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To achieve a better understanding of the dominant loss mechanisms for the rapid dropouts of radiation belt electrons, three distinct radiation belt dropout events observed by Van Allen Probes are comprehensively investigated. For each event, observations of the pitch angle distribution of electron fluxes and electromagnetic ion cyclotron (EMIC) waves are analyzed to determine the effects of atmospheric precipitation loss due to pitch angle scattering induced by EMIC waves. Last closed drift shells (LCDS) and magnetopause standoff position are obtained to evaluate the effects of magnetopause shadowing loss. Evolution of electron phase space density (PSD) versus L* profiles and the μ and K (first and second adiabatic invariants) dependence of the electron PSD drops are calculated to further analyze the dominant loss mechanisms at different L*. Our findings suggest that these radiation belt dropouts can be classified into distinct classes in terms of dominant loss mechanisms: magnetopause shadowing dominant, EMIC wave scattering dominant, and combination of both mechanisms. Different from previous understanding, our results show that magnetopause shadowing can deplete electrons at L* 4. Compared to the magnetopause standoff position, it is more reliable to use LCDS to evaluate the impact of magnetopause shadowing. The evolution of electron PSD versus L* profile and the μ, K dependence of electron PSD drops can provide critical and credible clues regarding the mechanisms responsible for electron losses at different L* over the outer radiation belt.

The most significant unknown regarding relativistic electrons in Earth's outer Van Allen radiation belt is the relative contribution of loss, transport, and acceleration processes within the inner magnetosphere. Detangling each individual process is critical to improve the understanding of radiation belt dynamics, but determining a single component is challenging due to sparse measurements in diverse spatial and temporal regimes. However, there are currently an unprecedented number of spacecraft taking measurements that sample different regions of the inner magnetosphere. With the increasing number of varied observational platforms, system dynamics can begin to be unraveled. In this work, we employ in situ measurements during the 13–14 January 2013 enhancement event to isolate transport, loss, and source dynamics in a one-dimensional radial diffusion model. We then validate the results by comparing them to Van Allen Probes and Time History of Events and Macroscale Interactions during Substorms observations, indicating that the three terms have been accurately and individually quantified for the event. Finally, a direct comparison is performed between the model containing event-specific terms and various models containing terms parameterized by geomagnetic index. Models using a simple 3/Kp loss time scale show deviation from the event-specific model of nearly 2 orders of magnitude within 72 h of the enhancement event. However, models using alternative loss time scales closely resemble the event-specific model.

We present simulations of the outer radiation belt electron flux during the March 2015 and March 2013 storms using a radial diffusion model. Despite differences in Dst intensity between the two sto...

Since 2000, Los Alamos National Laboratory (LANL) Combined X-ray and Dosimeter (CXD) and Burst Detector Dosimeter for Block II-R (BDD-IIR) instruments have been fielded on Global Positioning System (GPS) satellites. Today, 21 of the 31 operational GPS satellites are equipped with a CXD detector and a further 2 carry a BDD-IIR. Each of these instruments measures a wide range of energetic electrons and protons. These data have now been publicly released under the terms of the Executive Order for Coordinating Efforts to Prepare the Nation for Space Weather Events. The specific goal of releasing space weather data from the GPS satellites is to enable broad scientific community engagement in enhancing space weather model validation and improvements in space weather forecasting and situational awareness. The time period covered by this data release is approximately 16 years, which corresponds to more than 167 satellite years of data. As a result, the large number of GPS satellites, distributed over six orbital planes, will provide important context for ongoing and historical science missions, as well as enabling new types of research not previously possible.

Mechanisms for electron injection, trapping, and loss in the near‐Earth space environment are investigated during the October 2012 “double‐dip” storm using our ring current‐atmosphere interactions model with self‐consistent magnetic field (RAM‐SCB). Pitch angle and energy scattering are included for the first time in RAM‐SCB using L and magnetic local time (MLT)‐dependent event‐specific chorus wave models inferred from NOAA Polar‐orbiting Operational Environmental Satellites (POES) and Van Allen Probes Electric and Magnetic Field Instrument Suite and Integrated Science observations. The dynamics of the source (approximately tens of keV) and seed (approximately hundreds of keV) populations of the radiation belts simulated with RAM‐SCB is compared with Van Allen Probes Magnetic Electron Ion Spectrometer observations in the morning sector and with measurements from NOAA 15 satellite in the predawn and afternoon MLT sectors. We find that although the low‐energy (E< 100 keV) electron fluxes are in good agreement with observations, increasing significantly by magnetospheric convection during both SYM‐H dips while decreasing during the intermediate recovery phase, the injection of high‐energy electrons is underestimated by this mechanism throughout the storm. Local acceleration by chorus waves intensifies the electron fluxes at E≥50 keV considerably, and RAM‐SCB simulations overestimate the observed trapped fluxes by more than an order of magnitude; the precipitating fluxes simulated with RAM‐SCB are weaker, and their temporal and spatial evolutions agree well with POES/Medium Energy Proton and Electron Detectors data., Key Points First RAM‐SCB simulations with 2‐D (MLT‐ and L‐dependent) event‐specific chorus wave models inferred from LEO and RBSP dataThe measured low‐energy trapped and precipitating electron fluxes are well reproduced by magnetospheric convectionLocal acceleration by chorus waves intensifies the electron fluxes at energies E greater than approximately 50 keV and overestimates observations

