Multifractal analysis of the evolution of simulated precipitation over France in a climate scenario
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Bibliographic record
Abstract
Multifractal techniques are applied to the study of rainfall daily time series over France simulated by the climate model CNRM-CM3 of Météo France in a coupled climate scenario A2 over the period 1860–2100. We quantify the scaling variability of the simulated rainfall with the help of a few relevant multifractal exponents characterizing the intermittency and multifractality of the field. These multifractal exponents are determined by the Double Trace Moment (DTM), which shows a scaling range from one day to about 16 days. The opposite trends found in the evolution of the intermittency and multifractality exponents have contradictory effects on the evolution of the extremes. However, a refined analysis shows that due to the dominant effect of intermittency increase, we may expect an effective increase of rainfall extremes for the next hundred years.
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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 | 0.002 |
| 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) | 0.000 | 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 it