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At least 415 records · Page 23

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗

The Kinematically Hot, Extremely Metal-poor C-19 Stellar Stream in DESI DR2

Stellar streams are the result of a host galaxy’s gravitational potential tidally disrupting satellite dwarf galaxies and globular clusters (GCs), causing them to grow leading and trailing tidal tails. The C-19 stellar stream is an extremely metal-poor stellar population, showing chemical abundance patterns characteristic of a GC. However, its large velocity dispersion is difficult to reconcile with a conventional, purely baryonic, disrupting-GC progenitor. Current techniques for stream characterization are primarily applied to Gaia DR3, relying heavily on proper-motion measurements. Using the Dark Energy Spectroscopic Instrument (DESI), which provides radial velocities and metallicities for over 10 million stars and reaches significantly fainter magnitudes than comparable surveys, we employ a mixture model approach to jointly characterize stream populations in proper motions, radial velocities, and metallicities against a Milky Way halo background. By applying this framework to the C-19 stellar stream, we identify a total of 47 spectroscopically confirmed member stars, of which 41 are newly identified and only 6 were previously reported in the literature. In this work, we measure a velocity dispersion of $7.8^{+1.5}_{-1.3}$km s −1 and a mean metallicity of [Fe/H] = $-3.36^{+0.12}_{-0.10}$. We further identify a novel “spur” feature within the stream. We conclude that our measurements are in line with previous works identifying C-19 as a “hot,” metal-poor stream. In forthcoming work, we will apply this approach to many more streams in the DESI footprint, enabling population-level comparisons with predictions from simulations.

Mohammed, Nasser [University of Toronto; Dunlap In↗

Performance Measurement, Visualization and Modeling of Parallel and Distributed Programs

This paper presents a methodology for debugging the performance of message-passing programs on both tightly coupled and loosely coupled distributed-memory machines. The AIMS (Automated Instrumentation and Monitoring System) toolkit, a suite of software tools for measurement and analysis of performance, is introduced and its application illustrated using several benchmark programs drawn from the field of computational fluid dynamics. AIMS includes (i) Xinstrument, a powerful source-code instrumentor, which supports both Fortran77 and C as well as a number of different message-passing libraries including Intel's NX Thinking Machines' CMMD, and PVM; (ii) Monitor, a library of timestamping and trace -collection routines that run on supercomputers (such as Intel's iPSC/860, Delta, and Paragon and Thinking Machines' CM5) as well as on networks of workstations (including Convex Cluster and SparcStations connected by a LAN); (iii) Visualization Kernel, a trace-animation facility that supports source-code clickback, simultaneous visualization of computation and communication patterns, as well as analysis of data movements; (iv) Statistics Kernel, an advanced profiling facility, that associates a variety of performance data with various syntactic components of a parallel program; (v) Index Kernel, a diagnostic tool that helps pinpoint performance bottlenecks through the use of abstract indices; (vi) Modeling Kernel, a facility for automated modeling of message-passing programs that supports both simulation -based and analytical approaches to performance prediction and scalability analysis; (vii) Intrusion Compensator, a utility for recovering true performance from observed performance by removing the overheads of monitoring and their effects on the communication pattern of the program; and (viii) Compatibility Tools, that convert AIMS-generated traces into formats used by other performance-visualization tools, such as ParaGraph, Pablo, and certain AVS/Explorer modules.

Yan, Jerry C.↗

Perturbations in Brain Functional Connectivity Patterns After Waking From Slow Wave Sleep Under Different Cognitive States

Sleep inertia refers to the state of transition between sleep and wake characterized by impaired alertness, confusion, and reduced cognitive and behavioral performance. While the behavioral symptoms of sleep inertia are well described, the neurological changes that lead to this state remain elusive. Here, to understand the state of sleep inertia and the reorganization that the brain undergoes, we took a graph theoretical approach and compared the EEG derived brain connectivity patterns before sleep and after waking up while participants (n = 10) performed multiple tasks that differed in cognitive complexities. We focused on how the degree and the clustering coefficient of brain regions (EEG sensors) change immediately after participants wake up from slow wave sleep. During a psychomotor vigilance task (PVT), designed to assess vigilant attention, we find that the brain regions with strong network connectivity (degree) before sleep show a reduction in connectivity after waking. In contrast, those with low connectivity before sleep have greater connectivity after waking. The regions that undergo these changes are specific to each participant and these findings are unique to the beta frequency range, which plays a key role in sensorimotor functioning and preserving the current state of the brain. Moreover, in tasks that required inhibitory control and arithmetic reasoning, we found that only regions with weak connectivity before sleep exhibited more connections after waking, but regions with high connectivity prior to sleeping remained unchanged, highlighting task specific effects. Furthermore, we find that during the PVT, the clustering coefficient within low frequency oscillations of the brain is reduced upon waking while it remains unchanged during other tasks. These results suggest that the connections between regions that are lost after abrupt awakening can be reallocated to other regions in order to renormalize the brain. However, this response may only be evident during specific cognitive states and may be more nuanced during complex task performance.

