The Swarm satellites offer an unprecedented opportunity for improving our knowledge about polar cap patches, which are regarded as the main space weather issue in the polar caps. We present a new ...robust algorithm that automatically detects polar cap patches using in situ plasma density data from Swarm. For both hemispheres, we compute the spatial and seasonal distributions of the patches identified separately by Swarm A and Swarm B between December 2013 and August 2016. We show a clear seasonal dependency of patch occurrence. In the Northern Hemisphere (NH), patches are essentially a winter phenomenon, as their occurrence rate is enhanced during local winter and very low during local summer. Although not as pronounced as in the NH, the same pattern is seen for the Southern Hemisphere (SH). Furthermore, the rate of polar cap patch detection is generally higher in the SH than in the NH, especially on the dayside at about 77° magnetic latitude. Additionally, we show that in the NH the number of patches is higher in the postnoon and prenoon sectors for interplanetary magnetic field (IMF) By<0 and IMF By>0, respectively, and that this trend is mirrored in the SH, consistent with the ionospheric flow convection. Overall, our results confirm previous studies in the NH, shed more light regarding the SH, and provide further insight into polar cap patch climatology. Along with this algorithm, we provide a large data set of patches automatically detected with in situ measurements, which opens new horizons in studies of polar cap phenomena.
Key Points
New polar cap patch detection method based on Swarm in situ data provides an unprecedented data set for polar cap patch statistical studies
Polar cap patch occurrence rate is highest during local winter in both hemispheres; in the south it is also significant during local summer
There is a clear IMF By dependency in the spatial distribution of polar cap patches, consistent with the ionospheric flow pattern
Context. Strong electron cooling on the neutral gas in cometary comae has been predicted for a long time, but actual measurements of low electron temperature are scarce. Aims. Our aim is to ...demonstrate the existence of cold electrons in the inner coma of comet 67P/Churyumov-Gerasimenko and show filamentation of this plasma. Methods. In situ measurements of plasma density, electron temperature and spacecraft potential were carried out by the Rosetta Langmuir probe instrument, LAP. We also performed analytical modelling of the expanding two-temperature electron gas. Results. LAP data acquired within a few hundred km from the nucleus are dominated by a warm component with electron temperature typically 5–10 eV at all heliocentric distances covered (1.25 to 3.83 AU). A cold component, with temperature no higher than about 0.1 eV, appears in the data as short (few to few tens of seconds) pulses of high probe current, indicating local enhancement of plasma density as well as a decrease in electron temperature. These pulses first appeared around 3 AU and were seen for longer periods close to perihelion. The general pattern of pulse appearance follows that of neutral gas and plasma density. We have not identified any periods with only cold electrons present. The electron flux to Rosetta was always dominated by higher energies, driving the spacecraft potential to order − 10 V. Conclusions. The warm (5–10 eV) electron population observed throughout the mission is interpreted as electrons retaining the energy they obtained when released in the ionisation process. The sometimes observed cold populations with electron temperatures below 0.1 eV verify collisional cooling in the coma. The cold electrons were only observed together with the warm population. The general appearance of the cold population appears to be consistent with a Haser-like model, implicitly supporting also the coupling of ions to the neutral gas. The expanding cold plasma is unstable, forming filaments that we observe as pulses.
The collected current by spherical and cylindrical Langmuir probes immersed in an unmagnetized and collisionless non-Maxwellian plasma at rest are theoretically studied, and analytical expressions ...for the currents of attracted and repelled plasma particles are presented. We consider Kappa, Cairns and the generalized Kappa-Cairns distributions as possible models for the velocity field in the plasma. The current-voltage characteristics curves are displayed and discussed. Furthermore, comparisons with the collected currents in Maxwellian plasmas are given. The results of Particle-in-Cell (PIC) simulations of spherical and cylindrical probes in non-Maxwellian plasmas are also presented, and compared with the theoretical expressions. The results for the collected currents by the Langmuir probes obtained by PIC simulations are in good agreement with the corresponding analytical expressions.
This paper presents a new efficient algorithm based on the spectral-Galerkin numerical approximations complemented by a magnetohydrodynamics–Boussinesq model and a new solver for studying the ...development of a Rayleigh–Taylor (RT) instability. We use the Shenfun computational framework in the Cartesian coordinates, which gives the spectral order and accuracy for the considered model based on the magnetohydrodynamics equations and the Boussinesq conjecture. The numerical simulations were conducted for each two- and three-dimensional case, both with and without an external static magnetic field. The validity of the numerical results was examined by comparing the calculated squared L2-norm of the density parameter with the linear stability analysis. We also examined the effects of a uniform tangential magnetic field on the onset and growth of an RT instability at different magnetic field strengths. The analysis of the effectiveness of the presented method suggests that it can be modified for further research on two-component plasma.
We study the spatial structure of a polarization jet/Sub‐Auroral Ion Drift (PJ/SAID) based on data from the NorSat‐1 and Swarm satellites during a geomagnetic storm. Observations of plasma parameters ...inside the PJ/SAID are obtained with NorSat‐1 using a system of Langmuir probes with a nominal sampling rate of up to 1 kHz, which allowed measurements with such a high temporal resolution for the first time. A comparative analysis of plasma parameters and electron density spectra inside PJ according to the data from both satellites is presented. Our results show that fluctuations of plasma parameters inside the PJ increase at all scales with increasing geomagnetic activity. Small‐scale irregularities in the PJ are measured in situ down to hundreds of meters. The role of large‐scale effects in the PJ increases in comparison with the small‐scale ones during high geomagnetic activity. The PJ consists of structures ∼0.2° latitude in size within which small‐scale irregularities are present.
