Assessing the Impacts of Climate Change on Future Precipitation Trends Based on Downscaled CMIP5 Simulations Data
Bibliographic record
Abstract
This study investigates future changes in precipitation over the CRB (Columbia River Basin) in both wet (DJF) and dry (JJA) seasons under RCP85 GHG emission scenario. The simulations from four climate models which participated in CMIP5 (Coupled Model Intercomparison Project Phase-5) were downscaled using the BCSD (Bias Correction and Spatial Disaggregation) method. After downscaling, extreme value analysis and MME (Multi Model Ensemble) averaging is performed. This study focuses on computing 2, 5, 10 and 25 years return levels for both winter (DJF) and summer (JJA) seasons. The maximum winter precipitation values for 2, 5, 10 and 25 years return periods have been estimated to be about 112, 127, 148 and 171 mm/day respectively whereas the maximum summer precipitation values for 2, 5, 10 and 25 years return periods are observed to be about 56, 81, 96 and 126 mm/day respectively. The MME average outperformed the individual models in simulating the historical precipitation in both seasons. The MME results showed a consistent and significant increase in the extreme precipitation and decrease in mean precipitation in both future wet and dry seasons. Largest increase in precipitation occurs over the higher elevations of the Cascades Range, Coast Range and the Mountainous Range.
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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 | 0.001 | 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".