sleep inertia↗

Cluster environment quenches the star formation of low-mass satellite galaxies from the inside-out

ABSTRACT Environment plays a critical role in the star formation history of galaxies. Tidal and hydrodynamical stripping, prominent in cluster environment, can remove the peripheral gas of galaxies and star formation may thus be environmentally suppressed from the outside-in. We revisit the environmental dependence of the radial gradient of specific star formation rate (sSFR) profile. We probe the radial gradient by using the archival spectral indices D4000n and HδA measured from SDSS fibre spectra, to indicate central sSFR and the total sSFR from fitting the spectral energy distribution. Despite the low spatial resolution, the wealth of SDSS data allows to disentangle the dependences on stellar mass, sSFR, and environment. We find that low-mass satellite galaxies in the mass range $9\lt \mathrm{log}\, \mathcal {M}_{\star }/\mathcal {M}_{\odot }\lt 9.8$ on average quench in more inside-out pattern compared to isolated galaxies matched in mass, sSFR, and fibre coverage. This environmental effect is particularly strong for galaxies below the star formation main sequence, and peaks for those in the core of massive clusters where the phase-space diagram reveals clear links between the inside-out quenching and orbital properties. Our results suggest that both tidal and hydrodynamical interactions in cluster environment suppress the star formation of satellites mainly from the inside-out. As accreted gas of low angular momentum from hot gas haloes is an important source for replenishing central gas reservoir, we discuss how gas stripping in clusters may lead to starvation and cause inside-out quenching when the outer star-forming discs are not significantly affected.

79 ASTRONOMY AND ASTROPHYSICS↗

Understanding the chemical bonding of ground and excited states of HfO and HfB with correlated wavefunction theory and density functional approximations

Knowledge of the chemical bonding of HfO and HfB ground and low-lying electronic states provides essential insights into a range of catalysts and materials that contain Hf–O or Hf–B moieties. Here, we carry out high-level multi-reference configuration interaction theory and coupled cluster quantum chemical calculations on these systems. We compute full potential energy curves, excitation energies, ionization energies, electronic configurations, and spectroscopic parameters with large quadruple-ζ and quintuple-ζ quality correlation consistent basis sets. We also investigate equilibrium chemical bonding patterns and effects of correlating core electrons on property predictions. Differences in the ground state electron configuration of HfB(X 4 Σ - ) and HfO(X 1 Σ + ) lead to a significantly stronger bond in HfO than HfB, as judged by both dissociation energies and equilibrium bond distances. We extend our analysis to the chemical bonding patterns of the isovalent HfX (X = O, S, Se, Te, and Po) series and observe similar trends. We also note a linear trend between the decreasing value of the dissociation energy (D e ) from HfO to HfPo and the singlet–triplet energy gap (ΔE S–T ) of the molecule. Finally, we compare these benchmark results to those obtained using density functional theory (DFT) with 23 exchange–correlation functionals spanning multiple rungs of “Jacob’s ladder.” When comparing DFT errors to coupled cluster reference values on dissociation energies, excitation energies, and ionization energies of HfB and HfO, we observe semi-local generalized gradient approximations to significantly outperform more complex and high-cost functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transcriptional networks underlying a primary ovarian insufficiency disorder in alligators naturally exposed to EDCs

