Validation of upper mesospheric and lower thermospheric temperatures measured by the Solar Occultation for Ice Experiment
Bibliographic record
Abstract
Temperature observations in the polar mesosphere and lower thermosphere are critical for studies of polar mesospheric cloud (PMC) formation and variability. The Solar Occultation for Ice Experiment (SOFIE) on NASA's Aeronomy of Ice in the Mesosphere (AIM) satellite has been measuring temperatures in the polar atmosphere nearly continuously since 2007. We herein present an improved SOFIE temperature data set and validate it against a variety of satellite and ground‐based observations. We find that when taking all comparisons together, SOFIE temperatures are in agreement with independent observations to within reported systematic uncertainties from 15 to 88 km altitude. Between 88 and 95 km SOFIE temperatures have a warm bias that peaks between 10 and 15 K in the Arctic summer and 20–30 K in the Antarctic summer. Much of the warm bias is likely related to uncertainties in prescribed atomic oxygen densities that are required for the SOFIE temperature retrieval.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".