Validation of Environment Canada and NOAA UV Index Forecasts with Brewer Measurements from Canada
Bibliographic record
Abstract
Abstract Ground-based ultraviolet (UV) irradiance measurements by Brewer spectrophotometers at 10 sites across Canada are compared with UV index forecasts for the same locations from Environment Canada (EC) and NOAA. For the EC forecast validation, summertime (May–August) data for the period from 1996 to 2009 are used. Comparison with NOAA forecasts is made for the more limited period of May–August 2006 and 2007. Several statistical measures are used, including the mean and the standard deviation of differences, correlation coefficients, and the probability of detection and false-alarm rate for prediction of high (UV index of 6 or above) values. For most conditions, only modest differences are found between the two forecasting systems; that is, UV index forecasts reported in the United States and Canada for Canadian sites are compatible. In general, the physically based NOAA system, which started operation in 2005, performs better than the semiempirical EC model, developed in the mid-1990s. The difference in model performance is not large under clear-sky and light-cloud conditions, but the EC model underperforms relative to the NOAA model under heavy-cloud and rainy conditions. Both the EC and the NOAA forecast models tend to overestimate UV under clear-sky and light-cloud conditions. Under heavy-cloud and rainy conditions, the EC model underestimates UV values, with about 30% of all forecasts under these conditions being 2 or more units below observations. NOAA forecasts tend to overestimate UV index values under these conditions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".