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Resonant interactions with whistler‐mode waves are one of the most important drivers for rapid energetic electron precipitation. In this letter, we study a conjunction event, where bursts of energetic electron precipitation (50–800 keV) with timescales of several seconds are observed by the twin ELFIN Cubesats at low Earth orbit, while very‐oblique intense whistler‐mode waves are observed by the Time History of Events and Macroscale Interactions during Substorms E satellite at the conjugate magnetic equator. Our observation‐constrained test‐particle simulations reveal that the electron precipitation, particularly above 100 keV, results from high‐order resonant scattering by the very‐oblique whistler‐mode waves. Our study provides the first direct evidence for high‐order resonance driven precipitation, explaining a bursty precipitation event. The results demonstrate that high‐order resonant scattering could be important, not only in long‐term diffusion models, but also in models of short timescale events.

 

We analyze the drivers, distribution, and properties of the relativistic electron precipitation (REP) detected near midnight by the Polar Orbiting Environmental Satellites (POES) and Meteorological Operational (MetOp) satellites, critical for understanding radiation belt losses and nightside atmospheric energy input. REP is either driven by wave‐particle interactions (isolated precipitation within the outer radiation belt), or current sheet scattering (CSS; precipitation with energy dispersion), or a combination of the two. We evaluate the L‐MLT distribution for the identified REP events in which only one process evidently drove the precipitation (∼10% of the REP near midnight). We show that the two mechanisms coexist and drive precipitation in a broadL‐shell range (4–7). However, wave‐driven REP was also observed atL < 4, whereas CSS‐driven REP was also detected atL > 7. Moreover, we estimate the magnetotail stretching during each REP event using the magnetic field observations from the Geostationary Operational Environmental Satellite (GOES). Both wave‐particle interactions and CSS drive REP in association with a stretched magnetotail, although CSS‐driven REP potentially shows more pronounced stretching. Wave‐driven REP events are localized inLshell and often occur on spatial scales of <0.3 L. Using either proton precipitation (observed by POES/MetOp during wave‐driven REP) as a proxy for electromagnetic ion cyclotron (EMIC) wave activity or wave observations (from GOES and the Van Allen Probes) at the conjugate event location, we find that ∼73% wave‐driven REP events are associated with EMIC waves.

 

We evaluate the location, extent, and energy range of electron precipitation driven by ElectroMagnetic Ion Cyclotron (EMIC) waves using coordinated multisatellite observations from near‐equatorial and Low‐Earth‐Orbit (LEO) missions. Electron precipitation was analyzed using the Focused Investigations of Relativistic Electron Burst Intensity, Range and Dynamics (FIREBIRD‐II) CubeSats, in conjunction either with typical EMIC‐driven precipitation signatures observed by Polar Orbiting Environmental Satellites (POES) or with in situ EMIC wave observations from Van Allen Probes. The multievent analysis shows that electron precipitation occurred in a broad region near dusk (16–23 MLT), mostly confined to 3.5–7.5 L‐shells. Each precipitation event occurred on localized radial scales, on average ∼0.3 L. Most importantly, FIREBIRD‐II recorded electron precipitation from ∼200 to 300 keV to the expected ∼MeV energies for most cases, suggesting that EMIC waves can efficiently scatter a wide energy range of electrons.

 

