AN ULTRAVIOLET (290 TO 325 NM) IRRADIATION MODEL FOR SOUTHERN CANADIAN CONDITIONS
Bibliographic record
Abstract
A numerical model to estimate spectral and broadband ultraviolet irradiance (290 to 325 nm) for Canadian conditions is described and validated with Brewer spectro-radiometer measurements at four stations. The model applies the delta-Eddington algorithm to a 50-level, 100-km, plane-parallel atmosphere with cloud inserted between 2 and 3 km. It requires measured total atmospheric ozone depth and hourly observations of cloud amount. In the absence of ozone soundings, model ozone profiles are scaled by the ratio of measured (from the Brewer instrument) to model total atmospheric ozone depths. In the model calculations, SUSIM ATLAS 3 extraterrestrial irradiance measurements are averaged for each nanometer of wavelength to mimic the triangular filter used by the Brewer instrument. Ozone absorption is calculated from the temperature-dependent coefficients of Pauer and Bass (1985), Rayleigh optical depths after Elterman (1968), and aerosol optical properties from MODTRAN. Surface albedo is a function of snow depth and 0.05 for snow-free ground. Model and measured spectral irradiances for cloudless skies agree well, but model values are smaller than measurements for wavelengths below about 305 nm because of enhancement of the Brewer signal by stray light. Model values of daily cloudless sky irradiance using lidar aerosol optical depth measurements from York University after the Mt. Pinatubo eruption in 1991 agree well with measurements. Cloud optical depths were calculated iteratively for overcast conditions. A fixed optical depth of 45 was used to calculate cloudy sky irradiances at the four stations. These agree well with measurements. Mean bias error (MBE) is less than 5% of the mean measured daily irradiance and root mean square error (RMSE) less than 25%, decreasing to below 12% for 10-day averages. Agreement between mean daily measured and calculated spectral irradiances over a month is also good. [Key words: radiation modeling, ultraviolet irradiance, cloud optical depth.]
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".