Global Moisture Cycling Rate an Important Control on Regional-Mean Precipitation under Warming
Bibliographic record
Abstract
Abstract This study presents an updated framework for understanding regional precipitation change under climate forcing. We propose that most adjustments in zonal-mean precipitation can be explained by three additive drivers: Changes in global evaporation alter the overall availability of moisture for precipitation, shifts in the global moisture cycling rate affect the distance over which moisture is transported before precipitating, and atmospheric circulation adjustments further moderate changes in moisture transport distance. The global cycling rate of atmospheric moisture effectively explains many key features of the spatial pattern of zonal-mean precipitation change, including the well-documented “wet-get-wetter, dry-get-drier” response. Furthermore, we find that the response of the global moisture cycling rate and its corresponding impact on moisture transport distance are robust across several state-of-the-art Earth system models and forcing scenarios. Given the high level of certainty in how the global moisture cycling rate adjusts to warming, we can use the proposed framework to better understand, observe, and project changes in regional-mean precipitation under current climate change.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".