EarthCARE’s Broadband Radiometer: Uncertainties Associated with Cloudy Atmospheres
Bibliographic record
Abstract
Abstract The Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite’s Broadband Radiometer (BBR) consists of three telescopes and a rotating chopper drum (CD). Together they yield alternating measurements of total wave (TW; 0.25 to >50 μm) and shortwave (SW; 0.25–4 μm) radiances with point spread functions that translate to 0.6-km-diameter pixels. The mission requires that SW and TW radiances be averaged over 100-km2 domains. Correspondingly, the average longwave (LW) radiances are the differences between TW and SW averages. It is shown that impacts on domain-average nadir radiances resulting from alternating samples of TW and SW signals for realistic cloudy atmospheres are sensitive to the variance of cloudy-sky radiances, CD rotation rate, and along-track length of averaging domains. Over domains measuring 5 × 21 km2 and at a 50% rotation rate, uncertainties reached up to 3.2 and 4.1 W m−2 sr−1 for SW and TW radiances, respectively. The BBR’s design allows for in-flight alteration of the CD rate. An approximate method is provided for estimating SW and LW uncertainties resulting from the CD rate. While the nominal rotation rate meets EarthCARE’s mission requirements, reducing below 75% of that rate will lead to uncertainties for domain-average LW radiances that will often exceed mission requirements. This could be mitigated by increasing the size of averaging domains but that would compromise the BBR’s role in EarthCARE’s radiative closure assessment program. Uncertainties for off-nadir radiances are largely free of impacts arising from changes to the CD rotation rate.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".