Comparison of daily UV doses estimated from Nimbus 7/TOMS measurements and ground‐based spectroradiometric data
Bibliographic record
Abstract
During recent years, methods have been developed for estimating UV irradiance reaching the Earth's surface using satellite‐measured backscattered UV radiances. The NASA‐developed method is based on radiative transfer calculations and satellite measurements of parameters affecting UV radiation: extraterrestrial solar irradiance, atmospheric ozone, cloud reflectivity, aerosol amounts, and ground albedo. In this work a comparison is made between daily UV erythemal doses estimated from Nimbus‐7/TOMS measurements (from 1991 to May 1993) and those calculated from ground‐based spectroradiometer data. Three stations operated by the National Science Foundation were chosen for this comparison: Ushuaia, Argentina (for 573 days), Palmer, Antarctica (for 450 days), and San Diego, California, (for 149 days). These stations were selected to illustrate the differences between ground‐based measurements using the same type of instrument, SUV‐100 double monochromator spectroradiometers, and satellite estimates of surface UV irradiance under three different environmental conditions (mountains and snow, nearly continuous snow cover, and midlatitude urban sea level conditions). Averaging the measured and TOMS‐estimated doses over periods from 1 week to 1 month improves the agreement. The daily or monthly mean bias increases during months when there is snow/ice on the surface. TOMS has a larger estimate of the UV irradiance by 25% at San Diego (no snow), in agreement with the summer‐month analysis of Toronto irradiances [ Herman et al. , 1999]. TOMS underestimates the average daily‐UV dose at Ushuaia (monthly mean bias of −13%) and at Palmer (−35%) consistent with snow/ice with cloud effects not being properly accounted for in the TOMS algorithm. When the reflectivity at all three sites is low (no snow), the TOMS irradiance estimate is larger than the SUV‐100 measurements consistent with previously analyzed Brewer data at Toronto. The effects of local fog or clouds smaller than the satellite field of view and undetected UV‐absorbing aerosols near the ground are discussed. In addition to uncertainties in radiometric calibrations of the spectrometers, none of the SUV‐100 data are corrected for deviations of diffuser‐transmittance from true cosine response.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".