Radiation Belt Relativistic Electron Loss Processes

1. Radiation Belt Relativistic Electron Loss Processes John Sample UC Berkeley-Space Sciences Lab Spring AGU 2006 With Thanks to Robyn Millan

2. The Static Radiation Belts • Even the quiet, ‘static’ radiation belts are constrained by losses. • Slot formation by Wave-Particle scattering of electrons into the atmosphere • outer boundary (inside the last closed field line) determined by: ~current sheet scattering ~magnetopause encounters

3. The Highly Variable Radiation Belts • Fluxes can change by orders of magnitude on short timescales, especially around magnetic storms • However, the wide variability in radiation belt response to storm conditions (or lack thereof) demonstrates a competition between acceleration and loss processes Reeves et al. ‘03

4. Tools of the Trade • The end of the field line • LEO satellites in high inclination orbits • Bremsstrahlung observing Balloons • Sounding Rockets • Mid field line • GEO Satellites • Other Equatorial Orbits • Generally looking at Changes in flux: convolves acceleration, loss, and adiabatic changes • Loss cone usually too narrow to resolve • Theory and Modeling • With good models of field and distributions we can connect disparate observations, follow evolution of PSD, and make predictions based on input conditions • still require validation and refinement Blake et al Onsager et al Days, Dec. 1999 Frequently, we need multi-point observations, and must rely on models to connect the dots

5. A Zoo of Loss Processes • At least three broad categories of flux decrease • pitch angle scattering-atmospheric precipitation • magnetopause encounters • adiabatic decreases • Classification Schemes • Local Time (e.g. Duskside dropouts, Dawnside microbursts) • Energy Dependence (keV microbursts vs. MeV microbursts) • Time profile (microbursts vs. bands, Duskside REP) • Storm-time Dependence (Main phase vs. Recovery • Even observation method (large historical record waiting to be mined) • Different Physics (e.g. Current sheet scattering vs. gyroresonance, when does QL theory break down) • Still to Determine the t, L,MLT, E, and activity dependent relative importance of each • Should be included in any comprehensive model • Losses can constrain acceleration rates required to give measured fluxes

6. (e.g. Dessler + Karplus ’61 McIlwain ‘66) The Adiabatic Response • Kim and Chan ‘97 looked at fully adiabatic response of equatorially mirroring electrons for Nov. 93 storm • changes must occur slower than the drift frequency • Ring current reduces B in inner magnetosphere • electrons move outward to conserve third adiabatic invariant • conservation of the first adiabatic inv. reduces perp. momentum Used symmetric and asymmetric field models Flux decrease occurs because of energy dependence and spatial gradient Found that some real loss was required, suggested magnetopause encounters

7. Precipitation into the atmosphere • Equatorial pitch angles smaller than αL will encounter the atmosphere before mirroring • Wave Particle Interactions • Gyroresonance requires w-k||v|| = ±nW/g • Chorus (~100Hz- few kHz) • EMIC (~Hz, below H+,He+,O+) • Hiss (~100Hz- few kHz) • Current sheet scattering • when electron gyro-radius is comparable to radius of curvature of the field line. • should be most important near midnight • should also affect protons • Bounce Loss Cone vs. Drift Loss Cone Size of Loss cone is a function of longitude Equatorial pitch angles smaller than this will strike the atmosphere Degrees East after Selesnick 03

8. Available Waves • Large number of wave modes available for gyroresonance • Hiss vs. Chorus separation occasionally ambiguous • Waves have local time, activity dependence • many times we do not have wave measurements at the same time as particles Meredith et al. ‘04 Summers et al. ‘98

9. Plasmaspheric Hiss Hiss magnetic field amplitude: (Meredith et al., 2004) Electron minimum resonant energy ~1 MeV only inside L~3

10. Microburst Precipitation X-ray Microbursts Anderson and Milton, 1964 • Early balloon observations of ~100 keV microbursts attributed to scattering by VLF whistler-mode waves (Parks, 1978, Rosenberg et al., 1990) Sampex • Relativistic electron microbursts: first reported by Imhof ‘92, studied extensively with SAMPEX, large geometric factor HILT which measures >1MeV electrons allows for time resolution up to 20ms. ~100s (Lorentzen et al., 2001)

11. Microburst precipitation Occur between L=4-6 0200-1000 MLT Outside plasmapause MLT / L Distribution Microbursts (Courtesy T. P. O’Brien) Whistler Chorus • Also occurs on dayside • Outside plasmapause Meredith et al. ‘02

12. MeV microbursts and Whistler Chorus • local time circumstantial evidence led Lorentzen ’01 to look for conjunction of POLAR (Wave data) with SAMPEX observations of MeV microbursts. • no 1-1 correspondence was found, but Chorus risers having duration similar to single microbursts were seen at similar times,L-Shells, MLT • Demonstrated that resonance with MeV electrons would have to occur off equatorially or at a higher harmonic

