The Medieval Climate Anomaly in Oceania
Bibliographic record
Abstract
Temperatures in Oceania have risen by 0.5–1 °C over the past 100 years, resulting in significant retreat of New Zealand’s glaciers as an example. To better understand natural and anthropogenic contributions to this warming process, the observed climatic change must be placed in a longer-term palaeotemperature context. Of interest is the Medieval Climate Anomaly (MCA, 1000–1200 AD), a recognized period of natural pre-industrial climate change, associated with marked temperature and hydroclimatic variability that is best known from the Northern Hemisphere. Temperature reconstructions for Oceania were traditionally based on two classical tree ring series. Here, we enlarge the Oceania reference data set with another 13 published temperature reconstructions from SE Australia, New Zealand, and West Papua. These are based on a variety of proxy types and help to geographically and methodologically augment the regional palaeoclimate database. The proxy series have been thoroughly compared and the MCA trends palaeoclimatologically mapped. Ten out of the 15 sites show a relatively warm MCA, compared to the last 1500 years, with warming generally occurring in the envelope period 900–1500 AD. In some sites of SE Australia and at the west coast of New Zealand’s South Island, warming appears to be delayed by 200–300 years. The end of the medieval warming at around 1500 AD occurred about two centuries later than on most other continents, suggesting a possible interhemispheric climate lag mechanism possibly involving deep-water circulation. Likely drivers for the medieval warming in Oceania are atmospheric-ocean cycles such as the Southern Annular Mode and El Niño-Southern Oscillation, in combination with solar activity changes. MCA palaeotemperature data are still lacking for large parts of Oceania, namely the arid and tropical parts of Australia, Micronesia, central and northern Polynesia, as well as central and eastern Melanesia, highlighting the need for future research.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 0.005 |
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".