Interactions between the endocrine system and environmental contaminants are responsible for impairing reproductive development and function. Despite the taxonomic diversity of affected species and attendant complexity inherent to natural systems, the underlying signaling pathways and cellular consequences are mostly studied in lab models. To resolve the genetic and endocrine pathways that mediate affected ovarian function in organisms exposed to endocrine disrupting contaminants in their natural environments, we assessed broad-scale transcriptional and steroidogenic responses to exogenous gonadotropin stimulation in juvenile alligators (Alligator missippiensis) originating from a lake with well-documented pollution (Lake Apopka, FL) and a nearby reference site (Lake Woodruff, FL). Here, we found that individuals from Lake Apopka are characterized by hyperandrogenism and display hyper-sensitive transcriptional responses to gonadotropin stimulation when compared to individuals from Lake Woodruff. Site-specific transcriptomic divergence appears to be driven by wholly distinct subsets of transcriptional regulators, indicating alterations to fundamental genetic pathways governing ovarian function. Consistent with broad-scale transcriptional differences, ovaries of Lake Apopka alligators displayed impediments to folliculogenesis, with larger germinal beds and decreased numbers of late-stage follicles. After resolving the ovarian transcriptome into clusters of co-expressed genes, most site-associated modules were correlated to ovarian follicule phenotypes across individuals. However, expression of two site-specific clusters were independent of ovarian cellular architecture and are hypothesized to represent alterations to cell-autonomous transcriptional programs. Collectively, our findings provide high resolution mapping of transcriptional patterns to specific reproductive function and advance our mechanistic understanding regarding impaired reproductive health in an established model of environmental endocrine disruption.

59 BASIC BIOLOGICAL SCIENCES↗

Helium abundance enhancements in the solar wind

Evidence for a link between helium enhancements at 1 AU and transient coronal mass ejections is provided by the statistical analysis of 73 large helium abundance enhancement observations made by IMPs 6, 7 and 8 over 1972-1978. These events, in which helium abundance enhancement is greater than about 10%, are sporadic, sometimes clustered in time, occur approximately in phase with the solar cycle, and nearly 50% of them are associated with interplanetary shocks and/or geomagnetic activity sudden commencements. The plasma pattern associated with them is nevertheless independent of shock occurrence, and features high magnetic field strength, low alpha-proton velocity difference, and low proton temperature, suggesting that the enhancement is embedded in a closed, magnetically dominated structure that expands adiabatically. Evidence of an association between helium enhancement at 1 AU and type II and IV radio bursts in the corona is presented.

Borrini, G.↗

Ion mobility spectrometry of hydrazine, monomethylhydrazine, and ammonia in air with 5-nonanone reagent gas

Hydrazine (HZ) and monomethylhydrazine (MMH) in air were monitored continuously using a hand-held ion mobility spectrometer equipped with membrane inlet, 63Ni ion source, acetone reagent gas, and ambient temperature drift tube. Response characteristics included detection limit, 6 ppb; linear range, 10-600 ppb; saturated response, >2 ppm; and stable response after 15-30 min. Ammonia interfered in hydrazines detection through a product ion with the same drift time as that for MMH and HZ. Acetone reagent gas was replaced with 5-nonanone to alter drift times of product ions and separate ammonia from MMH and HZ. Patterns in mobility spectra, ion identifications from mass spectra, and fragmentation cross-sections from collisional-induced dissociations suggest that drift times are governed by ion-cluster equilibria in the drift region of the mobility spectrometer. Practical aspects including calibration, stability, and reproducibility are reported from the use of a hand-held mobility spectrometer on the space shuttle Atlantis during mission STS-37.

Flight Experiment↗

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Koslovsky, Matthew↗

Covariability of Climate and Streamflow in the Upper Rio Grande from Interannual to Interdecadal Timescales

Study region: The Upper Rio Grande (URG) flows from its headwaters in Colorado, U.S., and provides an important source of water to millions of people in the U.S. states of Colorado, New Mexico, Texas, and also Mexico. Study focus: We reassess the explanatory power of the relationship of sea surface temperatures (SST) on URG streamflow variability on interannual to interdecadal timescales. We find a significant amount of the variance of spring-summer URG streamflow cannot be fully explained by SST. New hydrological insights: We find that the interdecadal teleconnection between SST and streamflow is more clear than on interannual timescales. The highest ranked years tend to be clustered during positive phases of the Pacific Decadal Oscillation (PDO). During the periods of decadal high flow (1900-1920, and 1979-1995), Pacific SST resembles a positive PDO pattern and the Atlantic a negative Atlantic Multidecadal Oscillation (AMO) pattern; an interbasin pattern shown in prior studies to be conducive to high precipitation and streamflow. To account for the part of streamflow variance not explained by SST, we analyze atmospheric Reanalysis data for the months preceding the highest spring-summer streamflow events. A variety of atmospheric configurations are found to precede the highest flow years through anomalous moisture convergence. This lack of consistency suggests that, on interannual timescales, weather and not climate can dominate the generation of high streamflow events.

