Global Climate
Bibliographic record
Abstract
Climate S28La Niña-the cool phase of the El Niño-Southern Oscillation (ENSO)-in the Pacific Ocean had a dampening effect on the global temperatures, in comparison to years characterized by El Niño or ENSO-neutral conditions.The year began with La Niña conditions, which first developed in August 2020 and persisted throughout most of 2021 and all of 2022 (see section 4b for details).2022 was also the warmest La Niña year on record, surpassing the previous record set in 2021.While it is common, and arguably expected, for each newly completed year to rank as a top 10 warmest year (see Arguez et al. 2020), the global annual temperature for 2022 was lower than we would expect due to the secular warming trend alone, with trend-adjusted anomalies registering between the 20th and 40th percentiles (depending on the dataset) following the Arguez et al. ( 2020) approach.Trend-adjusted anomalies for 2022 are consistent with the typical slight cooling influence of La Niña and similar to the trend-adjusted anomalies recorded over the relatively cool years from 2011 to 2014, as well as 2021, years that also predominantly exhibited cooler-than-normal ENSO index values.Above-normal temperatures were observed across much of the world's land and ocean surfaces during 2022 (Plate 2.1a; Appendix Figs.A2.1-A2.4).Notably, record-high annual temperatures were present across Europe, northern Africa, and parts of the Middle East, central Asia, and China, as well as the northern and southwestern Pacific, Atlantic, and Southern Oceans.Below-normal annual temperatures were present across parts of northern North America, South America, Africa, Australia, and the southeastern, central, and eastern tropical Pacific Ocean.The global land-only surface temperature was 0.30°C-0.49°Cabove normal, the fifth to seventh highest on record, depending on the dataset.The annual global sea-surface temperature was also fifth or sixth highest on record, at 0.19°C-0.26°Cabove normal.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".