Space science deals with the bodies within the solar system and the interplanetary medium; the primary focus is on atmospheres and above-at Earth the short timescale variation in the the geomagnetic field, the Van Allen radiation belts and the deposition of energy into the upper atmosphere are key areas of investigation. SpacePy is a package for Python, targeted at the space sciences, that aims to make basic data analysis, modeling and visualization easier. It builds on the capabilities of the well-known NumPy and matplotlib packages. Publication quality output direct from analyses is emphasized. The SpacePy project seeks to promote accurate and open research standards by providing an open environment for code development. In the space physics community there has long been a significant reliance on proprietary languages that restrict free transfer of data and reproducibility of results. By providing a comprehensive library of widely-used analysis and visualization tools in a free, modern and intuitive language, we hope that this reliance will be diminished for non-commercial users. SpacePy includes implementations of widely used empirical models, statistical techniques used frequently in space science (e.g. superposed epoch analysis), and interfaces to advanced tools such as electron drift shell calculations for radiation belt studies. SpacePy also provides analysis and visualization tools for components of the Space Weather Modeling Framework including streamline tracing in vector fields. Further development is currently underway. External libraries, which include well-known magnetic field models, high-precision time conversions and coordinate transformations are accessed from Python using ctypes and f2py. The rest of the tools have been implemented directly in Python. The provision of open-source tools to perform common tasks will provide openness in the analysis methods employed in scientific studies and will give access to advanced tools to all space scientists, currently distribution is limited to non-commercial use.

We provide the first ever characterization of the primary modes of ionospheric Hall and Pedersen conductance variability as empirical orthogonal functions (EOFs). These are derived from six satellite years of Defense Meteorological Satellite Program (DMSP) particle data acquired during the rise of solar cycles 22 and 24. The 60 million DMSP spectra were each processed through the Global Airlglow Model. Ours is the first large‐scale analysis of ionospheric conductances completely free of assumption of the incident electron energy spectra. We show that the mean patterns and first four EOFs capture ∼50.1 and 52.9% of the total Pedersen and Hall conductance variabilities, respectively. The mean patterns and first EOFs are consistent with typical diffuse auroral oval structures and quiet time strengthening/weakening of the mean pattern. The second and third EOFs show major disturbance features of magnetosphere‐ionosphere (MI) interactions: geomagnetically induced auroral zone expansion in EOF2 and the auroral substorm current wedge in EOF3. The fourth EOFs suggest diminished conductance associated with ionospheric substorm recovery mode. We identify the most important modes of ionospheric conductance variability. Our results will allow improved modeling of the background error covariance needed for ionospheric assimilative procedures and improved understanding of MI coupling processes.

We present simulations of the outer radiation belt electron flux during the March 2015 and 2013 storms using a radial diffusion model. Despite differences in disturbance short‐time intensity between the two storms, the response of the ultra‐relativistic electrons in the outer radiation belt was remarkably similar, both showing a sudden drop in the electron flux followed by a rapid enhancement in the outer belt flux to levels over an order of magnitude higher than those observed during the pre‐storm interval. Simulations of the ultra‐relativistic electron flux during the March 2015 storm show that outward radial diffusion can explain the flux dropout down to L*~4. However, in order to reproduce, the observed flux dropout at L* < 4 requires the addition of a loss process characterized by an electron lifetime of around 1 hr operating below L*~3.5 during the flux dropout interval. Nonetheless, during the pre‐storm and recovery phase of both storms, the radial diffusion simulation reproduces the observed flux dynamics. For the March 2013 storm, the flux dropout across all L‐shells is reproduced by outward radial diffusion activity alone. However, during the flux enhancement interval at relativistic energies, there is evidence of a growing local peak in the electron phase space density at L*~3.8, consistent with local acceleration such as by very low frequency chorus waves. Overall, the simulation results for both storms can accurately reproduce the observed electron flux only when event specific radial diffusion coefficients are used, instead of the empirical diffusion coefficients derived from ultra‐low frequency wave statistics.

