All-Sky Downwelling Longwave Radiation and Atmospheric-Column Water Vapour and Temperature over the Western Maritime Arctic
Bibliographic record
Abstract
Measurements of downwelling longwave radiation and atmospheric-column variables (precipitable water, mean vapour pressure, and mean temperature) derived from microwave radiometric profiles were collected over a composite year at various locations in the Beaufort Sea–Amundsen Gulf region of the Canadian Arctic. Cloud cover was specified by a temporal fractional cloud cover derived from ceilometer measurements. A logarithmic relationship was found between downwelling longwave radiation and atmospheric-column water vapour expressed as precipitable water or mean vapour pressure. This relationship explained about 84% of the variance with a standard error of around 9%. Downwelling longwave radiation was not as well correlated with mean atmospheric temperature. The parameterization of downwelling longwave radiation as a function of atmospheric-column variables, which can be analyzed more accurately than surface variables in data sparse regions, may contribute to improved climate modelling of the western maritime Arctic region. It was shown that both the annual cycle of monthly median precipitable water and water vapour intrusions influenced the magnitude of downwelling longwave radiation, and the impact was enhanced by cloud cover. RÉSUMÉ [Traduit par la rédaction] Des mesures du rayonnement descendant de grandes longueurs d'onde et des variables de colonne atmosphérique (eau précipitable, pression de vapeur moyenne et température moyenne) dérivées de profils radiométriques en hyperfréquences ont été recueillies au cours d'une année composite à différents sites dans la région de la mer de Beaufort et du golfe d'Amundsen dans l'Arctique canadien. La couverture nuageuse était spécifiée comme une fraction temporelle de couverture nuageuse dérivée de mesures faites par célomètre. Nous avons trouvé une relation logarithmique entre le rayonnement descendant de grandes longueurs d'onde et la vapeur d'eau dans la colonne atmosphérique exprimée sous forme d'eau précipitable ou de pression de vapeur moyenne. Cette relation explique environ 84% de la variance avec une erreur-type d'environ 9%. Le rayonnement descendant de grandes longueurs d'onde n’était pas aussi bien corrélé avec la température atmosphérique moyenne. La paramétrisation du rayonnement descendant de grandes longueurs d'onde en tant que fonction des variables de la colonne atmosphérique, qui peuvent s'analyser plus précisément que les variables de surface dans les régions où il y a peu de données, peut contribuer à améliorer la modélisation du climat de la région ouest de l'Arctique maritime. Il apparaît que tant le cycle annuel de la médiane mensuelle de l'eau précipitable que les intrusions de vapeur d'eau ont influencé l'intensité du rayonnement descendant de grandes longueurs d'onde et l'effet a été amplifié par la couverture nuageuse.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".