Plain Language Summary
Polarization jet (PJ), also known as Sub‐Auroral Ion Drift (SAID), events are fast westward plasma drifts with a narrow latitudinal extent, occurring at subauroral latitudes in the Earth's ionosphere. The decrease in the density of the ionospheric plasma inside PJ/SAID significantly affects the conditions for the propagation of shortwave radio waves, which indicates the practical importance of studying this phenomenon. Despite the importance of using a variety of ground‐based observation facilities for studying and analyzing PJ/SAID properties, as well as developing analytical models and numerical modeling, in situ observations are the most valuable. Such in situ observations can be obtained only with satellites flying through a developing PJ/SAID. Large‐scale features of PJ/SAID are currently well understood, but small‐scale processes within PJ/SAID are practically not studied, and many open questions remain. In this work, we study the small‐scale structures in PJ/SAID during a geomagnetic storm of 20 April 2018, using multi‐instrumental approach involving low‐Earth orbit.
Key Points
Fluctuations of plasma parameters inside the polarization jet (PJ) increase at all scales during higher geomagnetic activity
Small‐scale irregularities inside the PJ are measured in situ down to hundreds of meters
The role of large‐scale effects in the PJ increases in comparison with small‐scale ones with geomagnetic activity
We develop an open source algorithm to apply Transfer learning to Aurora image classification and Magnetic disturbance Evaluation (TAME). For this purpose, we evaluate the performance of 80 ...pretrained neural networks using the Oslo Auroral THEMIS (OATH) data set of all‐sky images, both in terms of runtime and their features' predictive capability. From the features extracted by the best network, we retrain the last neural network layer using the Support Vector Machine (SVM) algorithm to distinguish between the labels “arc,” “diffuse,” “discrete,” “cloud,” “moon” and “clear sky/ no aurora”. This transfer learning approach yields 73% accuracy in the six classes; if we aggregate the 3 auroral and 3 non‐aurora classes, we achieve up to 91% accuracy. We apply our classifier to a new dataset of 550,000 images and evaluate the classifier based on these previously unseen images. To show the potential usefulness of our feature extractor and classifier, we investigate two test cases: First, we compare our predictions for the “cloudy” images to meteorological data and second we train a linear ridge model to predict perturbations in Earth's locally measured magnetic field. We demonstrate that the classifier can be used as a filter to remove cloudy images from datasets and that the extracted features allow to predict magnetometer measurements. All procedures and algorithms used in this study are publicly available, and the code and classifier are provided, which opens possibility for large scale studies of all‐sky images.
Plain Language Summary
In the interest of auroral research and space physics, many images capturing the night sky have been taken automatically over the last decades. Sifting through these images manually takes a lot of time and is generally impractical. We use Convolutional Neural Networks (CNN), which are good at image classification to extract a set of numbers per image (“features”) that capture the essential contents of the image. A Support Vector Machine (SVM) is trained to interpret these features and assign labels to the images. We search for the best configuration between different CNNs and SVMs and achieve up to 91% accuracy. To show that our method can be extended to other datasets, we classify half a million images from a different dataset and evaluate the performance of our classifier based on these results. We show that our classifier also excels at detecting clouds in images. It can therefore be used to filter unusable images from this kind of datasets. Based on the images' features, we create a model to predict disturbances in the Earth's local magnetic field. To enable other researches to work with our results, we use industry‐standard, open‐source software and make our algorithms and results available the same way.
Key Points
A pretrained feature extractor and a subsequent classifier can successfully detect aurora in all‐sky images
A validation on unknown, partially manually categorized images achieved a classification accuracy of 91%
We predict physical quantities such as magnetic disturbance and cloud height from the underlying image feature representation
Spacecraft‐plasma interactions are studied with self‐consistent numerical simulations of magnetized plasmas, where electrons are strongly magnetized whereas ions are weakly magnetized. It is found ...that for a spacecraft in such a magnetized plasma corresponding to a low Earth orbit, electrons can be reflected from a negatively charged spacecraft and then guided by geomagnetic field lines. The reflected electrons can leave a sharp trail like wings if the spacecraft size is greater than an average electron gyroradius of the environment. Such an electron wing‐like structure is associated with propagating Langmuir waves. This results in nontrivial asymmetric electrostatic potentials close to the spacecraft and even farther than the Debye screening distance. The convective electric field also gives rise to a differential potential of the spacecraft with respect to the plasma, resulting in yet another asymmetry in the plasma dynamics and the potential distribution around the spacecraft. These asymmetries in the plasma dynamics can significantly influence in‐situ measurements of space plasma. The results show a good qualitative agreement with actual measurements by a satellite in the polar regions.
Key Points
Electrons reflected at a negatively charged moving spacecraft form wing‐like density structures in a magnetized plasma
Electron wing‐like structures are characterized by the trail of field‐aligned propagation of Langmuir waves
Reflected electrons cause spurious electric fields that can be measured by double probes on a satellite
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