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This paper presents observations of electromagnetic ion cyclotron (EMIC) waves from multiple data sources during the four Geospace Environment Modeling challenge events in 2013 selected by the Geospace Environment Modeling Quantitative Assessment of Radiation Belt Modeling focus group: 17 and 18 March (stormtime enhancement), 31 May to 2 June (stormtime dropout), 19 and 20 September (nonstorm enhancement), and 23–25 September (nonstorm dropout). Observations include EMIC wave data from the Van Allen Probes, Geostationary Operational Environmental Satellite, and Time History of Events and Macroscale Interactions during Substorms spacecraft in the near-equatorial magnetosphere and from several arrays of ground-based search coil magnetometers worldwide, as well as localized ring current proton precipitation data from low-altitude Polar Operational Environmental Satellite spacecraft. Each of these data sets provides only limited spatial coverage, but their combination shows consistent occurrence patterns and reveals some events that would not be identified as significant using near-equatorial spacecraft alone. Relativistic and ultrarelativistic electron flux observations, phase space density data, and pitch angle distributions based on data from the Relativistic Electron-Proton Telescope and Magnetic Electron Ion Spectrometer instruments on the Van Allen Probes during these events show two cases during which EMIC waves are likely to have played an important role in causing major flux dropouts of ultrarelativistic electrons, particularly near L* ~4.0. In three other cases, identifiable smaller and more short-lived dropouts appeared, and in five other cases, these waves evidently had little or no effect. 

Many factors influence relativistic outer radiation belt electron fluxes, such as waves in the ultralow frequency (ULF) Pc5, very low frequency (VLF), and electromagnetic ion cyclotron (EMIC) frequency bands, seed electron flux, Dst disturbance levels, substorm occurrence, and solar wind inputs. In this work we compared relativistic electron flux poststorm versus prestorm using three methods of analysis: (1) multiple regression to predict flux values following storms, (2) multiple regression to predict the size and direction of the change in electron flux, and (3) multiple logistic regression to predict only the probability of the flux rising or falling. We determined which is the most predictive model and which factors are most influential. We found that a linear regression predicting the difference in prestorm and poststorm flux (Model 2) results in the highest validation correlations. The logistic regression used in Model 3 had slightly weaker predictive abilities than the other two models but had the most value in providing a prediction of the probability of the electron flux increasing after a storm. Of the variables used (ULF Pc5 and VLF, seed electrons, substorm activity, and EMIC waves), the most influential in the final model were ULF Pc5 waves and the seed electrons. IMF Bz, Dst, and solar wind number density, velocity, and pressure did not improve any of the models, and were deemed unnecessary for effective predictions.