Rapid Outer Radiation Belt Flux Dropouts and Fast Acceleration during the March 2015 and 2013 Storms: The Role of ULF Wave Ttansport From a Dynamic Outer Boundary
Bibliographic record
Abstract
Duplicate copy of the electron phase space density provided for the Geospace Environment Modeling (GEM) challenge event in March 2013 selected by the Quantitative Assessment of Radiation Belt Modeling focus group. The original copy of the data is available from https://drive.google.com/drive/u/0/folders/0ByNhSbWkAgdfaGt6TnJMcElhUTg Data Providers: Michael G. Henderson (LANL; mghenderson@lanl.gov) Steven K. Morley (LANL; smorley@lanl.gov) This data product provides electron phase space density from the Van Allen Probes ECT suite of instruments. The data are calculated similarly to the method described in Morley et al. (2013), with some differences that are noted below. The files are provided in HDF5 format, so the files are self-describing and contain ISTP-style metadata. The files should be directly readable with: - SpacePy (http://sourceforge.net/p/spacepy) - import the spacepy.datamodel module, use the function fromHDF5 to read the data - Autoplot (http://autoplot.org) - MatLab and IDL provide convience routines for reading HDF5 Method ------ Starting with directional differential flux data from HOPE, MagEIS and REPT, we calculate the PSD as a function of energy, pitch angle, position and time. Following the same basic method given by Morley et al., we transform this to phase space density as a function of the three adiabatic invariants (M, K, L*); note that where Morley et al. used a relativistic Maxwellian fit to the flux spectrum, these data use a smoothing spline fit so that more complex spectral shapes can be represented. Note also that Morley et al. only used REPT, where these files represent the energy ranges of MagEIS and REPT, but also use HOPE to constrain the fit at low energies. While the pitch angles are determined using the EMFISIS data, all three adiabatic invariants are derived from a magnetic field model. These PSD data files use the Tsyganenko and Sitnov (2005) model (aka TS04, T05 or TS05). The models were run using the "definitive" Qin-Denton data files provided by the RBSP ECT-SOC. These files should be made available through the QARBM google drive. Caveats ------- These data should be considered preliminary. They have undergone a limited amount of verification and prior to publication the data providers should be contacted. New versions of these data may be generated at some point - we do not expect noticeable changes to the data present. Some gaps may be present in the files that are due to calculation of the adiabatic invariants failing. The issues causing these gaps have been resolved in the underlying software, but the data have not yet been regenerated. References ---------- Morley, S. K., M. G. Henderson, G. D. Reeves, R. H. W. Friedel, and D. N. Baker (2013), Phase Space Density matching of relativistic electrons using the Van Allen Probes: REPT results, Geophys. Res. Lett., 40, 4798-4802, doi:10.1002/grl.50909. Tsyganenko, N. A., and M. I. Sitnov (2005), Modeling the dynamics of the inner magnetosphere during strong geomagnetic storms, J. Geophys. Res., 110, A03208, doi:10.1029/2004JA010798.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".