Geoelectromagnetic disturbances (GMDs) are an important consequence of space weather that can directly impact many types of terrestrial infrastructure. In this paper, we analyze 30 years of SuperMAG magnetometer data from the range of magnetic latitudes 20°≤λ≤75° to derive characteristic latitudinal profiles for median GMD amplitudes. Based on this data, we obtain a parameterization of these latitudinal profiles of different types of GMDs, providing an analytical fit with Dst-dependent parameters. We also obtain probabilistic estimates for the magnitudes of “100 year” GMDs, finding that B = 6.9 (3.60–12.9) nT/s should be expected at 45°≤λ < 50°, exceeding the 5 nT/s threshold for dangerous inductive heating.

As electromagnetic ion cyclotron (EMIC) waves may play an important role in radiation belt dynamics, there has been a push to better include them into global simulations. How to best include EMIC wave effects is still an open question. Recently many studies have attempted to parameterize EMIC waves and their characteristics by geomagnetic indices. However, this does not fully take into account important physics related to the phase of a geomagnetic storm. In this paper we first consider how EMIC wave occurrence varies with the phase of a geomagnetic storm and the SYM-H, AE, and Kp indices. We show that the storm phase plays an important role in the occurrence probability of EMIC waves. The occurrence rates for a given value of a geomagnetic index change based on the geomagnetic condition. In this study we also describe the typical plasma and wave parameters observed in L and magnetic local time for quiet, storm, and storm phase. These results are given in a tabular format in the supporting information so that more accurate statistics of EMIC wave parameters can be incorporated into modeling efforts.

The 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.

Computational analysis has become ubiquitous within the heliophysics community. However, community standards for peer-review of codes and analysis have lagged behind these developments. This absence has contributed to the reproducibility crisis, where inadequate analysis descriptions and loss of scientific data have made scientific studies difficult or impossible to replicate. The heliophysics community has responded to this challenge by expressing a desire for a more open, collaborative set of analysis tools. This article summarizes the current state of these efforts and presents an overview of many of the existing Python heliophysics tools. It also outlines the challenges facing community members who are working towards the goal of an open, collaborative, Python heliophysics toolkit and presents guidelines that can ease the transition from individualistic data analysis practices to an accountable, communalistic environment., Comment: Published in JGR

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. A full two-way coupling of physics-based models across multiple scales, including a global MHD (BATS-R-US) embedding a particle-in-cell (iPIC3D) and an inner magnetosphere (RAM-SCB) codes, is achieved. New data assimilation techniques employing in situ satellite data are developed; these provide an order of magnitude improvement in the accuracy in the simulation of the SCE. SHIELDS also includes a post-processing tool designed to calculate the surface charging for specific spacecraft geometry using the Curvilinear Particle-In-Cell (CPIC) code that can be used for reanalysis of satellite failures or for satellite design.

Energetic electron observations in Earth's radiation belts are typically sparse, and multipoint studies often rely on serendipitous conjunctions. This paper establishes the scientific utility of the Combined X-ray Dosimeter (CXD), currently flown on 19 satellites in the Global Positioning System (GPS) constellation, by cross-calibrating energetic electron measurements against data from the Van Allen Probes. By breaking our cross calibration into two parts—one that removes any spectral assumptions from the CXD flux calculation and one that compares the energy spectra—we first validate the modeled instrument response functions, then the calculated electron fluxes. Unlike previous forward modeling of energetic electron spectra, we use a combination of four distributions that together capture a wide range of observed spectral shapes. Moreover, our two-step approach allowed us to identify, and correct for, small systematic offsets between block IIR and IIF satellites. Using the Magnetic Electron Ion Spectrometer and Relativistic Electron-Proton Telescope on Van Allen Probes as a “gold standard,” here we demonstrate that the CXD instruments are well understood. A robust statistical analysis shows that CXD and Van Allen Probes fluxes are similar and the measured fluxes from CXD are typically within a factor of 2 of Van Allen Probes at energies inline image4 MeV.more » Our team present data from 17 CXD-equipped GPS satellites covering the 2015 “St. Patrick's Day” geomagnetic storm to illustrate the scientific applications of such a high data density satellite constellation and therefore demonstrate that the GPS constellation is positioned to enable new insights in inner magnetospheric physics and space weather forecasting.« less