We investigate relativistic electron precipitation events detected by Polar Environmental Satellites (POES) in low‐Earth orbit in close conjunction with Van Allen Probe A observations of electromagnetic ion cyclotron (EMIC) waves near the geomagnetic equator. We show that the occurrence rate of >0.7 MeV electron precipitation recorded by POES during those times strongly increases, reaching statistically significant levels when the minimum electron energy for cyclotron resonance with hydrogen or helium band EMIC waves at the equator decreases below ≃1.0–2.5 MeV, as expected from the quasi‐linear theory. Both hydrogen and helium band EMIC waves can be effective in precipitating MeV electrons. However, >0.7 MeV electron precipitation is more often observed (at statistically significant levels) when the minimum electron energy for cyclotron resonance with hydrogen band waves is low (E_min = 0.6–1.0 MeV), whereas it is more often observed when the minimum electron energy for cyclotron resonance with helium band waves is slightly larger (E_min = 1.0–2.5 MeV). This is indicative of the warm plasma effects for waves approaching the He⁺gyrofrequency. We further show that most precipitation events had energies > 0.7–1.0 MeV, consistent with the estimated minimum energy (E_min ∼ 0.6 − 2.5 MeV) of cyclotron resonance with the observed EMIC waves during the majority of these events. However, 4 out of the 12 detected precipitation events cannot be explained by electron quasi‐linear scattering by the observed EMIC waves, and 12 out of 20 theoretically expected precipitation events were not detected by POES, suggesting the possibility of nonlinear effects likely present near the magnetic equator, or warm plasma effects, and/or narrowly localized bursts of EMIC waves.

 

This study analyzes the effects of electromagnetic ion cyclotron (EMIC) waves on relativistic electron scattering and losses in the Earth’s outer radiation belt. EMIC emissions are commonly observed in the inner magnetosphere and are known to reach high amplitudes, causing significant pitch angle changes in primarily > 1 MeV electrons via cyclotron resonance interactions. We run test-particle simulations of electrons streaming through helium band waves with different amplitudes and wave normal angles and assess the sensitivity of advective and diffusive scattering behaviors to these two parameters, including the possibility of very oblique propagation. The numerical analysis confirms the importance of harmonic resonances for oblique waves, and the very oblique waves are observed to efficiently scatter both co-streaming and counter-streaming electrons. However, strong finite Larmor radius effects limit the scattering efficiency at high pitch angles. Recently discussed force-bunching effects and associated strong positive advection at low pitch angles are, surprisingly, shown to cause no decrease in the phase space density of precipitating electrons, and it is demonstrated that the transport of electrons into the loss cone balances out the scattering out of the loss cone. In the case of high-amplitude obliquely propagating waves, weak but non-negligible losses are detected well below the minimum resonance energy, and we identify them as the result of non-linear fractional resonances. Simulations and theoretical analysis suggest that these resonances might contribute to subrelativistic electron precipitation but are likely to be overshadowed by non-resonant effects. 

We show an application of supervised deep learning in space sciences. We focus on the relativistic electron precipitation into Earth’s atmosphere that occurs when magnetospheric processes (wave-particle interactions or current sheet scattering, CSS) violate the first adiabatic invariant of trapped radiation belt electrons leading to electron loss. Electron precipitation is a key mechanism of radiation belt loss and can lead to several space weather effects due to its interaction with the Earth’s atmosphere. However, the detailed properties and drivers of electron precipitation are currently not fully understood yet. Here, we aim to build a deep learning model that identifies relativistic precipitation events and their associated driver (waves or CSS). We use a list of precipitation events visually categorized into wave-driven events (REPs, showing spatially isolated precipitation) and CSS-driven events (CSSs, showing an energy-dependent precipitation pattern). We elaborate the ensemble of events to obtain a dataset of randomly stacked events made of a fixed window of data points that includes the precipitation interval. We assign a label to each data point: 0 is for no-events, 1 is for REPs and 2 is for CSSs. Only the data points during the precipitation are labeled as 1 or 2. By adopting a long short-term memory (LSTM) deep learning architecture, we developed a model that acceptably identifies the events and appropriately categorizes them into REPs or CSSs. The advantage of using deep learning for this task is meaningful given that classifying precipitation events by its drivers is rather time-expensive and typically must involve a human. After post-processing, this model is helpful to obtain statistically large datasets of REP and CSS events that will reveal the location and properties of the precipitation driven by these two processes at all L shells and MLT sectors as well as their relative role, thus is useful to improve radiation belt models. Additionally, the datasets of REPs and CSSs can provide a quantification of the energy input into the atmosphere due to relativistic electron precipitation, thus offering valuable information to space weather and atmospheric communities.