Winter Air Temperature Change over the Terrestrial Arctic, 1961–1990
Bibliographic record
Abstract
We evaluate two approaches to spatially interpolating winter surface air-temperature fields over the terrestrial Arctic from available weather-station records. We then examine 30 yr (1961–1990) of winter air-temperature change over the terrestrial Arctic through a time-trend analysis of interpolated winter air-temperature fields. We used monthly average air temperatures from 4984 Arctic station records that were available for the period 1961–1990. The two spatial interpolation procedures employed were “traditional” interpolation and a method that makes use of spatially high-resolution digital-elevation information, called “DEM-assisted” (DAI). The Arctic average winter air temperature obtained from the traditionally interpolated 1961–1990 climatology is over 9°C colder than the mean winter station temperature, illustrating the considerable warm bias in Arctic weather station locations. The DAI-based average is 1°C colder, further emphasizing the importance of spatial interpolation prior to spatial averaging.Over the 30 yr, increases in winter air temperature appear across western Canada and in parts of central Asia, with decreasing trends apparent over eastern Canada. Much of the Arctic exhibits no clear trend, with low explained variances. In western Canada, however, warming trends are on the order of 0.1 to 0.4°C yr−1 when the fields analyzed were traditionally interpolated or interpolated using DAI. Explained variances (r 2s) are higher where trends are largest: approximately 0.2 to 0.4 in western Canada and slightly higher (albeit spuriously) in an isolated area of central Asia. Over the entire terrestrial Arctic, mean winter air temperature has increased at a rate of about 0.05°C yr−1 based on traditional interpolation and DAI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".