IMPACT OF THE RCP8.5 SCENARIO ON AGROCLIMATIC INDICES IN WESTERN CANADA FROM CONVECTION-PERMITTING CLIMATE SIMULATIONS
Bibliographic record
Abstract
Climate change has the potential to alter growing seasons worldwide. This study evaluates how agroclimatic indices and hotspots for compound events related to cool-season crops in Western Canada may change under the RCP8.5 scenario, using high-resolution climate data. The study employed a convection-permitting Weather Research and Forecasting model simulation for the current climate (CTL, 2000–2015) and future climate under the high-end emission scenario based on a pseudo-global-warming (PGW) approach. The multivariate quantile mapping method was applied to CTL and PGW to bias-correct the simulations to the GEM-CaPA dataset. An evaluation of the CTL simulation of daily temperatures and precipitation during the growing season against the gridded observation shows good agreement in Western Canada. The CTL captured the spatial pattern of agroclimatic indices and the hotspots of compound events, especially in the major croplands. Rising temperatures will result in substantial increases in growing degree-days (GDD) and reductions in frost days, favoring the expansion of crop fields and pushing temperatures to optimal conditions of growth for cool-season crops. However, plant heat stress and Temperature Humidity Index will substantially increase in the southern prairies, Okanagan, and the Fraser Valley offsetting the positive effects caused by the reduction in frost days and increases in GDD. Extended dry days coupled with substantial increases in precipitation intensity in the future growing season will lead to scarce (surplus) water at different stages of crop growth. The joint exceedance frequency of compound events related to extreme heat is projected to increase by up to 15 days per season, while events of cool waves and drought co-occurring will reduce in the major croplands by the end of the 21st century. The significant increases in heat-related ACIs, reduction in the frequency of precipitation while intensities increase, and the increased frequency of compound events suggest global warming will pose immense challenges to crop production on the Canadian prairies.
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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 | 0.001 |
| 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) | 0.023 | 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".