Dynamically Downscaled High-Resolution Hydroclimate Projections for Western Canada
Bibliographic record
Abstract
Abstract Accurate identification of the impact of global warming on water resources in major river systems represents a significant challenge to the understanding of climate change on the regional scale. Here, dynamically downscaled climate projections for western Canada are presented, and impacts on hydrological variables in two major river basins, the Fraser and Athabasca, are discussed. These regions are both challenging because of the complexity of the topography and important because of the economic activity occurring within them. To obtain robust projections of future conditions, and to adequately characterize the impact of natural variability, a small initial condition ensemble of independently downscaled climate projections is employed. The Community Earth System Model, version 1 (CESM1), is used to generate the ensemble, which consists of four members. Downscaling is performed using the Weather Research and Forecasting Model, version 3.4.1 (WRF V3.4.1), in a nested configuration with two domains at 30- and 10-km resolution, respectively. The entire ensemble was integrated for a historical validation period and for a mid-twenty-first-century projection period [assuming representative concentration pathway 8.5 (RCP8.5) for the future trajectory of greenhouse gases]. The projections herein are characterized by an increase in winter precipitation for the mid-twenty-first-century period, whereas net precipitation in summer is projected to decrease, due to increased evapotranspiration. In the Fraser River basin, a shift to more liquid precipitation and earlier snowmelt will likely reduce the seasonal variability of runoff, in particular the spring freshet. In the Athabasca River basin, winter precipitation and snowmelt may increase somewhat, but increasing evapotranspiration may lead to reduced streamflow in late summer.
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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 | 0.001 | 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 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".