13. Distribution of EMIC waves • Peak near dusk meridian ~colocated with bulge in plasmasphere (from Meredith et al., 2003) (from Erlandson and Ukhorskiy, 2001)

14. EMIC Resonance Condition Meredith et al. 03 • In order for EMIC waves to be resonant with electrons, the electrons must overtake the wave at high doppler shift • this enforces a minimum v|| minimum Eres • small pitch angles will resonate at a smaller total E • Resonance condition depends strongly on wave velocity • Dispersion relation requires high density or low magnetic field to resonate with ~1-2MeV electrons • will also resonate with ~few keV protons Imhof et al ’86 found ~30% of pre-midnight selective high energy events studied using S81 and other satellites were related to or embedded in regions of proton precipitation

15. Combination of waves can be important • Albert 2003 showed lifetimes with hiss alone ~7x longer than with hiss and EMIC • EMIC still needs high ratio of fpe to fce in order to resonate with ~MeV electrons L=4, 100pT Hiss, 1pT EMIC (weighted by drift time in relevant region)

16. Energy Selective Precipitation on the Dusk Side • We do see strong scattering losses on the duskside • Thorne and Andreoli ‘80 • 3 events in 14 months of s3-3 data (1% of all precipitation events observed) • Imhof ’86 • 41 events using S-(72,78,81)-1 data. Some very intense. • Filtered on narrow L structures • e-foldings >500keV • Concluded such events were rare, but poor MLT coverage may have missed peak. • Foat ’96, Millan ’02 • Observed Bremsstrahlung X-ray bursts from similarly high energy electron precipitation on the dusk side.

17. Energy Selective Precipitation on the Dusk Side NOON • We do see strong scattering losses on the duskside • Thorne and Andreoli ‘80 • 3 events in 14 months of s3-3 data (1% of all precipitation events observed) • Imhof ’86 • 41 events using S-(72,78,81)-1 data. Some very intense. • Filtered on narrow L-structures • e-foldings >500keV • Concluded such events were rare, but poor MLT coverage may have missed peak. • Foat ’96, Millan ’02 • Observed Bremsstrahlung X-ray bursts from similarly high energy electron precipitation on the dusk side. MIDNIGHT

18. Loss out the Magnetopause • Adiabatic drift outward • When Dst drops, particles move outward to conserve their 3rd invariant • Magnetopause compression • Sharp increases in solar wind dynamic pressure • Li et al ‘97 used to explain losses into L=4.6 during November ‘93 storm • Usually thought to be most important at higher L but… • Outward radial diffusion towards a time dependent boundary has recently been found to be capable of rapidly propagating flux drops from MP encounters inward • In some cases magnetopause losses should be recognizable in proton fluxes at similar energies • Very difficult to measure directly

19. >2MeV flux dropouts • Sudden drops in high energy flux at GEO identified by Onsager et al. ’02 • Events begin with tailward stretching of nightside magnetopause, an asymmetric process that can occur before Dst drops • Fluxes aren’t equilibrated in local time within one electron drift.

20. Looking for a mechanism • Green et al. ’04 Identified 52 similar events, performed a superposed epoch analysis using GEO,HEO,LEO data • events first observed at dusk, similar LT progression as in Onsager • converting to PSD eliminates adiabatic effects • accounts for local time progression of events • however fluxes remain low well after field returns to normal so real loss occurred • Magnetopause encounters? • losses went in to L ~4, • no similar dropout in proton flux • Precipitation?

21. Looking for a mechanism • Green et al. ’04 Identified 52 similar events, performed a superposed epoch analysis using GEO,HEO,LEO data • Adiabatic? No • Magnetopause encounter? Unlikely • Precipitation? • Do see an increase of Bounce Loss around time of event onset, however data coverage is sparse • Millan et al. ’06 • One of the events identified by Green et al. study occurred during the MAXIS balloon campaign of January 2000. • MAXIS observed an extended, intense X-ray burst with sufficient precipitation to account for the flux drop at GEO

22. Quantification of Loss Rates • Lorentzen ’01 Demonstrated that microburst loss from a single storm could flush the radiation belts of MeV electrons • O’Brien ’04 Principal losses occur during main phase, losses continue through recovery, but with less cumulative effect. • Millan ’02 Losses from Duskside REP discussed earlier were shown to be capable of emptying outer belt in a few days • Current work by Shprits et al. has shown outward radial diffusion and MP encounters capable of similar high loss rates • Ukorhisky et al. used test particles in TS05 to show strong MP losses during Sep. 7, ’02 storm • Selesnick ’06 By using a model to compare drift loss to trapped population using SAMPEX able to calculate daily energy dependent atmospheric loss rates.

23. Summary • Wide variety of loss processes act on relativistic electrons in the radiation belts • Each process (subprocess!) has been shown to be dominant in some cases • To actually specifically identify any given event with a particular process usually requires joining multiple satellite data sets with appropriately fit models • It is possible to quantify a loss rate without understanding the details of the loss process • Much work to be done