Abstract. Some studies over the last decade have indicated that the instability responsible for substorm expansion phase onset may require an external trigger such as a northward turning of the interplanetary magnetic field (IMF). Statistical investigations have lead to contrasting interpretations regarding the relationship between proposed solar wind triggers and substorm onsets identified from geomagnetic data. We therefore present the results of a study into the possible triggering of 260 substorms between 2001-2005, exploiting data from the Cluster and IMAGE satellite missions. We find that only a small fraction (<25%) of the substorms studied are associated with northward turnings of the IMF. However, the majority of the observed onsets are associated with a growth phase characterised using a subset of the criteria employed to define northward-turning IMF triggers. Based upon a case-by-case investigation and the results of an analysis using the statistics of point processes, we conclude that northward-turning structures in the IMF, while sometimes coinciding with the initial phase of individual substorms, are not required to trigger the magnetospheric instability associated with substorm expansion phase onset.

This report reviews existing literature describing forecast accuracy metrics, concentrating on those based on relative errors and percentage errors. We then review how the most common of these metrics, the mean absolute percentage error (MAPE), has been applied in recent radiation belt modeling literature. Finally, we describe metrics based on the ratios of predicted to observed values (the accuracy ratio) that address the drawbacks inherent in using MAPE. Specifically we define and recommend the median log accuracy ratio as a measure of bias and the median symmetric accuracy as a measure of accuracy.

The arrival of high‐speed solar wind streams (HSSs) at the Earth's magnetopause drives particle and wave phenomena that are distinct from the phenomena caused by other solar wind structures. Although HSS events do not generally produce a particularly strong ring current (the current caused by ions and electrons drifting around the Earth), they do produce storm levels of other magnetospheric phenomena (enhanced convection, heating, precipitation, relativistic electron energization, and so forth) that can persist for an extended time period (e.g., many days). These events contrast with interplanetary coronal mass ejection (ICME) events, where more transient driving (e.g., 1 day) is the norm. As such, the energy input to the magnetosphere during HSS events is comparable to, or may exceed, the energy input to the magnetosphere during ICME events.

Halford et al: Application Usability LevelsThe space physics community continues to grow and become both more interdisciplinary and more intertwined with commercial and government operations. This has created a need for a framework to easily identify what projects can be used for specific applications and how close the tool is to routine autonomous or on-demand implementation and operation. We propose the Application Usability Level (AUL) framework and publicizing AULs to help the community quantify the progress of successful applications, metrics, and validation efforts. This framework will also aid the scientific community by supplying the type of information needed to build off of previously published work and publicizing the applications and requirements needed by the user communities. In this paper, we define the AUL framework, outline the milestones required for progression to higher AULs, and provide example projects utilizing the AUL framework. This work has been completed as part of the activities of the Assessment of Understanding and Quantifying Progress working group which is part of the International Forum for Space Weather Capabilities Assessment.The existing frameworks each focus on tracking a particular type of product, and so do not fully meet the needs of the heliophysics community. Space physics products include observational data, derived indices, modeled outputs, and more. These products are often used together for different purposes. Each user will have different requirements for the application in terms of the type of product, robustness, and accuracy.The unique needs of the space weather community led to the modification of existing research-to-application communication frameworks to create the Application Usability Level (AUL) framework. Applying AULs to model and data analysis efforts can benefit space physics research. These benefits include improving access to collaborators, project transparency, and communication of project results. As the requirements and user interests for each application are unique, the AUL framework uses specifically-tuned metrics. For instance, a research user interested in upper atmospheric coupling may want to know the flux and characteristic energy of precipitating electrons. Similarly, a satellite industry partner may want to predict satellite drag during a geomagnetic storm. A single research project may be able to provide both users with the products they need. However, the different outputs will require different metrics, implementation strategies, and time frames for implementation. Since the AUL framework is highly adaptable, it can help a single research project meet and track both of these user needs.The AUL framework can bolster communication between researchers, users, funding bodies, and stakeholders. Using a standard framework provides a clear path for users and researchers to follow. This improves efficiency assuring that all components from the researchers' project to the user needs are considered. It enables communication about a proposal's dev...

Predicting variations in the near-Earth space environment that can lead to spacecraft damage and failure is one example of "space weather" and a big space physics challenge. A project recently funded through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program aims at developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to understand the dynamics of the surface charging environment (SCE), the hot (keV) electrons representing the source and seed populations for the radiation belts, on both macro-and micro-scale. Important physics questions related to particle injection and acceleration associated with magnetospheric storms and substorms, as well as plasma waves, are investigated. These challenging problems are addressed using a team of world-class experts in the fields of space science and computational plasma physics, and state-of-the-art models and computational facilities.