Changes in seasonal land precipitation during the latter twentieth‐century
Bibliographic record
Abstract
Climate models predict substantial changes in seasonal precipitation in the future. Anthropogenic forcing has been found to contribute to the observed pattern of land precipitation change over the 2nd half of the 20th century when annual precipitation is averaged within latitude bands, the observed change was substantially larger than response simulated in climate models, based on a single observational dataset. Here we investigate the robustness of this finding using several land only observational datasets and look for an explanation for why observed changes are significantly larger. We show the discrepancy between model simulated and observed trends is reduced when changes are expressed as percent climatology, which reduces the difference in scale between observed point locations and model gridboxes. Focusing on seasonal rather than annual data reveals that there are seasonal differences in the pattern of zonal precipitation changes over the 20th century. We use fingerprint for zonal precipitation changes from 54 CMIP3 simulations and show that observed changes are detectable in all seasons but boreal summer (JJA), even when doubling the variance of the model simulation, and irrespective of the dataset used. The observed change is still larger than that simulated by the multi‐model mean in all datasets except in boreal summer but only in boreal spring is the observed change robustly and significantly larger than that simulated.
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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) | 0.001 | 0.001 |
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".