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This study exploits the volumetric sampling capabilities of the Resolute Bay Incoherent Scatter Radar (RISR-N) in collaboration with all-sky imagery and in-situ measurements (DMSP) to examine the i...

We report one of the first comprehensive ground-based investigations of energy transfer rates in the E-region ionosphere compared relative to geomagnetic activity, seasonal effects, and solar activ...

Joule heating deposits a significant amount of energy into the high-latitude ionosphere and is an important factor in many magnetosphere-ionosphere-thermosphere coupling processes. Although the int...

Key Points: 8 • E region energy transfer rates are estimated from PFISR measurements for the 9 first time. 10 • The electromagnetic energy transfer rate and the Joule heating rate are larger in 11 ...

Recent attention has been given to mesoscale phenomena across geospace (∼10 s km to 500 km in the ionosphere or ∼0.5 RE to several RE in the magnetosphere), as their contributions to the system global response are important yet remain uncharacterized mostly due to limitations in data resolution and coverage as well as in computational power. As data and models improve, it becomes increasingly valuable to advance understanding of the role of mesoscale phenomena contributions—specifically, in magnetosphere-ionosphere coupling. This paper describes a new method that utilizes the 2D array of Time History of Events and Macroscale Interactions during Substorms (THEMIS) white-light all-sky-imagers (ASI), in conjunction with meridian scanning photometers, to estimate the auroral scale sizes of intense precipitating energy fluxes and the associated Hall conductances. As an example of the technique, we investigated the role of precipitated energy flux and average energy on mesoscales as contrasted to large-scales for two back-to-back substorms, finding that mesoscale aurora contributes up to ∼80% (∼60%) of the total energy flux immediately after onset during the early expansion phase of the first (second) substorm, and continues to contribute ∼30–55% throughout the remainder of the substorm. The average energy estimated from the ASI mosaic field of view also peaked during the initial expansion phase. Using the measured energy flux and tables produced from the Boltzmann Three Constituent (B3C) auroral transport code (Strickland et al., 1976; 1993), we also estimated the 2D Hall conductance and compared it to Poker Flat Incoherent Scatter Radar conductance values, finding good agreement for both discrete and diffuse aurora.

Following substorm auroral onset, the active aurora region usually expands poleward toward the poleward auroral boundary. Such poleward expansion is often associated with a bulge region that expands westward and forms the westward travelling surge (WTS). In this paper we show all-sky imager and Poker Flat Advanced Modular Incoherent Scatter Radar (PFISR) radar observations of two surge events to investigate the relationship between the surge and flow from the polar cap. For both events, we observe auroral streamers, with an adjacent flow channel consisting of decreased density and cool electron temperature plasma flowing equatorward. This flow channel appears to impinge and lead/feed surge formation, and to stay connected to the surge as it moves westward. Also, for both events, streamer observations indicate that, following initial surge development, similar flows led to explosive surge enhancements. The observation that the streamers connected to the auroral polar boundary and that the flow channels consisted of low density, low electron temperature plasma indicates that the impinging plasma came from the polar cap. For both events, the altitude variations of F region plasma within the surges are related with aurora emission and the poleward/equatorward flow, and the surges develop strong auroral streamers that initiate along the poleward auroral boundary when contacted with flow from the polar cap. These results suggest that the polar cap flow channels play a crucial role in auroral surges by feeding low entropy plasma into surge initiation and development, and also playing an important role in the dynamics within a surge.

The Reproducible Software Environment (Resen) is an open-source software tool enabling computationally reproducible scientific results in the geospace science community. Resen was developed as part of a larger project called the Integrated Geoscience Observatory (InGeO), which aims to help geospace researchers bring together diverse datasets from disparate instruments and data repositories, with software tools contributed by instrument providers and community members. The main goals of InGeO are to remove barriers in accessing, processing, and visualizing geospatially resolved data from multiple sources using methodologies and tools that are reproducible. The architecture of Resen combines two mainstream open source software tools, Docker and JupyterHub, to produce a software environment that not only facilitates computationally reproducible research results, but also facilitates effective collaboration among researchers. In this technical paper, we discuss some challenges for performing reproducible science and a potential solution via Resen, which is demonstrated using a case study of a geospace event. Finally we discuss how the usage of mainstream, open-source technologies seems to provide a sustainable path towards enabling reproducible science compared to proprietary and closed-source software.

