Broadband Radiative Quantities for the EarthCARE Mission: The ACM-COM and ACM-RT Products
Bibliographic record
Abstract
Abstract. The EarthCARE satellite mission’s objective is to retrieve profiles of aerosol and water cloud physical properties from measurements made by its cloud-profiling radar, backscattering lidar, and passive multi-spectral spectral imager (MSI). These retrievals, together with other geophysical properties, are input into broadband (BB) radiative transfer (RT) models that predict radiances, and fluxes, commensurate with measurements made, and inferred from, EarthCARE’s BB radiometer (BBR). The scientific goal is that modelled and “observed” BB fluxes differ, on average, by less than ±10 W m-2. When sound synergistic retrievals from the ACM-CAP process are available, they are acted on by the RT models. When they are not available, the RT models act on “composite” atmospheric profiles of retrievals from individual sensors. “Compositing” is performed in the ACM-COM process as described in this report. The majority of this report describes the RT models, and their products, that make-up Earth-CARE’s ACM-RT process. Shortwave (SW) and longwave (LW) flux and heating rate (HR) profiles are computed by 1D RT models for each ~1 km nadir column of inferred properties. 3D RT models compute radiances for the BBR’s three viewing directions, with the SW model also computing flux and HR profiles; the 3D LW model produces upwelling flux at just one level. All 3D RT products are averages over 5 x 21 km “assessment domains” that are constructed using MSI data. A subset of ACM-RT’s products is passed forward to the “radiative closure assess-ment” process that quantifies, for each assessment domain, the likelihood that EarthCARE’s goal has been achieved. As EarthCARE represents the first mission to make “operational” use of 3D RT models, emphasis in this report is placed on differences between 1D and 3D RT results. For upwelling SW flux at 20 km altitude, 1D and 3D values can be expected to differ by more than EarthCARE’s scientific goal of ±10 W m-2 at least 50 % of the time.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".