Dataset of future-shifted weather files for Canada using climate projections from CMIP6
Bibliographic record
Abstract
Investigating energy use in new building designs or existing structures in Canada is often performed with energy models that incorporate present-day climate information from the Canadian Weather Year for Energy Calculation 2020 (CWEC2020) weather files. Here we present a new dataset of future-shifted versions of these weather files that have been produced at all CWEC2020 sites across Canada, incorporating projections from the latest generation of climate models from CMIP6. These future-shifted files have been generated using a weather file "morphing" procedure applied to adjust hourly time series of selected thermodynamic variables including dry bulb and dew point temperature, relative humidity, and surface pressure. Projected changes used to calculate morphing factors were taken from CMIP6 global climate models following low, medium and high future emissions pathways (SSP1 2.6, SSP2 4.5, SSP5 8.5). Using the projections from each pathway, future-shifted files have been produced for five future periods from the 2040s through the 2080s. These files facilitate the use of energy modelling to understand building performance and guide design choices for infrastructure under future climate change. All of the future-shifted CWEC2020 files are publicly available via the Pacific Climate Impacts Consortium (PCIC) Weather Files Data Portal at https://www.pacificclimate.org/data/weather-files.
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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 | 0.001 |
| 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".