Sudden commencement (SC) induced by solar wind pressure enhancement can produce significant global impact on the coupled magnetosphere-ionosphere (MI) system, and its effects have been studied extensively using ground magnetometers and coherent scatter radars. However, very limited observations have been reported about the effects of SC on the ionospheric plasma. Here we report detailed Poker Flat Incoherent Scatter Radar (PFISR) observations of the ionospheric response to SC during the 17 March 2015 storm. PFISR observed lifting of the F region ionosphere, transient field-aligned ion upflow, prompt but short-lived ion temperature increase, subsequent F region density decrease, and persistent electron temperature increase. A global magnetohydrodynamic (MHD) simulation has been carried out to characterize the SC-induced current, convection, and magnetic perturbations. Simulated magnetic perturbations at Poker Flat show a satisfactory agreement with observations. The simulation provides a global context for linking localized PFISR observations to large-scale dynamic processes in the MI system.

Time domain signal processing techniques are employed by the Super Dual Auroral Radar Network (SuperDARN) to obtain bulk measurements of the velocity and spectral width of F region ionospheric plasma irregularities. The measurements are obtained by fitting estimates of the mean autocorrelation function (ACF) of the radar target. To accurately and consistently extract target parameters from the mean unnormalized ACF, it is necessary to utilize error-weighted fitting algorithms with a weight given by the variance of the ACF. Currently implemented weights are ad hoc, and a detailed description of the statistical characterization of SuperDARN ACFs is needed. Following the discussions in Farley (1969) and Woodman and Hagfors (1969), which describe the variance for the mean normalized ACF used with incoherent scatter radars, we present analytic expressions for obtaining the variance of the real and imaginary components of the mean unnormalized SuperDARN ACF. These expressions are based on models by Andre et al. (1999) and Moorcroft (2004) of the voltage signal received by SuperDARN radars but may be used for other soft target radar systems. An algorithm for obtaining the variance of both the magnitude and phase of the mean ACF is also presented. The results of this study may be directly integrated into existing SuperDARN data analysis software and other pulse-Doppler radar systems that utilize estimates of the mean unnormalized ACF.

Thermal ion retarding potential analyzers (RPAs) are used to measure in situ auroral ionospheric plasma parameters. This article analyzes data from a low-resource RPA in order to quantify the capability of the sensor. The RPA collects a sigmoidal current-voltage (I-V) curve, which depends on a non-linear combination of Maxwellian plasma parameters, so a forward-modeling procedure is used to match the best choice plasma parameters for each I-V curve. First, the procedure is used, given constraining information about the flow moment, to find scalar plasma parameters-ion temperature, ion density, and spacecraft sheath potential-for a single I-V curve interpreted in the context of a Maxwellian plasma distribution. Second, two azimuthally separated I-V curves from a single sensor on the spinning spacecraft are matched, given constraining information on density and sheath potential, to determine the bulk plasma flow components. These flows are compared to a high-fidelity, high-resource flow diagnostic. In both cases, the procedure's sensitivity to variations in constraining diagnostics is tested to ensure that the matching procedure is robust. Finally, a standalone analysis is shown, providing plasma scalar and flow parameters using known payload velocity and International Reference Ionosphere density as input information. The results show that the sensor can determine scalar plasma measurements as designed, as well as determine plasma DC flows to within hundreds of m/s error compared to a high-fidelity metric, thus showing their capability to replace higher-resource methods for determining DC plasma flows when coarse-resolution measurements at in situ spatial scales are suitable.

