Deciphering the role of evapotranspiration in declining relative humidity trends over land
Bibliographic record
Abstract
In recent decades, relative humidity (RH) over land has declined, driving increases in droughts and wildfires. Previous explanations attribute this trend to insufficient moisture advection from the ocean to sustain RH over land, but this ignores atmospheric moisture supplied from terrestrial evapotranspiration (E). While state-of-the-art climate models underestimate this RH trend, the reason behind this discrepancy remains unclear. Here, we decipher the influence of E on near-surface humidity using observations, reanalysis, and climate simulations. Global E in reanalysis has remained fairly steady in recent decades. Consequently, changes in ocean advection can reproduce observed RH declines without considering changes in E. Conversely, climate simulations estimate significant increases in E in recent decades, leading to model-based underestimation of observed RH declines. These findings suggest E intensifications may be overestimated in current climate models, thus underestimating coupled land-atmosphere drying in model output. We also highlight an upper limit of E change under observed RH trends, which could help benchmark global E trend analyses.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".