Comparative experimental validation of microwave hyperspectral atmospheric soundings in clear-sky conditions
Bibliographic record
Abstract
Abstract. Accurate observations of atmospheric temperature and water vapor profiles are essential for weather forecasting and climate change detection. Hyperspectral radiance measurements afford a useful means to retrieve these thermodynamic variable fields by harnessing the rich information contained in the electromagnetic wave spectrum of the atmospheric radiation. In contrast to infrared radiometry, microwave radiometry can penetrate clouds, making it a valuable tool for all-sky thermodynamic retrievals. Recent advancements have led to the fabrication of a hyperspectral microwave radiometer: the High Spectral Resolution Airborne Microwave Sounder (HiSRAMS). This study utilizes HiSRAMS to retrieve atmospheric temperature and water vapor profiles under clear-sky conditions; this is an initial assessment of one of the first hyperspectral microwave radiometers, comparing the results to those from an infrared hyperspectrometer, the Atmospheric Emitted Radiance Interferometer (AERI). HiSRAMS and AERI measurements under different viewing geometries have been acquired and compared for atmospheric retrieval. When both instruments are placed on the ground to acquire zenith-pointing measurements, the infrared hyperspectral measurements exhibit higher information content and greater vertical resolution for temperature and water vapor retrievals than the microwave hyperspectral measurements. A synergistic fusion of HiSRAMS and AERI measurements from the air and ground is tested. This “sandwich” sounding of the atmosphere takes advantage of the complementary information contents of the two instruments and is found to notably improve retrieval accuracy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".