatial resolution. The results indicated that the plasma sheet was turbulent (El-Alaoui et al. 2013).
The simulation reproduced not only the overall magnetotail changes observed by spacecraft, but also the observed spectral properties of the turbulence. The February 7, 2009 substorm event was chosen for the simulation because there were eight spacecraft located in different regions of the magnetosphere during the time of interest (0300 UT to 0500 UT). Wind spacecraft observations were used for the solar wind parameters. MHD output and THEMIS P4 magnetic field measurements from 0200 UT to 0700 UT are compared in Fig. 17 (right panels) (El-Alaoui et al. 2013). The passage of a strong dipolarization front near 0400 UT is prominent in both the observations and the simulation. The magnetic field observations at 3-second intervals are indicated in red. The black lines indicate MHD output at 20-second intervals.
Around 0400 UT, THEMIS P4 was within the dipolarized region as indicated by the time history of B z. THEMIS P4 measured a value of B x indicating that the spacecraft was located in the southern plasma sheet and was never close to the center of the current sheet. Important features in the observations also occur in the simulation. In particular, the timing and magnitude of the dipolarization front reflected in the B z component were quite similar in the observations and in the simulation although the detailed behavior of fluctuations that lasted less than a few minutes were not possible to reproduce. THEMIS P5 saw developments similar to THEMIS P4 (Fig. 17 left panels). The magnetic field’s y-component was relatively small and had an overall slow drift at both spacecraft that was reproduced by the simulation at both P4 and P5, with a better match at P4.
The simulation results showed changes similar to those seen in the observed magnetic field and plasma flow during the event. Further, the simulation shows that PSDs and PDFs (not shown) computed from the simulation had the properties of fluid turbulence and that they were comparable to those seen in observations at THEMIS P5. The largest scales were associated with reconnection outflows that were diverted in the near-Earth region. The median value of the PSD slopes we obtained from event studies and in generic studies were close to −5/3 and both the PSD and PDF were comparable to those of Weygand et al. (2005).
These studies enhance our understanding of the relationship between turbulence and reconnection, especially in the magnetotail. MHD simulations have done a good job of generating turbulent spectra near dipolarization fronts. By comparing in situ observations to simulation results we hope to find out how the properties of turbulence depend on overall conditions. Eventually, MHD can be combined with kinetic studies to quantify the overall dissipation over both inertial and dissipative scales and how turbulence influences reconnection (Lapenta 2008; Kowal and Lazarian 2010; El-Alaoui et al. 2012, 2013). Studies using MMS data will probe further how turbulence changes the reconnection process and can affect the reconnection rate (Matthaeus and Lamkin 1985, 1986; Goldstein et al. 1986; Strauss 1988; Klimas et al. 2010; Eyink et al. 2011).
During the past several years, the GSFC-UCLA MOST IDS team has focused on several general themes. One activity has been to work with the FPI team in developing software tools to characterize the expected performance of both the DES and DIS detectors on orbit. In particular, we have helped to determine “burst mode triggers” that will flag data intervals of greatest scientific interest that will be telemetered to ground at the highest time resolution. This work included algorithms to account for various sources of error that affect the detection of particles as they move through the detectors. We also tested and developed various computational schemes for rapidly computing actual fluid moments from the electron and ion distribution functions (density, velocity, temperature, etc.).
The second general focus area has been to use Cluster and THEMIS data to explore in detail regions where reconnection has been observed so as to better characterize what MMS might encounter. On the dayside, we have used Cluster data when the four spacecraft were in a good tetrahedral configuration to characterize magnetic null geometry in the magnetosheath. The Cluster data were in general agreement with theories and descriptions of three-dimensional nulls. An interesting aspect of those data intervals is that they contained a significant level of magnetofluid turbulence.
In the magnetotail, the magnetic configuration resembles more the morphology of a Harris current sheet, but there, too, the data suggest a significant modification of any laminar picture due to the presence and generation of turbulence. Using both Cluster and THEMIS data, we characterized where and how particles are energized in the magnetotail. We found that particles were energized both adiabatically and nonadiabatically as dipolarization fronts swept up particles as the global magnetic fields relaxed toward more dipolar configurations or as particles bounced back and forth on moving field lines. For two quite similar events we were able to show, using global MHD, LSK and kinetic simulations why the observed particle characteristics were so distinct. We confirmed that although energization is associated with and initiated by magnetic reconnection, the reconnection site is not necessarily where the strongest plasma heating and acceleration arise.
Turbulence generated by reconnection and turbulence affects how and where reconnection happens. The physical processes that trigger reconnection are influenced greatly by the ubiquity of turbulence in both the magnetosheath and magnetotail. Strong ambient turbulence appears capable of initiating reconnection if the magnetic and velocity fields are sufficiently stochastic. But as turbulence evolves in two and three dimensions, plasma bubbles can interact to form thin current sheets that become preferred sites of reconnection. Using global simulations to drive dipolarization fronts and magnetic substorms, we have shown that the excitation of reconnection in the tail current sheet is accompanied by the generation of strong turbulence that is characterized by nested vortical structures and power spectra that resemble Kolmogorov fluid turbulence.
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