Reduced terrestrial evaporation increases atmospheric water vapor by generating cloud feedbacks
Bibliographic record
Abstract
Abstract Reduced terrestrial evaporation directly warms the surface by reducing latent cooling, but also indirectly modifies surface climate by altering atmospheric processes. We use a global climate model to explore two end cases of terrestrial evaporation, comparing the climate of SwampLand, a world where land is always fully saturated with water, to that of DesertLand, where land is always completely lacking in soil moisture. When we suppress evaporation to create a desert-like planet, we find that temperatures increase and precipitation decreases in the global mean. We find an increase in atmospheric water vapor over both land and ocean in the DesertLand simulation. Suppressing evaporative cooling over the continents reduces continental cloud cover, allowing more energy input to the surface and increasing surface moist static energy over land. The residence time of atmospheric water vapor increases by about 50 percent. Atmospheric feedbacks such as changes in air temperatures and cloud cover contribute larger changes to the terrestrial surface energy budget than the direct effect of suppressed evaporation alone. Without the cloud feedback, the land surface still warms with suppressed land evaporation, but total atmospheric water vapor decreases, and the anomalous atmospheric circulations over the continents are much shallower than in simulations with cloud changes; that is, the cloud feedback changes the sign of the water vapor response. This highlights the importance of accounting for atmospheric feedbacks when exploring land surface change impacts on the climate system.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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; both teacher heads agree on what is shown here.
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".