Spatial datasets of CMIP6 climate change projections for Canada and the United States
Bibliographic record
Abstract
Geospatial climate change projections are critical for assessing climate change impacts and adaptations across a wide range of disciplines. Here we present monthly-based grids of climate change projections at a 2-km resolution covering Canada and the United States. These data products are based on outputs from the 6th Coupled Model Intercomparison Project (CMIP6) and include projections for 13 General Circulation Models (GCMs), three Shared Socio-economic Pathways (SSP1 2.6, SSP2 4.5, and SSP5 8.5), four 30-year time periods (2011-2040, 2021-2050, 2041-2070, and 2071-2100), and a suite of climate variables, including monthly maximum and minimum temperature, precipitation, climate moisture index, and various bioclimatic summaries. The products employ a delta downscaling method, which combines historical normal values at climate stations with broad-scale change projections (or deltas) from GCMs, followed by spatial interpolation using ANUSPLIN. Various quality control efforts, described herein, were undertaken to ensure that the final products provided reasonable estimates of future climate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".