AMO↗

Agricultural Burning and Air Quality over Northern India: A Synergistic Analysis Using NASA's A-Train Satellite Data and Ground Measurements

In the recent years, New Delhi, the capital city of India, has ranked among the most polluted cities in the world regarding its air quality related to the submicron Particulate Matter (PM(sub 2.5)). Using NASA's A-train satellite data (MODIS, OMI, and CALIOP), ground-level PM2.5 measured in New Delhi (2013-2016), and back-trajectory calculations, we show that the PM(sub 2.5). over New Delhi is strongly affected by the agricultural fires in the northwestern Indian states of Punjab and Haryana during the post-monsoon season (October and November). The mass concentration of PM2.5 escalates from ~50 μg m(exp -3) measured prior to the onset of residue burning in early October to as high as 300 μg m(exp -3) (24-hour averaged, 7- day running mean) during the peak burning period in early November. A linear regression analysis reveals that the variations in PM(sub 2.5) over New Delhi can be attributed to the concurrent changes in the satellite retrievals of fire counts and aerosols over the crop burning area. The back-trajectory analysis shows that most clusters (> 80%) of the northwesterly flow near the ground intercepted the crop burning region before arriving at the receptor location in New Delhi; this further corroborates the transport patterns inferred from the satellite data. A 15-year long satellite record (2002-2016) reveals an increasing trend in agricultural fires (~617 per year) and aerosol loading (0.031 and 0.04 per year in aerosol optical depth and UV aerosol index) in November. Increasing levels of crop residue burning and resulting particulate matter pollution at an alarming rate over northern India is a pressing concern demanding corrective measures to substantially reduce or completely diminish the crop burning through an effective residue management system.

Crop Residue Fires↗

Quantitative microstructural investigation of 3D-printed and cast cement pastes using micro-computed tomography and image analysis

Highlights: • Processing alters the microstructure in 3D-printed lamellar cubic element. • A unique patterned and connected pore microstructure network exists. • Micro-channels are connected through micro-pores present at interfaces regions. • Three distinct pore volume domains exists in hardened microstructure. • Volume and frequency of pore, hydrated, and unhydrated clusters are dissimilar. Microstructural phases and mechanical properties of lamellar 3D-printed and cast hardened cement paste (hcp) elements were investigated using a lab-based X-ray microscope at two levels of magnification (0.4× and 4×). K-means clustering was used for quantitative image analysis. The entire volume of intact 3-days-old 3D-printed and cast hcp elements was characterized at 0.4× magnification. Three microstructural features (macro-pores, micro-channels, and interfacial micro-pores) were found to reside in three distinct pore size domains. The largest pores of the 3D-printed element were larger than the largest pores of the reference cast hcp element. Moreover, the smallest pore sizes of the 3D-printed element were found to be smaller than those present in the cast counterparts. Micro-channels were found to be connected to one another through the micro-pores present at interfacial regions, indicating the presence of a uniquely patterned and interconnected pore network. The role of locally weak and porous interfaces on mechanical response and fracture properties is discussed.

36 MATERIALS SCIENCE↗

Research Introduction [Slides]

In the topic of Reverse Time Imaging, we proposed a new IC to reduce computation cost but reserve image resolution for distributed sensor networks. For Induced Seismicity in Oklahoma, we analyzed fault stress state analysis at state scale, and we applied machine learning techniques to polarity picking and seismicity rate forecasting. The results provide better understanding of fault properties, stress field, and the relationships among fault, stress state, injections, and potential seismic hazards. Lastly, for Microseismic Monitoring, we detected and located 770 low-frequency events (5-50 Hz): (1) Shallow events are highly clustered, consistent with the pathway from injection well 13-10A to monitoring well; moment tensor inversion shows dominant tensile cracking; (2) Deep events are scattered and show migration pattern to the basement; moment tensors show that most events are shear cracks.

58 GEOSCIENCES↗

Spectral characteristics and the extent of paleosols of the Palouse formation

Spectral relationships were investigated for several bare soil fields which were in summer fallow rotation on the date of the imagery. Printouts of each band were examined and compared to aerial photography. Bands with dissimilar reflectance patterns for known areas were then combined using ratio techniques which were proven useful in other studies (Williams, 1983). Selected ratios were Thematic Mapper (TM) 1/TM4, TM3/TM4, and TM5/TM4. Cluster analyses and Baysian and Fastclass classifier images were produced using the three ratio images. Plots of cluster analysis outputs revealed distinct groupings of reflectance data representing green crops, ripened crops, soil and green plants, and bare soil. Bare soil was represented by a line of clusters on plots of the ratios TM5/TM4 and TM3/TM4. The soil line was investigated further to determine factors involved in the distributin of clusters alone the line. The clusters representing the bare soil line were also studied by plotting the Tm5/TM4, TM1/TM4 dimension. A total of 76 soil samples were gathered and analyzed for organic carbon.

