Magnetospheric convection electric field dynamics and stormtime particle energization: Case study of the magnetic storm of 4 May 1998

It is shown that narrow channels of high electric field are an effective mechanism for injecting plasma into the inner magnetosphere. Analytical expressions for the electric field cannot produce these channels of intense plasma flow, and thus, result in less entry and adiabatic energization of the plasma sheet into near-Earth space. For the ions, omission of these channels leads to an underprediction of the strength of the stormtime ring current and therefore, an underestimation of the geoeffectiveness of the storm event. For the electrons, omission of these channels leads to the inability to create a seed population of 10-100 keV electrons deep in the inner magnetosphere. These electrons can eventually be accelerated into MeV radiation belt particles. To examine this, the 1-7 May 1998 magnetic storm is studied with a plasma transport model by using three different convection electric field models: Volland-Stern, Weimer, and AMIE. It is found that the AMIE model can produce particle fluxes that are several orders of magnitude higher in the <i>L</i> = 2 – 4 range of the inner magnetosphere, even for a similar total cross-tail potential difference. <br><br><b>Key words.</b> Space plasma physics (charged particle motion and acceleration) – Magnetospheric physics (electric fields, storms and substorms

Editorial honoring the 2018 reviewers for JGR Space Physics

The Editors of the Journal of Geophysical Research Space Physics would like to honor and thank the 2018 manuscript reviewers for the journal. This is a large‐scale, community‐wide effort for which 1,358 scientists submitted 3,027 reviews in 2018. We understand that this is a volunteer task and we greatly appreciate your time and effort to fulfill this service role back to the research community

Predicting geostationary 40–150 keV electron flux using ARMAX (an autoregressive moving average transfer function), RNN (a Recurrent Neural Network), and logistic regression: a comparison of models

We screen several algorithms for their ability to produce good predictive models of hourly 40–150 keV electron flux at geostationary orbit (data from GOES-13) using solar wind, Interplanetary Magnetic Field, and geomagnetic index parameters that would be available for real time forecasting. Value-predicting models developed using ARMAX (autoregressive moving average transfer function), RNN (recurrent neural network), or stepwise-reduced regression produced roughly similar results. Including magnetic local time as a categorical variable to describe both the differing levels of flux and the differing influence of parameters improved the models (r as high as 0.814; Heidke Skill Score (HSS) as high as 0.663), however value-predicting models did a poor job at predicting highs and lows. Diagnostic tests are introduced (cubic fit to observation-prediction relationship and Lag1 correlation) that better assess predictions of extremes than single metrics such as root mean square error, mean absolute error, or median symmetric accuracy. Classifier models (RNN and logistic regression) were equally able to predict flux rise above the 75th percentile (HSS as high as 0.667). Logistic regression models were improved by the addition of multiplicative interaction and quadratic terms. Only predictors from 1 or 3 hr before were necessary and a detailed description of flux time series behavior was not needed. Stepwise selection of these variables trimmed non-contributing parameters for a more parsimonious and portable logistic regression model that predicted as well as neural network-derived models. We provide a logistic regression model (LL3: LogisticLag3) based on inputs measured 3 hr previous, along with optimal probability thresholds, for future predictions

Recommendations for Next‐Generation Ground Magnetic Perturbation Validation

Data‐model validation of ground magnetic perturbation forecasts, specifically of the time rate of change of surface magnetic field, dB/dt, is a critical task for model development and for mitigation of geomagnetically induced current effects. While a current, community‐accepted standard for dB/dt validation exists (Pulkkinen et al., 2013), it has several limitations that prevent more complete understanding of model capability. This work presents recommendations from the International Forum for Space Weather Capabilities Assessment Ground Magnetic Perturbation Working Team for creating a next‐generation validation suite. Four recommendations are made to address the existing suite: greatly expand the number of ground observatories used, expand the number of events included in the suite from six to eight, generate metrics as a function of magnetic local time, and generate metrics as a function of activity type. For each of these, implementation details are explored. Limitations and future considerations are also discussed.Plain Language SummarySpace weather forecast models of magnetic field perturbations are important for protecting the power grid and other vulnerable infrastructure. These models must be validated by comparing their predictions to observations. This paper makes recommendations for how future models should be validated in order to best test their capabilities.Key PointsWe present a new validation suite for models of ground magnetic perturbations, dB/dt, of interest for geomagnetically induced currentsThe existing standard remains useful but provides limited information, so an expanded set of metrics is defined hereThis work is a result of the International Forum for Space Weather Capabilities Assessment and represents a new community consensusPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147786/1/swe20777_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147786/2/swe20777.pd

The Earth: Plasma Sources, Losses, and Transport Processes

This paper reviews the state of knowledge concerning the source of magnetospheric plasma at Earth. Source of plasma, its acceleration and transport throughout the system, its consequences on system dynamics, and its loss are all discussed. Both observational and modeling advances since the last time this subject was covered in detail (Hultqvist et al., Magnetospheric Plasma Sources and Losses, 1999) are addressed