Suomi‐NPP CrIS radiometric calibration uncertainty
Bibliographic record
Abstract
Abstract The Cross‐track Infrared Sounder (CrIS) is the high spectral resolution spectroradiometer on the Suomi National Polar‐Orbiting Partnership (NPP) satellite, providing operational observations of top‐of‐atmosphere thermal infrared radiance spectra for weather and climate applications. This paper describes the CrIS radiometric calibration uncertainty based on prelaunch and on‐orbit efforts to estimate calibration parameter uncertainties, and provides example results of recent postlaunch validation efforts to assess the predicted uncertainty. Prelaunch radiometric uncertainty (RU) estimates computed for the laboratory test environment are less than ~0.2 K 3 sigma for blackbody scene temperatures above 250 K, with primary uncertainty contributions from the calibration blackbody temperature, calibration blackbody reflected radiance terms, and detector nonlinearity. Variability of the prelaunch RU among the longwave band detectors and midwave band detectors is due to different levels of detector nonlinearity. A methodology for on‐orbit adjustment of nonlinearity correction parameters to reduce the overall contribution to RU and to reduce field of view (FOV)‐to‐FOV variability is described. The resulting on‐orbit RU estimates for Earth view spectra are less than 0.2 K 3 sigma in the midwave and shortwave bands, and less than 0.3 K 3 sigma in the longwave band. Postlaunch validation efforts to assess the radiometric calibration of CrIS are underway; validation results to date indicate that the on‐orbit RU estimates are representative. CrIS radiance products are expected to reach “Validated” status in early 2014.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".