Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water Vapor Radiometer, GPS, and VLBI
Bibliographic record
Abstract
The accuracy of the Global Positioning System (GPS) as an instrument for measuring the integrated water vapor content of the atmosphere has been evaluated by comparison with concurrent observations made over a 14-day period by radiosonde, microwave water vapor radiometer (WVR), and Very Long Baseline Interferometry (VLBI).The Vaisala RS-80 A-HUMICAP radiosondes required a correction to the relative humidity readings (provided by Vaisala) to account for packaging contamination; the WVR data required a correction in order to be consistent with the wet refractivity formulation of the VLBI, GPS, and radiosondes.The best agreement of zenith wet delay (ZWD) among the collocated WVR, radiosondes, VLBI, and GPS was for minimum elevations of the GPS measurements below 10Њ.After corrections were applied to the WVR and radiosonde measurements, WVR, GPS, and VLBI (with 5Њ minimum elevation angle cutoff ) agreed within ϳ6 mm of ZWD [1 mm of precipitable water vapor (PWV)] when the differences were averaged, while the radiosondes averaged ϳ6 mm of ZWD lower than the WVR.After the removal of biases between the techniques, the VLBI and GPS scales differ by less than 3%, while the WVR scale was ϳ5% higher and the radiosonde scale was ϳ5% lower.Estimates of zenith wet delay by GPS receivers equipped with Dorne-Margolin choke ring antennas were found to have a strong dependence on the minimum elevation angle of the data.Elevation angle dependent phase errors for the GPS antenna/mount combination can produce ZWD errors of greater than 30 mm over a few hour interval for typical GPS satellite coverage.The VLBI measurements of ZWD are independent of minimum elevation angle and, based on known error sources, appear to be the most accurate of the four techniques.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".