Global changes in extreme daily temperature since 1950
Bibliographic record
Abstract
Extreme value analysis of observed daily temperature anomalies from a new quasi‐global data set indicates that extreme daily maximum and minimum temperatures (>98.5 or <1.5 percentile) have warmed for most regions since 1950. Changes in extreme anomalous daily temperatures are determined by fitting extreme value distributions with time‐varying parameters. Changes in the distribution of anomaly exceedances above a high threshold are found to be statistically significant at the 10% level for most land areas when compared with a time‐invariant distribution and with the unforced natural variability produced by a coupled climate model. The largest positive trends in the location parameter of the extreme distribution are found in Canada and Eurasia where daily maximum temperatures have typically warmed by 1 to 3°C since 1950. The total area exhibiting positive trends is significantly greater than can be attributed to unforced natural variability. For most regions, positive trend magnitudes are larger and cover a greater area for daily minimum temperatures than for maximum temperatures. The comparatively small areas of cooling are found to be consistent with unforced natural climate variability. The North Atlantic Oscillation (NAO) is found to have a significant influence on extreme winter daily temperatures for many areas, with a negative NAO of one standard deviation reducing expected extreme winter daily temperatures by ∼2°C over Eurasia but increasing temperatures over northeastern North America.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".