Climate Change Associated with Global Teleconnections, Volcanic Eruptions, and the Arctic’s Snow-Ice Albedo in Godthab, Greenland
Bibliographic record
Abstract
To study the impact of climate change on Godthab(Greenland), temperature and precipitation gathered from the Global Historical Climatology Network (GHCN) were analyzed for patterns within 1866-2011. Both temperature and precipitation have experienced an overall increase throughout the past 146 years. Precipitation, however, has experienced a declining trend since 1985. North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) indices showed strong correlations with average annual temperature (R = ?0.6) and smaller correlations with annual total precipitation (R = ?0.2). There are moderate correlations between temperature, precipitation, and Southern-Oscillation Index (SOI). The positive phases of Pacific-North American (PNA) led to increased winter and spring precipitation. The climate mode’s influential strength on Godthab’s temperature and precipitation, vary seasonally. In contrast with global average temperatures, Greenland has not experienced a continual warming trend since the 1950s; 30- and 10-year trends show a cooling period between 1965 and 1995. From 1866 to 2011, Godthab’s average annual temperature has increased by 1.9?C, and is anticipated to continue to warm in accordance with the global warming trend and the Arctic’s associated feedback mechanisms.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".