A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented. The optimization method minimizes a cost function-tau-that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performed in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in vertical bar B vertical bar was reduced from 4.54% to 3.84%. The difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization. Plain Language Summary We present a method for comparing and optimizing the accuracy of commonly used empirical models that reproduce the Earth's magnetic field for altitudes ranging from a thousand to hundreds of thousands of kilometers. This method uses magnetic field data from satellites orbiting the planet to create a "penalty function" and uses an optimization algorithm to minimize this function and find the model input parameters that produce the best results for a given date and time. Our results show that these models can be improved by the use of satellite data. The model known as TS04 produced the best results after the optimization procedure generating a smaller error in 57.3% of the points in our data set when compared to the standard (unoptimized) inputs. The optimized TS04 also outperformed the best unoptimized model by 56.2%. The differences among all the models analyzed are usually not very large; however, the unoptimized models can have very large errors, which are much reduced by the optimization.

Relationships exist between radiation belt electron flux intensities and solar drivers such as solar wind speed, ion density, and magnetic fields. The particulars of these relationships, however, are not well understood. Many forecasting models have been developed in the last 25 years, attempting to make sense of these relationships and produce accurate forecasts for electron flux intensities. We discuss some of the inherent limitations that many forecasting models (e.g., static models) possess when trying to untangle the intricate and dynamic relationships between electron flux levels and solar wind drivers. Dynamics related to the solar cycle limit physical interpretations for static forecasting models to customized and narrow time windows. Furthermore, the interrelatedness of solar drivers severely limit the ability to uniquely partition and describe the relationship between any one solar driver with electron flux levels. We suggest an alternate approach using dynamic linear models (DLMs). DLMs avoid some of the inherent limitations of physical understanding static models possess. We compare the 1 day ahead forecast accuracy of a relatively simple DLM to the current NOAA relativistic electron forecast model (REFM). The REFM does produce a more favorable prediction efficiency averaged across years when compared to the relatively simple DLM (0.749 to 0.721). However, the competitiveness of the DLM suggests that further development may lead to more accurate and interpretable models in the future.

The DREAM3D diffusion model is applied to Van Allen Probes observations of the fast dropout and strong enhancement of MeV electrons during the October 2012 “double-dip” storm. We show that in order to explain the very different behavior in the two “dips,” diffusion in all three dimensions (energy, pitch angle, and L*) coupled with data-driven, event-specific inputs, and boundary conditions is required. Specifically, we find that outward radial diffusion to the solar wind-driven magnetopause, an event-specific chorus wave model, and a dynamic lower-energy seed population are critical for modeling the dynamics. In contrast, models that include only a subset of processes, use statistical wave amplitudes, or rely on inward radial diffusion of a seed population, perform poorly. The results illustrate the utility of the high resolution, comprehensive set of Van Allen Probes' measurements in studying the balance between source and loss in the radiation belt, a principal goal of the mission.

We expanded our previous work on L* neural networks that used empirical magnetic field models as the underlying models by applying and extending our technique to drift shells calculated from a physics-based magnetic field model. While empirical magnetic field models represent an average, statistical magnetospheric state, the RAM-SCB model, a first-principles magnetically self-consistent code, computes magnetic fields based on fundamental equations of plasma physics. Unlike the previous L* neural networks that include McIlwain L and mirror point magnetic field as part of the inputs, the new L* neural network only requires solar wind conditions and the Dst index, allowing for an easier preparation of input parameters. This new neural network is compared against those previously trained networks and validated by the tracing method in the International Radiation Belt Environment Modeling (IRBEM) library. The accuracy of all L* neural networks with different underlying magnetic field models is evaluated by applying the electron phase space density (PSD)-matching technique derived from the Liouville's theorem to the Van Allen Probes observations. Results indicate that the uncertainty in the predicted L* is statistically (75%) below 0.7 with a median value mostly below 0.2 and the median absolute deviation around 0.15, regardless of the underlying magnetic field model. We found that such an uncertainty in the calculated L* value can shift the peak location of electron phase space density (PSD) profile by 0.2 RE radially but with its shape nearly preserved.

