Midlatitude Moisture Contribution to Recent Arctic Tropospheric Summertime Variability*
Bibliographic record
Abstract
Abstract The dynamics of late summer Arctic tropospheric heat content variability is studied using reanalyses. In both trends and interannual variability, much of the August heat content variability in the Arctic midtroposphere can be explained by the total—sensible plus latent—heat content variability at the midlatitude near surface in July. Climate models suggest that this connection is part of the global warming signal in September–November, but in reanalyses the connection is most strongly present in July–August variability and trends. It is argued that heat content signals are propagated from the midlatitude near surface to the Arctic midtroposphere approximately along climatological moist isentropes. High-frequency data reveal that the propagating signal is primarily driven by a few strong meridional heat flux events each summer season. Composite analysis on these events shows that August meridional heat fluxes into the Arctic midtroposphere are succeeded by positive heat content anomalies in the lower troposphere a few days later. This second connection between the Arctic midtroposphere and the Arctic lower troposphere could be sufficient to explain some of the recent Arctic 850-hPa temperature variability north of 75°N.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".