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
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. RÉSUMÉ [Traduit par la rédaction] Nous avons estimé les répercussions des modes de variabilité climatique à grande échelle sur le cycle annuel de l'hydrométéorologie terrestre dans le bassin canadien du fleuve Columbia dans le but d'en actualiser notre compréhension et d'identifier des possibilités de prévisions d'apport d'eau fondées sur le climat faites en début de saison. Des analyses composites de l’écoulement fluvial faites à partir de sept stations hydrométriques de la Division des relevés hydrologiques du Canada en relation avec les états de l'oscillation australe El Niño (ENSO), de l'oscillation décennale du Pacifique (PDO), de la configuration Pacifique/Amérique du Nord (PNA), de l'oscillation arctique (AO) et de l'oscillation du gyre du Pacifique Nord (NPGO) ont révélé que les répercussions hydrologiques d'un mode climatique pouvaient se manifester comme des changements dans le volume d’écoulement annuel ou des changements dans les configurations d’écoulement saisonnier. Les réponses étaient en général non linéaires. Dans le cas de l'ENSO et de la PDO par exemple, les anomalies d’écoulement fluvial liées à leurs phases chaudes contrastent avec celles liées à leurs phases froides; les phases chaudes ont toutefois tendance à produire des réponses d’écoulement fluvial plus cohérentes que les phases froides. Plus en profondeur, les réponses de l’écoulement fluvial à la PNA et à l'AO apparaissent très asymétriques –une seule phase (la PNA positive et l'AO négative) semble modifier l’écoulement fluvial de façon appréciable. Certains indices climatiques du Pacifique Nord et l'ENSO affichent des corrélations raisonnablement régulières et fortes avec l’écoulement fluvial, ce qui donne à penser qu'il est possible d'améliorer les prévisions d'apport d'eau fondée sur le climat en début de saison. Nous montrons qu'il est possible d'améliorer l'habileté des prévisions si l'information climatique du Pacifique Nord est incluse en plus de l'ENSO dans la génération actuelle des modèles opérationnels statistiques de prévision d'apport d'eau.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".