Are there interactive effects of physiological and radiative forcing produced by increased CO2 concentration on changes of land hydrological cycle?
Bibliographic record
Abstract
Three coupled climate–carbon cycle models including CESM (Community Earth System Model), CanEsm (the Canadian Centre for Climate Modelling and Analysis Earth System Model) and BCC (Beijing Climate Center Climate System Model) were used to estimate whether changes in land hydrological cycle responded to the interactive effects of CO 2 -physiological forcing and CO 2 -radiative forcing. No signs could be indicated that the interactive effects of CO 2 -physiological forcing and CO 2 -radiative forcing on the hydrological variables (e.g. precipitation, evapotranspiration and runoff) were detected at global and regional scales. For each model, increases in precipitation, evapotranspiration and runoff (e.g. 0.37, 0.18 and 0.25 mm/year 2 ) were simulated in response to CO 2 -radiative forcing (experiment M3). Decreases in precipitation and evapotranspiration (about − 0.02 and − 0.09 mm/year 2 ) were captured if the CO 2 physiological effect was only accounted for (experiment M2). In this experiment, a reverse sign in runoff (the increase of 0.08 mm/year 2 ) in contrast to M3 is presented. All models simulated the same signs across Eastern Asia in response to the CO 2 physiological forcing and radiative forcing: increases in precipitation and evapotranspiration only considering greenhouse effect; reductions in precipitation and evapotranspiration in response to CO 2 -physiological effect; and enhanced trends in runoff from all experiments. However, there was still a large uncertainty on the magnitude of the effect of transpiration on runoff (decreased transpiration accounting for 8% to 250% of the increased runoff) from the three models. Two models (CanEsm and BCC) attributed most of the increase in runoff to the decrease in transpiration if the CO 2 -physiological effect was only accounted for, whereas CESM exhibited that the decrease in transpiration could not totally explain the increase in runoff. The attribution of the CO 2 -physiological forcing to changes in stomatal conductance versus changes in vegetation structure (e.g. increased Leaf Area Index) is an issue to discuss, and among the three models, no agreement appeared.
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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 | 0.000 | 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) | 0.000 | 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 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".