Temporal-Spatial Distribution of Stable Isotopes in Precipitation and Its Relationship with ENSO over the North America
Bibliographic record
Abstract
The characteristics of temporal-spatial distribution of δ~(18)O in precipitation and its relationships with temperature,precipitation amount and ENSO were analyzed in this study.The analyses show that the latitudinal distribution of the mean δ~(18)O in precipitation is very remarkable in the North America,regardless over lands or oceans.The mean δ~(18)O differences between continent and ocean are less besides high latitudes.With increasing latitude,the δ~(18)O in precipitation decreases quickly.It is found that the temperature effect appears over the whole North America continent,and becomes much more marked with increasing latitude.The variations of extension and intensity characterize a distributional difference of temperature effect on different seasons.The amount effect happens mainly in low-latitude oceans,east coast of the low-middle-latitude Pacific Ocean and northwest coast of Gulf Stream.However,no amount effect in inland.Similarly,the variations of extension and intensity characterize also a distributional difference of amount effect on different seasons.In inland and high latitudes of the North America,the Δδ~(18)O displays greater positive value corresponding to the distinct temperature effect;in low-latitude oceans,it does smaller or a negative value;and in the same latitudes,Δδ~(18)O in land is markedly greater than that in ocean.Furthermore,there are distinct positive correlations between SST in Nino-4 and δ~(18)O in precipitation at Ottawa and Midway Island that stand for continental and oceanic situations respectively,in which,the continuous correlations between the precipitation δ~(18)O in May and SST in Nioo-4 are remarkable,showing that the strong signal form ENSO has important impact on the variations of stable isotopes in precipitation of the land and the ocean in this period.
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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 | 0.000 |
| 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 | 0.000 |
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 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".