On 30 September 2012, a flux “dropout” occurred throughout Earth's outer electron radiation belt during the main phase of a strong geomagnetic storm. Using eight spacecraft from NASA's Time History of Events and Macroscale Interactions during Substorms (THEMIS) and Van Allen Probes missions and NOAA's Geostationary Operational Environmental Satellites constellation, we examined the full extent and timescales of the dropout based on particle energy, equatorial pitch angle, radial distance, and species. We calculated phase space densities of relativistic electrons, in adiabatic invariant coordinates, which revealed that loss processes during the dropout were > 90% effective throughout the majority of the outer belt and the plasmapause played a key role in limiting the spatial extent of the dropout. THEMIS and the Van Allen Probes observed telltale signatures of loss due to magnetopause shadowing and subsequent outward radial transport, including similar loss of energetic ring current ions. However, Van Allen Probes observations suggest that another loss process played a role for multi-MeV electrons at lower L shells (L*

We have recently conducted a statistical survey on pitch angle distributions of energetic electrons trapped in the Earth's outer radiation belt, and a new empirical model was developed based upon survey results. This model—relativistic electron pitch angle distribution (REPAD)—aims to present statistical pictures of electron equatorial pitch angle distributions, instead of the absolute flux levels, as a function of energy, L shell, magnetic local time, and magnetic activity. To quantify and facilitate this statistical survey, we use Legendre polynomials to fit long-term in situ directional fluxes observed near the magnetic equator from three missions: CRRES, Polar, and LANL-97A. As the first of this kind of model, REPAD covers the whole outer belt region, providing not only the mean and median pitch angle distributions in the area but also error estimates of the average distributions. Preliminary verification and validation results demonstrate the reliable performance of this model. Usage of REPAD is mainly to predict the full pitch angle distribution of fluxes along a given magnetic field line, or even on a given drift shell, based upon one single unidirectional or omnidirectional flux measurement anywhere on that field line. This can be particularly useful for data assimilation, which usually has large tolerance on data errors. In addition, relatively small variations in pitch angle distributions measured at L shell between ~ 4 and 5 justify the assumption of fixed pitch angle distributions at GPS equatorial crossings (L ~ 4.2) used in our previous studies.

Drastic variations of Earth's outer radiation belt electrons ultimately result from various competing source, loss, and transport processes, to which wave-particle interactions are critically important. Using 15 spacecraft including NASA's Van Allen Probes, THEMIS, and SAMPEX missions and NOAA's GOES and POES constellations, we investigated the evolution of the outer belt during the strong geomagnetic storm of 30 September to 3 October 2012. This storm's main phase dropout exhibited enhanced losses to the atmosphere at L* 1 MeV electrons and energetic protons, SAMPEX >1 MeV electrons, and ground observations of band-limited Pc1-2 wave activity, we show that this sudden loss was consistent with pitch angle scattering by electromagnetic ion cyclotron waves in the dusk magnetic local time sector at 3 300 nT, and energetic electron injections and whistler-mode chorus waves were observed throughout the inner magnetosphere for >12 h. After this period, Bz turned northward, and injections, chorus activity, and enhancements in PSD ceased. Overall, the outer belt was depleted by this storm. From the unprecedented level of observations available, we show direct evidence of the competitive nature of different wave-particle interactions controlling relativistic electron fluxes in the outer radiation belt.

Energetic radiation belt electron fluxes can undergo sudden dropouts in response to different solar wind drivers. Many physical processes contribute to the electron flux dropout, but their respective roles in the net electron depletion remain a fundamental puzzle. Some previous studies have qualitatively examined the importance of magnetopause shadowing in the sudden dropouts either from observations or from simulations. While it is difficult to directly measure the electron flux loss into the solar wind, radial diffusion codes with a fixed boundary location (commonly utilized in the literature) are not able to explicitly account for magnetopause shadowing. The exact percentage of its contribution has therefore not yet been resolved. To overcome these limitations and to determine the exact contribution in percentage, we carry out radial diffusion simulations with the magnetopause shadowing effect explicitly accounted for during a superposed solar wind stream interface passage, and quantify the relative contribution of the magnetopause shadowing coupled with outward radial diffusion by comparing with GPS-observed total flux dropout. Results indicate that during high-speed solar wind stream events, which are typically preceded by enhanced dynamic pressure and hence a compressed magnetosphere, magnetopause shadowing coupled with the outward radial diffusion can explain about 60–99% of the main-phase radiation belt electron depletion near the geosynchronous orbit. While the outer region (L* > 5) can nearly be explained by the above coupled mechanism, additional loss mechanisms are needed to fully explain the energetic electron loss for the inner region (L* &leq; 5). While this conclusion confirms earlier studies, our quantification study demonstrates its relative importance with respect to other mechanisms at different locations.

