Coupling From the Middle Atmosphere to the Exobase: Dynamical Disturbance Effects on Light Chemical Species
Bibliographic record
Abstract
Abstract This paper characterizes the impacts of sudden stratospheric warmings (SSWs) and mesospheric coolings (MCs) on the light species distribution (i.e., helium [He], and atomic hydrogen [H]) of the thermosphere using a combined data‐modeling approach. Performing a set of numerical experiments with a general circulation model whose middle atmospheric dynamical and thermodynamical fields were constrained using a numerical weather prediction system, we simulate the effects of SSWs and MCs on light chemical species, and via comparisons with two data sets taken from the mesosphere and thermosphere, we quantify the associated variability in light species abundances and mass density. Large depletions in the observed and modeled polar H abundance in the mesosphere and lower thermosphere (MLT) occur with MC onset, as opposed to SSW onset. Depletions in all light thermospheric species at high northern latitudes extend up to the exobase in our model simulations during the January 2013 SSW/MC period, with the largest depletions simulated for the lightest species. Further, our modeling work substantiates the paradigm of increased mixing in the MLT driven by a meridional residual circulation during SSWs resulting from enhanced small‐scale gravity wave and migrating semidiurnal tidal forcing; the former being the primary driver and the latter of secondary but notable importance in our model simulations. SSW/MC induced light species variability then gets projected upward into the thermosphere through molecular diffusion. Modeled light species variability during the January 2013 SSW/MC event suggests SSW/MC signatures could be present in the topside ionosphere and plasmasphere.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".