Phase Space Density matching of relativistic electrons using the Van Allen Probes: REPT results

Morley, S.; Henderson, M. G.; Reeves, G. D.; Friedel, R. H. W.; Baker, D. N.

doi:10.1002/grl.50909

Cited by 30 publications

(48 citation statements)

References 35 publications

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“…It is worth noting that both of these studies were limited to geosynchronous orbit, and so we might not expect the results to be generally applicable. Indeed, Morley et al () found that T96 better reproduced the magnetic field magnitude during the storm recovery phase that they studied, even though TS04 gave better results for phase space density matching.…”

Section: Discussionmentioning

confidence: 99%

“…The configuration and strength of the geomagnetic field is a major controlling factor for energetic charged particle dynamics in the magnetosphere, including the dynamics of radiation belt electrons (e.g., Roederer & Zhang, ), ring current ions (e.g., Zaharia et al, ), cosmic rays, and solar energetic particle events (e.g., Desorgher et al, , Kress et al, ). For studies requiring magnetic conjugacy between satellites (e.g., Friedel et al, ; Morley et al, ) or between satellites and ground‐based instrumentation (e.g., Hones et al, ; Ge et al, ), the global morphology and mapping of magnetic field lines is crucial (e.g., Pulkkinen & Tsyganenko, ). Data‐based modeling of the external geomagnetic field has a long history of development in space physics (see Tsyganenko, , and references therein).…”

Section: Introductionmentioning

confidence: 99%

“…The contributions of each component current system are parametrized by upstream solar wind measurements and geomagnetic indices (Tsyganenko, , ). These models have been demonstrated to specify the global structure of the inner magnetosphere well on a statistical basis (McCollough et al, ; Woodfield et al, ; Zhang et al, ), with the later models generally performing better, although their performance varies through individual events (Huang et al, ; Morley et al, ).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

Brito

Morley

2017

Space Weather

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A method for comparing and optimizing the accuracy of empirical magnetic field models using in situ magnetic field measurements is presented. The optimization method minimizes a cost function—τ—that explicitly includes both a magnitude and an angular term. A time span of 21 days, including periods of mild and intense geomagnetic activity, was used for this analysis. A comparison between five magnetic field models (T96, T01S, T02, TS04, and TS07) widely used by the community demonstrated that the T02 model was, on average, the most accurate when driven by the standard model input parameters. The optimization procedure, performed in all models except TS07, generally improved the results when compared to unoptimized versions of the models. Additionally, using more satellites in the optimization procedure produces more accurate results. This procedure reduces the number of large errors in the model, that is, it reduces the number of outliers in the error distribution. The TS04 model shows the most accurate results after the optimization in terms of both the magnitude and direction, when using at least six satellites in the fitting. It gave a smaller error than its unoptimized counterpart 57.3% of the time and outperformed the best unoptimized model (T02) 56.2% of the time. Its median percentage error in |B| was reduced from 4.54% to 3.84%. The difference among the models analyzed, when compared in terms of the median of the error distributions, is not very large. However, the unoptimized models can have very large errors, which are much reduced after the optimization.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

Brito

Morley

2017

Space Weather

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“…These changes in the solar wind and geomagnetic parameters produce a sudden drop in the magnetopause position and the location of the last closed drift shell (LCDS) on 17 March, see Figures i and j. Note the LCDS is determined for 90° equatorial pitch angle electrons in the Tsyganenko and Sitnov () magnetic field model using the LANLmax and LANLstar algorithms (Yu et al, ) from the LANL* neural network (Morley et al, ). However, during the storm time interval on 17 and 18 March, the LCDS is obtained from the full calculation at a second adiabatic invariant of K = 0.05 G 1/2 Re using the LANLGeoMag software library (Henderson et al, ).…”

