Hydroclimatic Scenarios Using Dendroclimatic, Historical and GCM-Based Records Over the Northwestern Great Plains
Bibliographic record
Abstract
Historically, the Canadian Prairies have been highly susceptible to extreme drought and pluvial events, resulting in economic hardship. There are strong associations between large-scale circulation patterns (i.e. teleconnections), such as the low frequency Pacific Decadal Oscillation (PDO), and higher frequency El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation/Arctic Oscillation (NAO/AO), and the interannual to multi-decadal hydroclimatic variations over western North American. Archives of the longest instrumental period of record (~100 to 150 years) are unlikely to capture the full range of hydroclimatic variability (50-70 years) or enable full assessment of the links between the large-scale circulation patterns and the regional moisture conditions. Multi-centennial, seasonal paleoclimatic reconstructions were derived for the northwestern Great Plains using tree-rings located along the eastern Rocky Mountains of Alberta and Montana. The variability in these hydroclimatic reconstructions was explored on time scales of decadal to multi-decadal to assess the coherence between natural climate oscillations and the frequency, severity and duration of drought and excess precipitation. The results suggest that drought events are often associated with the positive phase of the PDO and increased ENSO variance. The association between pluvial events and the phases of the PDO and ENSO are not as clearly defined as the drought events. Due to the non-stationarity of the climate system, these historical climate trends and climate variability cannot be projected forward. However, water managers, stakeholders and policy makers are concerned how anthropogenic climate change will alter these natural variability patterns. Global Climate Models (GCMs) are the only credible tool to derive future climate scenarios. Scenarios of future climate change and hydroclimatic variability were derived using ten GCMs and three emission scenarios, with numerous runs, that were best able to replicate the 20th Century temporal and spatial characteristics of the relevant teleconnection patterns and the hydroclimatic variability recorded in our tree-ring network. The multi-model mean future PDO projections, for the early half of the 21st century, show a weak shift towards more negative PDO-like conditions; however, the GCMs were split between those showing a shift, often significant, between the more negative and positive PDO-like conditions for all three scenarios. This thesis is the first to: explore the pre-instrumental relationship between extreme events, as identified using a paleoclimatic moisture reconstruction, and the largescale circulation patterns (PDO and ENSO); explicitly project the PDO as calculated by Empirical Orthogonal Function Analysis of North Pacific sea surface temperature residuals; and, develop future scenarios of variability that incorporate the PDO, ENSO and NAO. This complementary analysis, of inferred, instrumental and modeled hydroclimate change and variability, produced a long-term time series to provide perspective on low-frequency natural climate variability and explore the potential future impacts of greenhouse gas warming on the large-scale atmosphere-ocean circulation linked with these hydroclimate oscillations. Risk assessments will help identify our vulnerability, and increase our adaptive capacity, to projected changes in water quantity and quality, introduction of new diseases (waterborne or airborne), insect infestations, shifts to fire occurrence and some of the economic concerns associated with changes and uncertainties to the hydroclimate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".