Parametrization of instantaneous global horizontal irradiance: clear‐sky component
Bibliographic record
Abstract
Abstract Based on an accurate atmospheric radiative transfer scheme, a parametrization of instantaneous global horizontal irradiance (GHI) at the Earth's surface has been developed. The scheme is named SUNFLUX and this article describes the development of the scheme for clear‐sky conditions. The work dealing with clouds has been published in a separate article. Unlike traditional methods, this study applies the band model idea used in radiative transfer theory to the development of the surface radiation scheme and, importantly, includes absorption and scattering in the parametrization. Thus the scheme is more accurate compared with those using simple empirical approaches and may be applied to any site without being tuned for local conditions. The parametrization of aerosol transmittance and albedo developed by Kokhanovskyet al.is adopted to account for the effects of aerosols. All variables used in the scheme are available in climate models or from satellite observations. Therefore, the parametrization can be used to determine the GHI at the surface under clear‐sky conditions The scheme is evaluated using observations obtained from three US Atmospheric Radiation Measurement (ARM) stations and three stations on the Tibetan Plateau, and the results demonstrate that the scheme is accurate. The relative mean bias difference is less than 4.3% and the relative root‐mean‐squared difference is less than 0.09%.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".