Clear sky UV simulations in the 21st century based on ozone and temperature projections from Chemistry-Climate Models
Bibliographic record
Abstract
Abstract. We have used total ozone columns and vertical profiles of ozone and temperature from 11 coupled Chemistry-Climate Models (CCMs) to project future solar ultraviolet radiation levels at the surface in the 21st century. The CCM simulations are used as input to a radiative transfer model for the simulation of the corresponding future UV irradiance levels under cloud free conditions, presented here as time series of monthly erythemal irradiance received at the surface during local noon covering the period 1960 to 2100. Starting from the first decade of the 21st century, the surface erythemal irradiance decreases globally as a result of the projected ozone recovery, at rates which are larger in the first half of the 21st century, compared to the period up to 2100. The magnitude of these decreases varies with latitude and is more pronounced at areas where ozone has been depleted most considerably after 1980. Over midlatitudes surface erythemal irradiance decreases between 5 and 15% by 2100 relative to 2000, while at the southern high latitudes these changes are twice as much. Climate change may affect future cloudiness, surface reflectivity and tropospheric aerosol loading, the effects of which are not included in this study. Therefore, the actual changes in future UV radiation are likely to change accordingly in the areas affected.
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 | 0.000 | 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) | 0.002 | 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".