Rapid Frequency Variations Within Intense Chorus Wave Packets

Abstract

Whistler mode chorus waves are responsible for electron acceleration in Earth's radiation belts. It is unclear, however, whether the observed acceleration is still well described by quasi‐linear theory, or if this acceleration is due to intense waves that require nonlinear treatment. Here, we perform a comprehensive statistical analysis of intense lower‐band chorus wave packets to investigate the relationships between wave frequency variations, packet length, and wave amplitude, and their temporal variability. We find that 15% of the wave power is carried by long packets, with low frequency sweep rates (linear trend in time) that agree with the nonlinear theory of chorus wave growth. Eighty‐five percent of the wave power, however, comes from short packets with large frequency variations around the linear trend. The kappa‐like probability distribution of these variations is consistent with random superposition of different waves that could result in a destruction of nonlinear resonant interaction.

Phase Decoherence Within Intense Chorus Wave Packets Constrains the Efficiency of Nonlinear Resonant Electron Acceleration

“…In Figures 4a-4d (blue and red curves for constant and smoothly increasing frequency, respectively), we next investigate the effects of the more realistic frequency difference Δ / ∼ 1/5 consistent with statistical observations, corresponding to wave amplitude modulations (subpackets) of typical length (∼5 wave periods), which are accompanied by random frequency jumps Δ / ∼ 0.1-0.5 at the edges of subpackets (Zhang et al, 2020). These realistic frequency jumps are equivalent to wave phase jumps of similar magnitude as observed phase jumps in Figure 2.…”

“…We use a comprehensive statistical data set of intense whistler mode chorus waves observed by the Van Allen Probes (Mauk et al, 2013) (and assembled previously by Zhang et al, 2019Zhang et al, , 2020. We analyze waveform data measured by the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) Waves instrument (Kletzing et al, 2013) during the continuous burst mode (tens to hundreds of bursts per day), which lasts 6 s during each capture (at a cadence of 35,000 samples per second).…”

“…Chorus wave frequency variations inside wave packets usually include a superposition of an average frequency sweep rate (t) calculated over packet duration (with / t > 0 for rising tones, / t < 0 for falling tones, or / t ≈ 0 for constant frequency waves) and additional frequency fluctuations (Zhang et al, 2020). These fast frequency fluctuations, Δ , are randomly distributed around (t), and their magnitude is comparable to the total frequency variation ( final − initial ) over packet duration (Zhang et al, 2020).…”

“…But the much stronger, abrupt Δ ω variations observed near the edges of subpackets in Figures 1a and 1b (see also Santolík et al, 2014; Zhang et al, 2020) have yet to be incorporated in test particle codes. Models of whistler mode wave generation predict frequency ω ( t ) changes over timescales of trapped electron quasiperiodic dynamics (Demekhov, 2011; Katoh & Omura, 2011, 2016; Nunn et al, 2009; Tao et al, 2017, 2020), leading to the formation of wave subpackets.…”

“…This phase decoherence allows for the assumption of independent shortwave packets, where continuous trapping by successive packets/subpackets would be impossible (i.e., the situation investigated by Mourenas et al, 2018). Such phase decoherence may be provided by wave frequency and wave phase variations, which are often observed within or in‐between chorus wave packets (Santolík et al, 2014; Zhang et al, 2020). These fast variations have not been included into wave‐particle interaction models, which only include smooth wave frequency growth/decrease in rising/falling tone chorus waves (Demekhov et al, 2006; Gan et al, 2020; Hsieh & Omura, 2017).…”