[1] Phase Space Density (PSD) matching can be used to identify the presence of nonadiabatic processes, evaluate accuracy of magnetic field models, or to cross-calibrate instruments. Calculating PSD in adiabatic invariant coordinates requires a global specification of the magnetic field. For a well specified global magnetic field, nonadiabatic processes or inadequate cross calibration will give a poor PSD match. We have calculated PSD(μ, K) for both Van Allen Probes using a range of models and compare these PSDs at conjunctions in L* (for given μ, K). We quantitatively assess the relative goodness of each model for radiation belt applications. We also quantify the uncertainty in the model magnetic field magnitude and the related uncertainties in PSD, which has applications for modeling and particle data without concurrent magnetic field measurements. Using this technique, we show the error in PSD for an energy spectrum observed by the relativistic electron-proton telescope (REPT) is a factor of ∼1.2 using the TS04 model.

The radiation belts and plasma in the Earth’s magnetosphere pose hazards to satellite systems which restrict design and orbit options with a resultant impact on mission performance and cost. For decades the standard space environment specification used for spacecraft design has been provided by the NASA AE8 and AP8 trapped radiation belt models. There are well-known limitations on their performance, however, and the need for a new trapped radiation and plasma model has been recognized by the engineering community for some time. To address this challenge a new set of models, denoted AE9/AP9/SPM, for energetic electrons, energetic protons and space plasma has been developed. The new models offer significant improvements including more detailed spatial resolution and the quantification of uncertainty due to both space weather and instrument errors. Fundamental to the model design, construction and operation are a number of new data sets and a novel statistical approach which captures first order temporal and spatial correlations allowing for the Monte-Carlo estimation of flux thresholds for user-specified percentile levels (e.g., 50th and 95th) over the course of the mission. An overview of the model architecture, data reduction methods, statistics algorithms, user application and initial validation is presented in this paper.

It is well-known that there are many wave-particle interaction processes which have the potential to affect the dynamics of the radiation belts [see e.g., the review by Mauk et al., 2013]. The issue that has continued to obstruct significant advances in our understanding of the radiation belts to the point of predictability is our ability to represent the nature of the magnetospheric processes controlling belt dynamics with sufficient accuracy to establish which dominate. In relation to the case examined here it is to determine which process or processes can act to create a third Van Allen radiation belt morphology in September 2012 as reported by Baker et al., (2013). As described in the main text of our Reply, and further expanded upon in the Supplementary Material presented here, we show that the original conclusion from Mann et al. (2016) remains valid. That is, a remnant belt and the third radiation belt morphology which arises following a subsequent flux recovery at higher L-shells, can be explained by the action of very fast outwards ULF wave radial diffusion associated with magnetopause shadowing. Contrary to the claims of the Comment by Shprits et al. (2017; hereafter S17), and the conclusions of modelling by Shprits et al. (2013; hereafter S13), the action of EMIC waves is not required.

Energetic ions observed in the cusp have been explained as a result of processes within the magnetosphere, but also proposed as a driver of some of those same processes. This study assesses potential connections between energetic ions observed in the cusp and geomagnetic storm and substorm activity. These connections may suggest sources of cusp energetic particles (CEPs), or imply effects of these particles on magnetospheric dynamics. We identify CEPs from six years of cusp crossings by the Polar satellite, relating them to storm and substorm onsets. CEPs showed no significant dependence on storms but did show a weak, statistically significant, increase after substorm onsets. CEPs had no significant association with subsequent storm or substorm onsets. We conclude that substorm acceleration may contribute to CEPs but CEPs are unlikely to contribute to global magnetospheric dynamics.

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 (

Recent observations of magnetospheric dynamics driven by interaction with both high-speed solar wind streams (HSSs) and interplanetary coronal mass ejections (ICMEs) have shown periodic substorms to be common under strong driving, but with different periods of ∼ 4 and 2–3 h, respectively. However, it is unclear what causes these substorms and what determines their periodicity. Observations during the passage of a corotating interaction region preceding a high-speed stream are presented here and the observed enhancements in the AE index are shown to be a quasi-periodic sequence of substorms. The occurrence times of these substorms and the variation of the AL index are shown to be consistent with a simple loading–unloading model without the need for external triggers. A possible explanation is given for the lengthening of the inter-substorm period during HSS relative to that of sawtooth events during ICMEs.

