2021
DOI: 10.5194/egusphere-egu21-10061
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Radiation belt electron acceleration during periods of low plasma density

Abstract: <p>Electrons in the Van Allen radiation belts can have energies in excess of 7 MeV. We present a unique way of analyzing phase space density data which demonstrates that local acceleration is capable of heating electrons up to 7 MeV. The Van Allen Probes mission not only provided unique measurements of ultra-relativistic radiation belt electrons, but also simultaneous observations of plasma waves that allowed for the routine inference of total plasma number density. Based on long-term observation… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
7
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
2
2

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(7 citation statements)
references
References 0 publications
0
7
0
Order By: Relevance
“…3. A low background plasma density that creates a preferential condition for the local diffusive acceleration of electrons from hundreds of keV to several MeV (Allison et al, 2021). shown with solid black lines to highlight periods of significant flux variations.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…3. A low background plasma density that creates a preferential condition for the local diffusive acceleration of electrons from hundreds of keV to several MeV (Allison et al, 2021). shown with solid black lines to highlight periods of significant flux variations.…”
Section: Resultsmentioning
confidence: 99%
“…3. A low background plasma density that creates a preferential condition for the local diffusive acceleration of electrons from hundreds of keV to several MeV (Allison et al, 2021). The source electron population exhibits an initial strong acceleration followed by a loss, and the seed electron population exhibits a strong acceleration followed by no/small flux variations.…”
Section: Methodsmentioning
confidence: 99%
“…Machine learning models also account intrinsically for multiple dependences (e.g., Chu et al, 2017a;Zhelavskaya et al, 2021), and are undoubtedly a promising approach to combine multiple satellite observations and produce the next-generation of global empirical plasma density models. A neural network-based density model has recently served to show that the plasma density has a controlling effect over acceleration of radiation belt electrons to ultra-relativistic energies (Allison et al, 2021). Contrary to empirical fits that do not allow trustable extrapolation, machine learning techniques, such as neural networks, are extremely promising in terms of predictive capability, which is a keystone for space weather codes.…”
Section: Discussionmentioning
confidence: 99%
“…A neural-network-based upper hybrid resonance (UHR) determination algorithm (NURD) was developed to automatically determine the electron density from plasma wave measurements using Van Allen Probes data (Zhelavskaya et al, 2016(Zhelavskaya et al, , 2018. NURD is applied to Van Allen Probes EMFISIS data in Allison et al (2021) to show that the plasma density has a controlling effect over acceleration of radiation belt electrons to ultra-relativistic energies. ML-based methods for automatically determining the UHR frequency have also been applied to the Arase satellite using convolutional neural network (Hasegawa et al, 2019;Matsuda et al, 2020) and the CLUSTER mission using several automated pipelines based on neural network methods (Gilet et al, 2021).…”
Section: Machine Learning Modelsmentioning
confidence: 99%
“…Likely both local acceleration and inward radial diffusion are contributing to the enhancements (e.g., Allison et al, 2019;Lejosne et al, 2022). Geoeffective sheaths are typically associated with strong substorm activity (e.g., Pulkkinen et al, 2007;Kalliokoski et al, 2020), which in turn excites chorus waves that can efficiently accelerate electrons to > 1 MeV energies (Miyoshi et al, 2013;Jaynes et al, 2015;Allison et al, 2021).…”
Section: Accepted Articlementioning
confidence: 99%