Biophysical Impacts of Land Use Change over North America as Simulated by the Canadian Regional Climate Model
Bibliographic record
Abstract
This study investigates the biophysical impacts of human-induced land use change (LUC) on the regional climate of North America, using the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two simulations are performed with CRCM5 using different land cover datasets, one corresponding to the potential vegetation and the other corresponding to current land use, spanning the 1988–2012 period, driven by European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA)-Interim at the lateral boundaries. Comparison of the two suggests higher albedo values, and therefore cooler temperatures, over the LUC regions, in the simulation with LUC, in winter. This is due to the absence of crops in winter, and also possibly due to a snow-mediated positive feedback. Some cooling is observed in summer for the simulation with LUC, mostly due to the higher latent heat fluxes and lower sensible heat fluxes over eastern US. Precipitation changes for these regions are not statistically significant. Analysis of the annual cycles for two LUC regions suggests that the impact of LUC on two meter temperature, evapotranspiration, soil moisture and precipitation are present year round. However, the impact on runoff is mostly restricted to the snowmelt season. This study thus highlights regions and variables most affected by LUC over North America.
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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) | 0.001 | 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 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".