On the Interplay Between Solar Wind Parameters and ULF Wave Power as a Function of Geomagnetic Activity at High‐ and Mid‐latitudes
Bibliographic record
Abstract
Abstract Using ground magnetometer measurements from the IMAGE array over the timespan of one solar cycle, we apply wavelets to statistically assess the power of ultra‐low frequency (ULF) waves from L = 3.34 to L = 13.6 as a function of Kp, solar wind speed (), solar wind dynamic pressure (), Dst, and . We find that although geomagnetic storms account for the overwhelming majority of ULF wave power at mid latitudes, this effect decreases for higher L‐shells. We present analysis of the effect of interplanetary magnetic field (IMF) on ULF wave power for different values of Kp and , revealing a strong inter‐dependency especially in relation to . A parameterization additionally incorporating appears to be more important at large‐L. Further, analysis for positive reveals a perhaps unexpected additional dependence on which points to effects of the interplanetary magnetic field cone angle and Kelvin‐Helmholtz instabilities. Finally, we derive ULF wave radial diffusion coefficients from the measured ULF wave power spectral densities and briefly discuss their importance for radiation belt dynamics. Interestingly, in part because of the correlation between Dst‐defined storm times and high Kp, we find that the low‐Kp radial diffusion coefficients during storms are higher than previously assumed almost certainly because of the dominance of nonstorm epochs in the statistics of median ULF wave power under conditions of low Kp. These inter‐dependencies should be taken into account in future specification models for ULF wave radial diffusion coefficients when applied in storm time simulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".