Physics

The anisotropy of solar wind turbulence is a critical issue in understanding the physics of energy transfer between scales and energy conversion between fields and particles in the heliosphere. Using the measurement of \emph{Parker Solar Probe} (\emph{PSP}), we present an observation of the anisotropy at kinetic scales in the slow, Alfvénic, solar wind in the inner heliosphere. \textbf{The magnetic compressibility behaves as expected for kinetic Alfvénic turbulence below the ion scale.} A steepened transition range is found between the inertial and kinetic ranges in all directions with respect to the local background magnetic field direction. The anisotropy of k ????k ??is found evident in both transition and kinetic ranges, with the power anisotropy P ??/ P ??>10 in the kinetic range leading over that in the transition range and being stronger than that at 1 au. The spectral index varies from α t??=??.7±1.0 to α t??=??.7±0.3 in the transition range and α k??=??.12±0.22 to α k??=??.57±0.09 in the kinetic range. The corresponding wavevector anisotropy has the scaling of k ????k 0.71±0.17 ??in the transition range, and changes to k ????k 0.38±0.09 ??in the kinetic range, consistent with the kinetic Alfvénic turbulence at sub-ion scales.

The magnetic fields of interplanetary coronal mass ejections (ICMEs), which originate close to the Sun in the form of a flux rope, determine their geoeffectiveness. Therefore, robust flux rope-based models of CMEs are required to perform magnetohydrodynamic (MHD) simulations aimed at space weather predictions. We propose a modified spheromak model and demonstrate its applicability to CME simulations. In this model, such properties of a simulated CME as the poloidal and toroidal magnetic fluxes, and the helicity sign can be controlled with a set of input parameters. We propose a robust technique for introducing CMEs with an appropriate speed into a background, MHD solution describing the solar wind in the inner heliosphere. Through a parametric study, we find that the speed of a CME is much more dependent on its poloidal flux than on the toroidal flux. We also show that the CME speed increases with its total energy, giving us control over its initial speed. We further demonstrate the applicability of this model to simulations of CME-CME collisions. Finally, we use this model to simulate the 12 July 2012 CME and compare the plasma properties at 1 AU with observations. The predicted CME properties agree reasonably with observational data.

The paper presents an assessment of the performances of the global empirical models: International Reference Ionosphere (IRI)-2016 and the NeQuick2 model derived ionospheric Total Electron Content (TEC) with respect to the Navigation with Indian Constellation (NavIC)/ Indian Regional Navigation Satellite System(IRNSS) estimated TEC under geomagnetic storm conditions. The present study is carried out over Indore (Geographic: 22.52 ∘ N 75.92 ∘ E and Magnetic Dip: 32.23 ∘ N, located close to the northern crest of the Equatorial Ionization Anomaly (EIA) region of the Indian sector). Analysis has been performed for an intense storm (September 6-10, 2017), a moderate storm (September 26-30, 2017) and a mild storm (January 17-21, 2018) that fall in the declining phase of the present solar cycle. It is observed that both IRI-2016 and NeQuick2 derived TEC are underestimates when compared with the observed TEC from NavIC and therefore fail to predict storm time changes in TEC over this region and requires real data inclusion from NavIC for better prediction over the variable Indian longitude sector.

As a result of intense solar activity during the first ten days of September, a ground level enhancement occurred on September 10, 2017. Here we computed the effective dose rates in the polar region at several altitudes during the event using the derived rigidity spectra of the energetic solar protons. The contribution of different populations of energetic particles viz. galactic cosmic rays and solar protons, to the exposure is explicitly considered and compared. We also assessed the exposure of a crew members/passengers to radiation at different locations and at several cruise flight altitudes and calculated the received doses for two typical intercontinental flights. The estimated received dose during a high-latitude, 40 kft, ∼ 10 h flight is ∼ 100 μ Sv.

Lightning was detected by Voyager 2 at Uranus and Neptune, and weaker electrical processes also occur throughout planetary atmospheres from galactic cosmic ray (GCR) ionisation. Lightning is an indicator of convection, whereas electrical processes away from storms modulate cloud formation and chemistry, particularly if there is little insolation to drive other mechanisms. The ice giants appear to be unique in the Solar System in that they are distant enough from the Sun for GCR-related mechanisms to be significant for clouds and climate, yet also convective enough for lightning to occur. This paper reviews observations (both from Voyager 2 and Earth), data analysis and modelling, and considers options for future missions. Radio, energetic particle and magnetic instruments are recommended for future orbiters, and Huygens-like atmospheric electricity sensors for in situ observations. Uranian lightning is also expected to be detectable from terrestrial radio telescopes.

