A comparison of the atmospheric conditions at Eureka, Canada, and Barrow, Alaska (2006–2008)
Bibliographic record
Abstract
It is now well understood that the Arctic is particularly sensitive to climate change. Arctic sea ice is already undergoing significant changes. Some of the recent decrease in sea ice extent is due to changes in the surface energy budget, including the effect of clouds. Accurate ground‐based measurements of atmospheric and cloud properties are valuable for estimating components of the surface energy budget. In this paper, measurements made between 2006 and 2008 at the Canadian Network for the Detection of Arctic Change (CANDAC) site at Eureka, Nunavut, Canada (80°N, 86°W) and the Atmospheric Radiation Measurement (ARM) program site at Barrow, Alaska (71°N, 156°W) are used to examine differences in the atmospheres over the two sites, including the temperature, humidity, winds, and the downwelling longwave radiation flux. A method is developed to convert infrared radiances to downwelling longwave fluxes since broadband measurements of flux were not available at Eureka during the study period; the method is validated by comparing the fluxes at Barrow to independent measurements made by a pyrgeometer. Comparisons of the derived fluxes show significant differences between the two sites. Eureka is consistently colder and drier than Barrow, and the infrared effect of clouds on the surface energy budget is less. To examine the meteorological conditions that cause such differences, the ERA‐Interim reanalysis model is used; it is chosen over other models because it provides the best reproduction of longwave radiation at the surface. We find that the location of Eureka predisposes it to cold and dry air masses from the central Arctic Ocean and the Greenland Ice Sheet. In contrast, the air masses at Barrow come from a variety of directions, some of which are relatively warm and moist.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".