Autocorrelation function (ACF) estimates from voltage data measured by high-frequency ionospheric radar systems that utilize the multiple-pulse technique of Farley (1972) are susceptible to interference from self-clutter. Self-clutter is caused by simultaneous returns from multiple transmitted pulses echoing from unwanted, or ambiguous ranges. Without accurate estimates of self-clutter it is impossible to account for all the uncertainty in estimates of the radar ACF. Voltage- and power-based self-clutter estimators are presented and evaluated using a modified version of the radar data simulator of Ribeiro et al. (2013a) and data from the Super Dual Auroral Radar Network (SuperDARN). It is shown that self-clutter caused by ambiguous ranges filled with ground scatter can be accurately estimated using a voltage-based self-clutter estimator but that for ionospheric origin self-clutter a maximal estimator must be used. Two maximal self-clutter estimators are discussed and verified using the radar data simulator. A discussion of the application of the self-clutter estimator as it is applied to ACFs obtained with Saskatoon SuperDARN radar is also presented.

Joule heating in the ionosphere takes place through collisions between ions and neutrals. Statistical maps of F region Joule heating in the Northern Hemisphere polar ionosphere are derived from satellite measurements of thermospheric wind and radar measurements of ionospheric ion convection. Persistent mesoscale heating is observed near postnoon and postmidnight magnetic local time and centered around 70° magnetic latitude in regions of strong relative ion and neutral drift. The magnitude of the Joule heating is found to be largest during solar maximum and for a southeast oriented interplanetary magnetic field. These conditions are consistent with stronger ion convection producing a larger relative flow between ions and neutrals. The global-scale Joule heating maps quantify persistent (in location) regions of heating that may be used to provide a broader context compared to small-scale studies of the coupling between the thermosphere and ionosphere.

A Matlab-based finite-difference numerical solver for the Poisson equation for a rectangle and a disk in two dimensions, and a spherical domain in three dimensions, is presented. The solver is optimized for handling an arbitrary combination of Dirichlet and Neumann boundary conditions, and allows for full user control of mesh refinement. The solver routines utilize effective and parallelized sparse vector and matrix operations. Computations exhibit high speeds, numerical stability with respect to mesh size and mesh refinement, and acceptable error values even on desktop computers. Program summary Program title: FDMRP 1.0 Catalogue identifier: AENQ_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AENQ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License v3.0 No. of lines in distributed program, including test data, etc.: 102793 No. of bytes in distributed program, including test data, etc.: 369378 Distribution format: tar.gz Programming language: Matlab 2010a. Computer: PC, Macintosh. Operating system: Windows, OSX, Linux. RAM: 8 GB (8, 589, 934, 592 bytes) Classification: 4.3. Nature of problem: To solve the Poisson problem in a standard domain with “patchy surface”-type (strongly heterogeneous) Neumann/Dirichlet boundary conditions. Solution method: Finite difference with mesh refinement. Restrictions: Spherical domain in 3D; rectangular domain or a disk in 2D. Unusual features: Choice between mldivide/iterative solver for the solution of large system of linear algebraic equations that arise. Full user control of Neumann/Dirichlet boundary conditions and mesh refinement. Running time: Depending on the number of points taken and the geometry of the domain, the routine may take from less than a second to several hours to execute.

The narrow escape problem refers to the problem of calculating the mean first passage time (MFPT) needed for an average Brownian particle to leave a domain with an insulating boundary containing N small well-separated absorbing windows, or traps. This mean first passage time satisfies the Poisson partial differential equation subject to a mixed Dirichlet-Neumann boundary condition on the domain boundary, with the Dirichlet condition corresponding to absorbing traps. In the limit of small total trap size, a common asymptotic theory is presented to calculate the MFPT in two-dimensional domains and in the unit sphere. The asymptotic MFPT formulas depend on mutual trap locations, allowing for global optimization of trap locations. Although the asymptotic theory for the MFPT was developed in the limit of asymptotically small trap radii, and under the assumption that the traps are well-separated, a comprehensive study involving comparison with full numerical simulations shows that the full numerical and asymptotic results for the MFPT are within 1% accuracy even when total trap size is only moderately small, and for traps that may be rather close together. This close agreement between asymptotic and numerical results at finite, and not necessarily asymptotically small, values of the trap size clearly illustrates one of the key side benefits of a theory based on a systematic asymptotic analysis. In addition, for the unit sphere, numerical results are given for the optimal configuration of a collection of traps on the surface of a sphere that minimizes the average MFPT. The case of N identical traps and a pattern of traps with two different sizes are considered. The effect of trap fragmentation on the average MFPT is also discussed.