Section: The March 2013 and 2015 Geomagnetic Stormsmentioning

confidence: 99%

Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration During the March 2015 and 2013 Storms: The Role of Ultra‐Low Frequency Wave Transport From a Dynamic Outer Boundary

et al. 2020

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We present simulations of the outer radiation belt electron flux during the March 2015 and 2013 storms using a radial diffusion model. Despite differences in disturbance short‐time intensity between the two storms, the response of the ultra‐relativistic electrons in the outer radiation belt was remarkably similar, both showing a sudden drop in the electron flux followed by a rapid enhancement in the outer belt flux to levels over an order of magnitude higher than those observed during the pre‐storm interval. Simulations of the ultra‐relativistic electron flux during the March 2015 storm show that outward radial diffusion can explain the flux dropout down to L*~4. However, in order to reproduce, the observed flux dropout at L* < 4 requires the addition of a loss process characterized by an electron lifetime of around 1 hr operating below L*~3.5 during the flux dropout interval. Nonetheless, during the pre‐storm and recovery phase of both storms, the radial diffusion simulation reproduces the observed flux dynamics. For the March 2013 storm, the flux dropout across all L‐shells is reproduced by outward radial diffusion activity alone. However, during the flux enhancement interval at relativistic energies, there is evidence of a growing local peak in the electron phase space density at L*~3.8, consistent with local acceleration such as by very low frequency chorus waves. Overall, the simulation results for both storms can accurately reproduce the observed electron flux only when event specific radial diffusion coefficients are used, instead of the empirical diffusion coefficients derived from ultra‐low frequency wave statistics.

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“…μ , K, and L * are the first, second, and third adiabatic invariants, respectively. For the relativistic electrons of a specified energy ( E ), their three adiabatic invariants and phase space density (f) are expressed as [ Kim and Chan , ; Chen et al , ; Morley et al , ; Reeves et al , ] follows:

μ = \frac{E ((), E + 2 E_{0})}{2 B E_{0}} \sin^{2} α

K = true {true\int}_{s_{s}}^{s_{n}} \sqrt{B_{m} - B ((), s)} normald s

L^{*} = \frac{2 π M}{Φ R_{E}}

f ((),,, μ, K, L^{*}) = 3.325 \times 10^{prefix- 11} \frac{j ((),,, E, α, r)}{E ((), E + 2 E_{0})}

…”

Section: Relativistic Electron Loss During a Sscmentioning

confidence: 99%

Multiple loss processes of relativistic electrons outside the heart of outer radiation belt during a storm sudden commencement

Cao

et al. 2015

JGR Space Physics

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By examining the compression‐induced changes in the electron phase space density and pitch angle distribution observed by two satellites of Van Allen Probes (RBSP‐A/B), we find that the relativistic electrons (>2 MeV) outside the heart of outer radiation belt (L* ≥ 5) undergo multiple losses during a storm sudden commencement. The relativistic electron loss mainly occurs in the field‐aligned direction (pitch angle α < 30° or >150°), and the flux decay of the field‐aligned electrons is independent of the spatial location variations of the two satellites. However, the relativistic electrons in the pitch angle range of 30°–150° increase (decrease) with the decreasing (increasing) geocentric distance (|ΔL| < 0.25) of the RBSP‐B (RBSP‐A) location, and the electron fluxes in the quasi‐perpendicular direction display energy‐dispersive oscillations in the Pc5 period range (2–10 min). The relativistic electron loss is confirmed by the decrease of electron phase space density at high‐L shell after the magnetospheric compressions, and their loss is associated with the intense plasmaspheric hiss, electromagnetic ion cyclotron (EMIC) waves, relativistic electron precipitation (observed by POES/NOAA satellites at 850 km), and magnetic field fluctuations in the Pc5 band. The intense EMIC waves and whistler mode hiss jointly cause the rapidly pitch angle scattering loss of the relativistic electrons within 10 h. Moreover, the Pc5 ULF waves also lead to the slowly outward radial diffusion of the relativistic electrons in the high‐L region with a negative electron phase space density gradient.

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Phase Space Density matching of relativistic electrons using the Van Allen Probes: REPT results

Cited by 30 publications

References 35 publications

Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

Improving Empirical Magnetic Field Models by Fitting to In Situ Data Using an Optimized Parameter Approach

Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration During the March 2015 and 2013 Storms: The Role of Ultra‐Low Frequency Wave Transport From a Dynamic Outer Boundary

Multiple loss processes of relativistic electrons outside the heart of outer radiation belt during a storm sudden commencement

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