Separating the Impact of Individual Land Surface Properties on the Terrestrial Surface Energy Budget in both the Coupled and Uncoupled Land–Atmosphere System
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Changes in the land surface can drive large responses in the atmosphere on local, regional, and global scales. Surface properties control the partitioning of energy within the surface energy budget to fluxes of shortwave and longwave radiation, sensible and latent heat, and ground heat storage. Changes in surface energy fluxes can impact the atmosphere across scales through changes in temperature, cloud cover, and large-scale atmospheric circulation. We test the sensitivity of the atmosphere to global changes in three land surface properties: albedo, evaporative resistance, and surface roughness. We show the impact of changing these surface properties differs drastically between simulations run with an offline land model, compared to coupled land–atmosphere simulations that allow for atmospheric feedbacks associated with land–atmosphere coupling. Atmospheric feedbacks play a critical role in defining the temperature response to changes in albedo and evaporative resistance, particularly in the extratropics. More than 50% of the surface temperature response to changing albedo comes from atmospheric feedbacks in over 80% of land areas. In some regions, cloud feedbacks in response to increased evaporative resistance result in nearly 1 K of additional surface warming. In contrast, the magnitude of surface temperature responses to changes in vegetation height are comparable between offline and coupled simulations. We improve our fundamental understanding of how and why changes in vegetation cover drive responses in the atmosphere, and develop understanding of the role of individual land surface properties in controlling climate across spatial scales—critical to understanding the effects of land-use change on Earth’s climate.
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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 | 0.003 | 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 it