Geospace can be defined as the region of near-Earth space dominated by the Earth’s, rather than the Sun’s, magnetic field. The terrestrial magnetosphere forms a cavity in the interplanetary medium that partially shields our planet from cosmic rays, solar energetic protons and numerous other

This special issue of the Journal of Atmospheric and Solar-Terrestrial Physics is devoted to research into high speed solar wind streams (HSSs) and their effects on the region of near-Earth space commonly known as ‘geospace’. Interest in the effects of HSSs has increased during the last solar cycle and, following the successful meeting focusing on corotating solar wind streams in Manaus, Brazil (Tsurutani et al., 2006), we recognised the need for further work on the topic, with particular focus on HSSs and their effects in the inner magnetosphere, ionosphere, and neutral atmosphere. As a result the High Speed Solar Wind Streams and Geospace Interactions (HSS–GI) Workshop was held at Hilltop, St. Martin's College in Ambleside, UK, from 2 to 7 September, 2007 (Kavanagh and Denton, 2007; Denton et al., 2008 M.H. Denton, J.E. Borovsky, R.B. Horne, R.L. McPherron, S.K. Morley and B.T. Tsurutani, High speed solar wind streams: a call for key research, EOS Trans. AGU 89 (7) (2008), pp. 62–63. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (7)Denton et al., 2009), sponsored by the Department of Communication Systems at Lancaster University. The majority of the work presented in this special issue was prompted by discussion and interaction at the workshop. It is indeed an indication of the importance of HSSs that the papers in this issue cover the entire region from the Sun and solar wind, through the magnetosphere, and into the ionosphere, thermosphere, and down to the stratosphere. It is hoped that this research will stimulate more understanding, appreciation, and research, into these important drivers of physical phenomena within geospace.

Local Acceleration How the electrons trapped in Earth-encircling Van Allen radiation belts get accelerated has been debated since their discovery in 1958. Reeves et al. (p. 991 , published online 25 July) used data from the Van Allen Radiation Belt Storm Probes, launched by NASA on 30 August 2012, to discover that radiation belt electrons are accelerated locally by wave-particle interactions, rather than by radial transport from regions of weaker to stronger magnetic fields.

Dynamics of the E Geophysical Mon © 2012. American 10.1029/2012GM Recent studies have shown how trapped energetic radiation belt electron fluxes rapidly “drop out” during small geomagnetic disturbances triggered by the arrival of a solar wind stream interface (SWSI). In the current study, we use satellite and ground-based observations to describe the significance of energetic electron precipitation (EEP) and direct magnetopause shadowing loss mechanisms, both of which have been suggested as possible causes of the dropouts. Superposed epoch analysis of low-Earth-orbiting Polar-Orbiting Environmental Satellites (POES) spacecraft observations indicate that neither “classic” magnetopause shadowing nor EEP appear able to explain the dropouts. However, SWSI-triggered dropouts in trapped flux are followed ~3 h later by large increases of EEP, which start as the trapped electron fluxes begin to recover and may be signatures of the acceleration process, which rebuilds the trapped fluxes. Ground-based observations indicate typical >30 keV EEP flux magnitudes of ~8 10 electrons cm 2 sr 1 s . While these are ~10 times larger than the equivalent precipitating fluxes measured by POES, this is consistent with the small viewing window of the POES telescopes.

The Dynamic Radiation Environment Assimilation Model (DREAM) was developed to provide accurate, global specification of the Earth's radiation belts and to better understand the physical processes that control radiation belt structure and dynamics. DREAM is designed using a modular software approach in order to provide a computational framework that makes it easy to change components such as the global magnetic field model, radiation belt dynamics model, boundary conditions, etc. This paper provides a broad overview of the DREAM model and a summary of some of the principal results to date. We describe the structure of the DREAM model, describe the five major components, and illustrate the various options that are available for each component. We discuss how the data assimilation is performed and the data preprocessing and postprocessing that are required for producing the final DREAM outputs. We describe how we apply global magnetic field models for conversion between flux and phase space density and, in particular, the benefits of using a self-consistent, coupled ring current–magnetic field model. We discuss some of the results from DREAM including testing of boundary condition assumptions and effects of adding a source term to radial diffusion models. We also describe some of the testing and validation of DREAM and prospects for future development.

