The future of droughts in Iran according to CMIP6 projections
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Anthropogenic climate change is exerting immense pressure on water resources in Iran. This study investigates future precipitation and meteorological droughts across the country considering performances of 41 general circulation models (GCMs). The findings indicate a significant increase in long-term average annual precipitation (LAAP) across Iran with an overall north-to-south increasing gradient, particularly in areas prone to extreme events. However, focusing solely on LAAP is misleading. Projected precipitation reveals substantial inter-annual variability, impacting both the severity and duration of meteorological droughts. For instance, 100-year return period droughts are expected to intensify in severity (The Shared Socio-economic Pathway SSP1-2.6: 4–91%, SSP8-5.5: 46–204%) and duration (SSP1-2.6: 19–76%, SSP8-5.5: 40–127%) across most regions, except the Persian Gulf coastal zone, where droughts may become less severe (SSP1-2.6: 23%, SSP8-5.5: 23%) and shorter in duration (SSP1-2.6: 27%, SSP8-5.5: 10%). Additionally, bivariate frequency analysis suggests that major droughts could become significantly more frequent in the future.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it