Abstract.During the solar wind dynamic pressure enhancement, around 0200 UT on January 11, 1997, at the end of the January 6-11 magnetic cloud event, the magnetopause was pushed inside geosynchronous orbit. The LANL 1994-084 and G MS 4 geosynchronous satellites crossed the magnetopause and moved into the magnetosheath. Also, the Geotail satellite was in the magnetosheath while the Interball i satellite observed magnetopause crossings. This event provides an excellent opportunity to test and validate the prediction capabilities and accuracy of existing models of the magnetopause location for producing space weather forecasts. In this paper, we compare predictions of two models: the Petrinec and Russell

An explicit function for the size and shape of the magnetopause, in terms of Dp and Bz, is obtained by using multiple parameter fitting in a form that is useful for operational space applications such as predicting when satellites at geosynchronous orbit will be found in the magnetosheath.

With the advent of the Heliophysics/Geospace System Observatory (H/GSO), a complement of multi-spacecraft missions and ground-based observatories to study the space environment, data retrieval, analysis, and visualization of space physics data can be daunting. The Space Physics Environment Data Analysis System (SPEDAS), a grass-roots software development platform ( www.spedas.org ), is now officially supported by NASA Heliophysics as part of its data environment infrastructure. It serves more than a dozen space missions and ground observatories and can integrate the full complement of past and upcoming space physics missions with minimal resources, following clear, simple, and well-proven guidelines. Free, modular and configurable to the needs of individual missions, it works in both command-line (ideal for experienced users) and Graphical User Interface (GUI) mode (reducing the learning curve for first-time users). Both options have “crib-sheets,” user-command sequences in ASCII format that can facilitate record-and-repeat actions, especially for complex operations and plotting. Crib-sheets enhance scientific interactions, as users can move rapidly and accurately from exchanges of technical information on data processing to efficient discussions regarding data interpretation and science. SPEDAS can readily query and ingest all International Solar Terrestrial Physics (ISTP)-compatible products from the Space Physics Data Facility (SPDF), enabling access to a vast collection of historic and current mission data. The planned incorporation of Heliophysics Application Programmer’s Interface (HAPI) standards will facilitate data ingestion from distributed datasets that adhere to these standards. Although SPEDAS is currently Interactive Data Language (IDL)-based (and interfaces to Java-based tools such as Autoplot), efforts are under-way to expand it further to work with python (first as an interface tool and potentially even receiving an under-the-hood replacement). We review the SPEDAS development history, goals, and current implementation. We explain its “modes of use” with examples geared for users and outline its technical implementation and requirements with software developers in mind. We also describe SPEDAS personnel and software management, interfaces with other organizations, resources and support structure available to the community, and future development plans. Electronic Supplementary Material The online version of this article (10.1007/s11214-018-0576-4) contains supplementary material, which is available to authorized users.

Strong enhancements of outer Van Allen belt electrons have been shown to have a clear dependence on solar wind speed and on the duration of southward interplanetary magnetic field. However, individual case study analyses also have demonstrated that many geomagnetic storms produce little in the way of outer belt enhancements and, in fact, may produce substantial losses of relativistic electrons. In this study, focused upon a key period in August–September 2014, we use GOES geostationary orbit electron flux data and Van Allen Probes particle and fields data to study the process of radiation belt electron acceleration. One particular interval, 13–22 September, initiated by a short‐lived geomagnetic storm and characterized by a long period of primarily northward interplanetary magnetic field (IMF), showed strong depletion of relativistic electrons (including an unprecedented observation of long‐lasting depletion at geostationary orbit) while an immediately preceding, and another immediately subsequent, storm showed strong radiation belt enhancement. We demonstrate with these data that two distinct electron populations resulting from magnetospheric substorm activity are crucial elements in the ultimate acceleration of highly relativistic electrons in the outer belt: the source population (tens of keV) that give rise to VLF wave growth and the seed population (hundreds of keV) that are, in turn, accelerated through VLF wave interactions to much higher energies. ULF waves may also play a role by either inhibiting or enhancing this process through radial diffusion effects. If any components of the inner magnetospheric accelerator happen to be absent, the relativistic radiation belt enhancement fails to materialize.

[1] In this paper we continue the community-wide rigorous modern space weather model validation efforts carried out within GEM, CEDAR and SHINE programs. In this particular effort, in coordination among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), modelers, and science community, we focus on studying the models' capability to reproduce observed ground magnetic field fluctuations, which are closely related to geomagnetically induced current phenomenon. One of the primary motivations of the work is to support NOAA SWPC in their selection of the next numerical model that will be transitioned into operations. Six geomagnetic events and 12 geomagnetic observatories were selected for validation. While modeled and observed magnetic field time series are available for all 12 stations, the primary metrics analysis is based on six stations that were selected to represent the high-latitude and mid-latitude locations. Events-based analysis and the corresponding contingency tables were built for each event and each station. The elements in the contingency table were then used to calculate Probability of Detection (POD), Probability of False Detection (POFD) and Heidke Skill Score (HSS) for rigorous quantification of the models' performance. In this paper the summary results of the metrics analyses are reported in terms of POD, POFD and HSS. More detailed analyses can be carried out using the event by event contingency tables provided as an online appendix. An online interface built at CCMC and described in the supporting information is also available for more detailed time series analyses.