We review and develop techniques to determine associations between series of discrete events. The bootstrap, a nonparametric statistical method, allows the determination of the significance of associations with minimal assumptions about the underlying processes. We find the key requirement for this method: one of the series must be widely spaced in time to guarantee the theoretical applicability of the bootstrap. If this condition is met, the calculated significance passes a reasonableness test. We conclude with some potential future extensions and caveats on the applicability of these methods. The techniques presented have been implemented in a Python-based software toolkit.

[1] Thirty years ago Paulikas and Blake (1979) showed a remarkable correlation between geosynchronous relativistic electron fluxes and solar wind speed (Vsw). This seminal result has been a foundation of radiation belt studies, space weather forecasting, and current understanding of solar wind radiation belt coupling. We have repeated their analysis with a considerably longer-running data set (1989–2010) from the Los Alamos National Laboratory energetic particle instruments with several surprising results. Rather than the roughly linear correlation between Vsw and log (flux), our results show a triangle-shaped distribution in which fluxes have a distinct velocity-dependent lower limit but a velocity-independent upper limit. The highest-electron fluxes can occur for any value of Vsw with no indication of a Vsw threshold. We also find a distinct solar cycle dependence with the triangle-shaped distribution evident in 2 declining phase years dominated by high-speed streams but essentially no correlation in 2 solar maximum years. For time periods that do show a triangle-shaped distribution we consider whether it can be explained by scatter due to other parameters. We examine the role of time dependence and time lag in producing the observed distribution. We also look at the same statistical relationship but at energies ≪1 MeV. We conclude that the relationship between radiation belt electron fluxes and solar wind velocity is substantially more complex than suggested by previous statistical studies. We find that there are important ways in which the “conventional wisdom” stating that high-velocity wind drives high-MeV electron fluxes is, in general, either misleading or unsupported.

[1] Electromagnetic ion cyclotron (EMIC) waves may contribute to ring current ion and radiation belt electron losses, and theoretical studies suggest these processes may be most effective during the main phase of geomagnetic storms. However, ground-based signatures of EMIC waves, Pc1–Pc2 geomagnetic pulsations, are observed more frequently during the recovery phase. We investigate the association of EMIC waves with various storm phases in case and statistical studies of 22 geomagnetic storms over 1996–2003, with an associated Dst < −30 nT. High-resolution data from the GOES 8, 9, and 10 geosynchronous satellite magnetometers provide information on EMIC wave activity in the 0–1 Hz band over ±3 days with respect to storm onset, defined as commencement of the negative excursion of Dst. Thirteen of 22 storms showed EMIC waves occurring during the main phase. In case studies of two storms, waves were seen with higher intensity in the main phase in one and the recovery phase in the other. Power spectral densities up to 500 nT2 Hz−1 were similar in prestorm, storm, and early recovery phases. Superposed epoch analysis of the 22 storms shows 78% of wave events during the main phase occurred in the He+ band. After storm onset the main phase contributed only 29% of events overall compared to 71% during recovery phase, up to 3 days. Some differences between storms were found to be dependent on the solar wind driver. Plasma plumes or an inflated plasmasphere may contribute to enhancing EMIC wave activity at geosynchronous orbit.

[1] A rapid loss of energetic (>230 keV) electrons from the outer radiation belt was observed with the GPS constellation between 1430 and 1730 UTC on 7 May 2007. The rapid loss occurred from 4 < L* < 6 over all measured energies above 230 keV. Currently accepted rapid loss mechanisms include magnetopause shadowing and/or outward diffusion, and precipitation to the atmosphere due to wave-particle interactions. Here the loss timescale is ∼2 hr, and the magnetopause is near L = 8, which requires unrealistically high outward diffusion rates. Current estimates of the loss timescales associated with EMIC waves, plasmaspheric hiss and whistler-mode chorus are too long, even in combination, to explain the observed losses inside L* ≃ 6.

Superposed epoch analyses have shown that, on average, the interplanetary magnetic field (IMF) turns northward close to substorm onset. This has been commonly accepted as evidence for the substorm onset being triggered by a rapid northward turning of the IMF. Here we show that the tendency arises in any superposed epoch analysis of the IMF in which event onset is biased to occur for southward IMF, irrespective of a coincident rapid northward turning of the IMF. The overall IMF variation found in the largest superposed epoch analysis of this kind is also well reproduced using a Minimal Substorm Model in which substorm onsets are determined without the requirement of a northward IMF turning trigger. We discuss the explanation underlying these results and conclude that there is no conclusive evidence in favour of the hypothesis that substorm onsets are triggered by a rapid northward turning of the IMF. Citation: Freeman, M. P., and S. K. Morley (2009), No evidence for externally triggered substorms based on superposed epoch analysis of IMF B-z, Geophys. Res. Lett., 36, L21101, doi: 10.1029/2009GL040621.

