Investigating Spatial Extremes of Annual Daily Precipitation Using CMIP6 Multi-Model Ensembles for Sustainable Flood Risk Assessment
Bibliographic record
Abstract
This study investigates the spatial characteristics of daily maximum precipitation for Prince Edward Island using a max-stable process model. The ssp126, ssp245, and ssp585 climate change scenarios, indicating low/optimistic, intermediate/in-between, and worst/pessimistic emissions scenarios, respectively, were extracted from 11 global climate model ensembles. For the time periods, the reference (historical) period was from 1971 to 2000, according to the World Meteorological Organization recommendations. Other time periods considered were 2011–2040, 2041–2070, and 2071–2100 as immediate, intermediate, and far future periods, respectively. The spatial trends analysis shows a west-to-east gradient throughout the entire study area. Return levels of 25 years were predicted for all the projections using the spatial generalized extreme value model fitted to the historical period, showing that topography should be included as a covariate in the spatial extreme model. Across the 134 grid points used in the study, the predicted return level for the historical period was 94 mm. Compared with the immediate time period, there is an increase of 47%, 53%, and 50% for the low, intermediate, and worst emission scenarios, respectively. For the intermediate period, there is an increase of 43%, 59%, and 56% for the low, intermediate, and worst emission scenarios, respectively. For the far future period, there is an increase of 49%, 48%, and 84% for the low, intermediate, and worst emission scenarios, respectively. There is a systematic increase in return levels based on the different periods. This shows a high chance of increased risks of extreme events of large magnitudes for this area in the immediate future through to the far future. This study will be useful for engineers, city planners, financial officials, and policymakers tasked with infrastructure development, long-term safety protocols, and sustainability and financial risk management.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".