The Role of Large-Scale Climate Modes in Regional Streamflow Variability and Implications for Water Supply Forecasting: A Case Study of the Canadian Columbia River Basin
Why this work is in the frame
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Bibliographic record
Abstract
The impacts of large-scale modes of climate variability on the annual cycle of terrestrial hydrometeorology in the Canadian Columbia River basin were assessed with the aim of updating our current understanding and identifying opportunities for climate-informed, early-season water supply forecasting. Composite analyses of streamflow from seven Water Survey of Canada gauging stations conditional on El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific/North American pattern (PNA), Arctic Oscillation (AO), and North Pacific Gyre Oscillation (NPGO) states revealed that hydrological impacts of a climate mode could be manifested through changes in the annual runoff volume and/or changes in seasonal runoff patterns. Responses were generally non-linear. Considering ENSO and the PDO, for instance, streamflow anomalies associated with their warm phases contrast with those associated with their cool phases; however, the warm phases tend to produce more consistent streamflow responses than the cool phases. More profoundly, the PNA and AO streamflow responses appear to be highly asymmetrical—only one phase (positive PNA and negative AO) is shown to significantly affect streamflow. Some North Pacific climate indices and ENSO show reasonably consistent and strong correlations with streamflow, which suggests that further refinement of climate-informed early season water supply forecasting is possible. It is shown that further improvement of forecast skills can be attained if North Pacific climate information is included in addition to ENSO in the current generation of operational statistical water supply forecast models.
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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 | 0.001 | 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 it