Frazier, B. E.↗

A microstrip array feed for land mobile satellite reflector antennas

A circularly polarized feed array for a spacecraft reflector antenna is described that was constructed by using linearly polarized microstrip elements. The array has seven subarrays which form a single cluster as part of a large overlapping cluster reflector feed array. Each of the seven subarrays consists of four linearly polarized microstrip elements. The array achieved a better than 0.8-dB axial ratio at the array pattern peak and better than 3 dB antenna gain to 20 degrees from the peak, across a 7.5 percent frequency bandwidth. A teardrop-shaped feed probe was used to achieve wideband input impedance matching for the relatively thick microstrip substrate. The low impedance and axial ratio bandwidths were achieved using a relatively thick honeycomb substrate with the impedance-matching feed probes.

Huang, John↗

Measurement of Model Noise in a Hard-Wall Wind Tunnel

Identification, analysis, and control of fluid-mechanically-generated sound from models of aircraft and automobiles in special low-noise, semi-anechoic wind tunnels are an important research endeavor. Such studies can also be done in aerodynamic wind tunnels that have hard walls if phased microphone arrays are used to focus on the noise-source regions and reject unwanted reflections or background noise. Although it may be difficult to simulate the total flyover or drive-by noise in a closed wind tunnel, individual noise sources can be isolated and analyzed. An acoustic and aerodynamic study was made of a 7-percent-scale aircraft model in a NASA Ames 7-by-10-ft (about 2-by-3-m) wind tunnel for the purpose of identifying and attenuating airframe noise sources. Simulated landing, takeoff, and approach configurations were evaluated at Mach 0.26. Using a phased microphone array mounted in the ceiling over the inverted model, various noise sources in the high-lift system, landing gear, fins, and miscellaneous other components were located and compared for sound level and frequency at one flyover location. Numerous noise-alleviation devices and modifications of the model were evaluated. Simultaneously with acoustic measurements, aerodynamic forces were recorded to document aircraft conditions and any performance changes caused by geometric modifications. Most modern microphone-array systems function in the frequency domain in the sense that spectra of the microphone outputs are computed, then operations are performed on the matrices of microphone-signal cross-spectra. The entire acoustic field at one station in such a system is acquired quickly and interrogated during postprocessing. Beam-forming algorithms are employed to scan a plane near the model surface and locate noise sources while rejecting most background noise and spurious reflections. In the case of the system used in this study, previous studies in the wind tunnel have identified noise sources up to 19 dB below the normal background noise of the wind tunnel. Theoretical predictions of array performance are used to minimize the width and the side lobes of the beam pattern of the microphone array for a given test arrangement. To capture flyover noise of the inverted model, a 104-element microphone array in a 622-mm-diameter cluster was installed in a 19-mm-thick poly(methyl methacrylate) plate in the ceiling of the test section of the wind tunnel above the aircraft model (see Figure 1). The microphones were of the condenser type, and their diaphragms were mounted flush in the array plate, which was recessed 12.7 mm into the ceiling and covered by a porous aromatic polyamide cloth (not shown in the figure) to minimize boundary-layer noise. This design caused the level of flow noise to be much less than that of flush-mount designs. The drawback of this design was that the cloth attenuated sound somewhat and created acoustic resonances that could grow to several dB at a frequency of 10 kHz.

Soderman, Paul T.↗

The Solar Wind as a Laboratory for the Study of Magnetofluid Turbulence

The solar wind is the Sun's exosphere. As the solar atmosphere expands into interplanetary space, it is accelerated and heated. Data from spacecraft located throughout the heliosphere have revealed that this exosphere has velocities of several hundred kilometers/sec, densities at Earth orbit of about 5 particles/cm(exp 3), and an entrained magnetic field that at Earth orbit that is about 5 X 10(exp 5) Gauss. A fascinating feature of this magnetized plasma, which is a gas containing both charged particles and magnetic field, is that the magnetic field fluctuates in a way that is highly reminiscent of "Alfven waves", first defined by Hannes Alfven in 1942. Such waves have the defining property that the fluctuating magnetic fields are aligned with fluctuations in the velocity of the plasma and that, when properly normalized, the fluctuations have equal magnitudes. The observed alignment is not perfect and the resulting mismatch leads to a variety of complex interactions. In many respects, the flow patterns appear to be an example of fully developed magnetofluid turbulence. Recently, the dissipation range of this turbulence has been revealed by Search Coil magnetometer data from the four Cluster spacecraft. This tutorial will describe some of the properties of the large-scale and small-scale turbulence.

Goldstein, Melvyn L.↗