The Responses of High Latitude Clouds and High and Mid-Latitude Surface Pressures to the Solar Wind Sector Structure.
Bibliographic record
Abstract
The opacity of clouds at Alert, Canada have been shown by measurements of their infrared irradiances to change with the day-to-day solar wind input to the global atmospheric electric circuit, as well as to the inputs of global thunderstorms and magnetic storms. These cloud changes appear to be the cause of surface pressure changes in the Arctic and Antarctic that have long been observed to correlate with the solar wind sector structure. We analyze large data sets of cloud irradiances and surface pressures, and find differences in the responses to 2, 4, or more sectors per 27-day solar rotation. There are seasonal variations, with sign reversal in the summer, which we interpret as due to changing geometry of solar insolation input. The correlation coefficients that were shown to be statistically significant at near the 95% confidence level for all-year, all sector types show further increases for just winter months and for just 2-sector intervals. The phase relationship of the pressure responses compared to those of the cloud responses are consistent but not understood. There are also interannual variations, whose cause has yet to be determined. A parameterization of the potential distribution near the magnetic poles and out through the high latitude ionospheric region affected by solar wind inputs has been made, giving correlations of IR irradiance and pressure with these parameterizations stronger than with those for the IMF B alone. The effects analyzed are an indication of more extensive influences of global atmospheric electricity on cloud microphysics and cloud development.
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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".