The Performance of Current Atmospheric Radiation Codes in Phase I of CIRC
Bibliographic record
Abstract
The Continual Intercomparison of Radiation Codes (CIRC) is intended as an evolving and regularly updated reference source for evaluation of radiative transfer (RT) codes used in Global Climate Models and other atmospheric applications. In our presentation we will discuss our evaluation of the performance of 13 shortwave and 11 longwave RT codes that participated in Phase I of CIRC. CIRC differs from previous intercomparisons in that it relies on an observationally validated catalogue of cases. The seven CIRC Phase I baseline cases, five cloud-free, and two with overcast liquid clouds, are built around observations by the Atmospheric Radiation Measurements (ARM) program that satisfy the goals .of Phase I, namely to examine RT model performance in realistic, yet not overly complex, atmospheric conditions. Besides the seven baseline cases, additional idealized "subcases" are also examined to facilitate interpretation of model errors. We will quantify individual model performance with respect to reference line-by-line calculations, and will also highlight RT code behavior for conditions of doubled CO2 , aspects of utilizing a spectral specification of surface albedo, and the impact of the inclusion of scattering in the thermal infrared. Our analysis suggests that RT codes should work towards improving their calculation of diffuse shortwave flux, shortwave absorption, treatment of spectral surface albedo, and shortwave CO2 forcing. Despite practical difficulties in comparing our results to previous results by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) conducted about 20 years ago, it appears that the current generation of RT codes do indeed perform better than the codes of the ICRCCM era. By enhancing the range of conditions under which participating codes are tested, future CIRC phases will hopefully allow even more rigorous examination of RT code performance.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".