An Extensive Comparison of Commercial Pyrheliometers under a Wide Range of Routine Observing Conditions
Bibliographic record
Abstract
Abstract In the most comprehensive pyrheliometer comparison known to date, 33 instruments were deployed to measure direct normal solar radiation over a 10-month period in Golden, Colorado. The goal was to determine their performance relative to four electrical-substitution cavity radiometers that were calibrated against the World Radiometric Reference (WRR) that is maintained at the World Radiation Center in Davos, Switzerland. Because of intermittent cabling problems with one of the cavity radiometers, the average of three windowed, electrical-substitution cavity radiometers served as the reference irradiance for 29 test instruments during the 10-month study. To keep the size of this work manageable, comparisons are limited to stable sunny conditions, passing clouds, calm and windy conditions, and hot and cold temperatures. Other variables could have been analyzed, or the conditions analyzed could have employed higher resolution. A more complete study should be possible now that the instruments are identified; note that this analysis was performed without any knowledge on the part of the analyst of the instruments’ manufacturers or models. Apart from the windowed cavities that provided the best measurements, two categories of performance emerged during the comparison. All instruments exceeded expectations in that they measured with lower uncertainties than the manufacturers’ own specifications. Operational 95% uncertainties for the three classes of instruments, which include the uncertainties of the open cavities used for calibration, were about 0.5%, 0.8%, and 1.4%. The open cavities that were used for calibration of all pyrheliometers have an estimated 95% uncertainty of 0.4%–0.45%, which includes the conservative estimate of 0.3% uncertainty for the WRR.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".