Changes in New Zealand pan evaporation since the 1970s
Bibliographic record
Abstract
Several previous studies have reported declines in pan evaporation rate throughout the Northern Hemisphere of about 2–4 mm a−2 for various periods since the 1950s. A recent analysis of Australian pan evaporation reported a similar decline and raises the possibility that part of the phenomenon may be related to the greenhouse effect. To assess that possibility, one needs to know whether the decline in evaporative demand is happening in other parts of the Southern Hemisphere. As a first step to addressing the latter question, we examined the trend in pan evaporation at 19 New Zealand sites. We found statistically significant declines in pan evaporation rate at 6 of the 19 sites. There were no sites with statistically significant increases in pan evaporation. When averaged across all 19 sites, the decline in pan evaporation rate was roughly 2 mm a−2 (i.e. mm per annum per annum) since the 1970s. Over a 30-year period, this is equivalent to a decline of about 60 mm a−1 in annual pan evaporation. These results are generally consistent with those reported throughout the Northern Hemisphere and in Australia. We conclude that the trend for decreasing evaporative demand previously reported throughout the Northern Hemisphere terrestrial surface may also be widespread in the Southern Hemisphere. This may be, in part, a greenhouse-related phenomenon. Copyright © 2005 Royal Meteorological Society.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".