Global observations of HNO<sub>3</sub> from the High Resolution Dynamics Limb Sounder (HIRDLS): First results
Bibliographic record
Abstract
We present the first evaluation of the HNO3 data product (version 2.04.09) from the High Resolution Dynamics Limb Sounder (HIRDLS) on the Earth Observing System (EOS) Aura satellite. The HIRDLS instrument obtains between 5000 and 7000 HNO3 profiles per day. HIRDLS HNO3 data are generally good over the latitude range of 64°S to 80°N and pressure range 100 to 10 hPa, with some profiles, depending on latitude, having useful information between 100 to 161 hPa. The individual profile “measured” precision is between 10 and 15%, but can be much larger if the HNO3 abundance is low or outside the 100 hPa to 10 hPa range. Global results are compared with the HNO3 observations from version 2.2 of the EOS Aura Microwave Limb Sounder (MLS), and it is found that large‐scale features are consistent between the two instruments. HIRDLS HNO3 is biased 0–20% low relative to Aura MLS in the mid‐to‐high latitudes and biased high in the tropical stratosphere. HIRDLS HNO3 is also compared with Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE‐FTS). In these mostly high‐latitude comparisons the HIRDLS HNO3 data are biased 10–30% low, depending on altitude. Finally, the HIRDLS HNO3 is compared to in situ data taken by the NOAA Chemical Ionization Mass Spectrometer (CIMS) instrument flown during the 2005 NASA Houston Aura Validation Experiment (AVE) and the ability of HIRDLS to measure HNO3 in the UTLS region is examined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".