[1] Coordinated observations from GOES-9, DMSP F-13, and Chokurdakh (CHD) have shown concurrent Pc1-2 band wave activity in the late afternoon sector, close to 16 MLT. The left-hand polarization of the waves in space indicates that these are electromagnetic ion cyclotron (EMIC) waves. In the region of field line conjunction, DMSP also observed 6–30 keV energy ion precipitation. We have examined the propagation of the EMIC waves from the magnetosphere to the ionosphere using both time series analysis and a 2-D magnetohydrodynamic model. Our analysis suggests that the EMIC are generated by interactions with cold plasma within a drainage plume, consistent with theory, and that the waves primarily propagate earthward along geomagnetic field lines at the eastward (outer) edge of the plume.

The images taken by the Heliospheric Imagers (HIs), part of the SECCHI imaging package onboard the pair of STEREO spacecraft, provide information on the radial and latitudinal evolution of the plasma compressed inside corotating interaction regions (CIRs). A plasma density wave imaged by the HI instrument onboard STEREO-B was found to propagate towards STEREO-A, enabling a comparison between simultaneous remote-sensing and in situ observations of its structure to be performed. In situ measurements made by STEREO-A show that the plasma density wave is associated with the passage of a CIR. The magnetic field compressed after the CIR stream interface (SI) is found to have a planar distribution. Minimum variance analysis of the magnetic field vectors shows that the SI is inclined at 54° to the orbital plane of the STEREO-A spacecraft. This inclination of the CIR SI is comparable to the inclination of the associated plasma density wave observed by HI. A small-scale magnetic cloud with a flux rope topology and radial extent of 0.08 AU is also embedded prior to the SI. The pitch-angle distribution of suprathermal electrons measured by the STEREO-A SWEA instrument shows that an open magnetic field topology in the cloud replaced the heliospheric current sheet locally. These observations confirm that HI observes CIRs in difference images when a small-scale transient is caught up in the compression region.

[1] We re-examine whether substorms are triggered by solar wind fluctuations or an internal magnetospheric instability by comparing the statistical associations between substorm onsets and (1) an external trigger definition, (2) a simple internal trigger definition of only prior loading of solar wind energy that is a subset of the external trigger definition. Statistical associations are calculated both for observed substorm onsets and onsets generated by a Minimal Substorm Model in which substorms are purely internally triggered. Thence we argue that a minimum interval of prior loading is a necessary condition for substorm onset, a subsequent northward IMF turning is not necessary, and consequently that an internal trigger from a magnetospheric instability is a necessary and sufficient condition for substorm onset. We discuss how this result may explain a report that externally triggered substorms are systematically larger than non-externally triggered substorms.

We compare the probability distributions of substorm magnetic bay magnitudes from observations and a minimal substorm model. The observed distribution was derived previously and independently using the IL index from the IMAGE magnetometer network. The model distribution is derived from a synthetic AL index time series created using real solar wind data and a minimal substorm model, which was previously shown to reproduce observed substorm waiting times. There are two free parameters in the model which scale the contributions to AL from the directly-driven DP2 electrojet and loading-unloading DP1 electrojet, respectively. In a limited region of the 2-D parameter space of the model, the probability distribution of modelled substorm bay magnitudes is not significantly different to the observed distribution. The ranges of the two parameters giving acceptable (95% confidence level) agreement are consistent with expectations using results from other studies. The approximately linear relationship between the two free parameters over these ranges implies that the substorm magnitude simply scales linearly with the solar wind power input at the time of substorm onset.

[1] An image of the dayside low-energy ion outflow event that occurred on 16 December 2003 was constructed with ground- and space-based GPS (Global Positioning System) Total Electron Content (TEC) data and ion drift meter data from the DMSP (Defense Meteorological Satellite Program). A tomographic reconstruction technique has been applied to the GPS TEC data obtained from the GPS receiver on the Low Earth Orbit (LEO) satellite FedSat. The two dimensional tomographic image of the topside ionosphere and plasmasphere reveals a spectacular beam-like dayside ion outflow emanating from the cusp region. The transverse components of the magnetic field in FedSat's NewMag data show the presence of field aligned current (FAC) sheets, indicating the existence of low-energy electron precipitation in the cusp region. The DMSP ion drift data show upward ion drift velocities and upward fluxes of low-energy ions and electrons at the orbiting height of the DMSP spacecraft in the cusp region. This study presents the first tomographic image of the flux tube structure of ionospheric ion outflows from 0.13 Re up to 3.17 Re altitude.