Attributing intensification of precipitation extremes to human influence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study provides estimates of the human contribution to the observed widespread intensification of precipitation extremes. We consider the annual maxima of daily (RX1day) and 5 day consecutive (RX5day) precipitation amounts over the Northern Hemisphere land area for 1951–2005 and compare observed changes with expected responses to external forcings as simulated by multiple coupled climate models participating in Coupled Model Intercomparison Project Phase 5. The effect of anthropogenic forcings can be detected in extreme precipitation observations, both individually and when simultaneously estimating anthropogenic and naturally forced changes. The effect of natural forcings is not detectable. We estimate that human influence has intensified annual maximum 1 day precipitation in sampled Northern Hemisphere locations by 3.3% [1.1% to 5.8%, >90% confidence interval] on average. This corresponds to an average intensification in RX1day of 5.2% [1.3%, 9.3%] per degree increase in observed global mean surface temperature consistent with the Clausius‐Clapeyron relationship.
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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 | 0.001 | 0.001 |
| 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 | 0.002 |
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