The coupled attitude and orbit dynamics of solar sails is studied. The shape of the sail is a simplified quasi-rhombic-pyramid that provides the structure helio-stablility properties. After adimensionalisation, the system is put in the form of a fast-slow dynamical system where the different time scales are explicitely related to the physical parameters of the system. The orientation of the body frame with respect to the inertial orbit frame is a fast phase that can be averaged out. This gives rise to a simplified formulation that only consists of the orbit dynamics perturbed by a flat sail with fixed attitude perpendicular to the direction of the sunlight. The results are exemplified using numerical simulations.

Although mass and energy in Jupiter's magnetosphere mostly come from the innermost Galilean moon Io's volcanic activities, solar wind perturbations can play crucial roles in releasing the magnetospheric energy and powering aurorae in Jupiter's polar regions. The systematic response of aurora to solar wind compression remains poorly understood. Here we report the analysis of a set of auroral images with contemporaneous in situ magnetopause detections. We distinguish two types of auroral enhancements: a transient localized one and a long-lasting global one. We show that only the latter systematically appears under a compressed magnetopause, while the localized auroral expansion could occur during an expanded magnetopause. Moreover, we directly examine previous theories on how solar wind compressions enhance auroral emissions. Our results demonstrate that auroral morphologies can be diagnostic of solar wind conditions at planets when in situ measurements are not possible.

We suggest that pairing of bouncing medium-energy electrons in the auroral upward current region close to the mirror points may play a role in driving the electron cyclotron maser instability to generate an escaping narrow band fine structure in the auroral kilometric radiation. We treat this mechanism in the gyrotron approximation, for simplicity using the extreme case of a weakly relativistic Dirac distribution instead the more realistic anisotropic Jüttner distribution. Promising estimates of bandwidth, frequency drift and spatial location are given.

Even though automatic classification and interpretation would be highly desired features for the Magnetospheric Multiscale mission (MMS), the gold rush era in machine learning has yet to reach the science done with observations collected by MMS. We investigate the properties of the ion sky maps produced by the Dual Ion Spectrometers (DIS) from the Fast Plasma Investigation (FPI). Running the Principal Component Analysis (PCA) on a mixed subset of the data suggests that more than 500 components are needed to cover 80% of the variance. Hence, simple machine learning techniques might not deal with classification of plasma regions. Use of a three-dimensional (3D) convolutional autoencoder (3D-CAE) allows to reduce the data dimensionality by 128 times while still maintaining a decent quality energy distribution. However, k-means clustering computed over the compressed data is not capable of separating measurements according to the physical properties of the plasma. A three-dimensional convolutional neural network (3D-CNN), trained on a rather small amount of human labelled training examples is able to predict plasma regions with 99% accuracy. The low probability predictions of the 3D-CNN reveal the mixed state regions, such as the magnetopause or bow shock, which are of key interest to researchers of the MMS mission. The 3D-CNN and data processing software could easily be deployed on ground-based computers and provide classification for the whole MMS database. Data processing through the trained 3D-CNN is fast and efficient, opening up the possibility for deployment in data-centers or in situ operation onboard the spacecraft.

We propose a new method of the automated identification of current sheets (CSs) that represents a formalization of the visual inspection approach employed in case studies. CSs are often identified by eye via the analysis of characteristic changes in the interplanetary magnetic field (IMF) and plasma parameters. Known visual and semi-automated empirical methods of CS identification are exact but do not allow a comprehensive statistical analysis of CS properties. Existing automated methods partially solve this problem. Meanwhile, these methods suggest an analysis of variations of the IMF and its direction only. In our three-parameter empirical method, we employ both the solar wind plasma and IMF parameters to identify CSs of various types. Derivatives of the IMF strength, the plasma beta and the ratio of the Alfv'en speed VA to the solar wind speed V taken with the one-second cadence are used. We find that the CS daily rate R correlates with the solar wind temperature T rather than with V and is proportional to the sum of the kinetic and thermal energy density ~ V2(N+5N')+10T(N+N'), where N'=2cm^-3 is the background level of the solar wind density N. Maxima of R are associated with stream/corotating interaction regions and interplanetary mass ejection sheaths. A multiyear list of CSs identified at 1 AU can be found at this https URL