Calibration of Sun Radiometer–Based Atmospheric Water Vapor Retrievals Using GPS Meteorology
Bibliographic record
Abstract
A study of the validation and calibration process for integrated water vapor (IWV) measurements derived from sun radiometry at the 940-nm solar absorption channel employed in the Aerosol Robotic Network (AERONET) Aerosol Canada (AEROCAN) is presented. The sun radiometer data are compared with GPS meteorology records used as a reference. Three Canadian sites from different climatic regimes covering the period 2000–04 are considered. The observations from five different sun radiometers (IWV-SUN) were processed using the initial AERONET IWV retrieval procedure (V1) whereas GPS-derived IWV (IWV-GPS) was retrieved using “GPSpace” software developed by the Geodetic Survey division of Natural Resources Canada. A sensitivity study is carried out to highlight the influence of both central wavelength and signal amplitude on the 940-nm filter characteristics, which are instrument dependent and can drift due to aging. The comparison between IWV-SUN (V1) and IWV-GPS shows an average rmse of 0.23 ± 0.11 g cm −2 (22%) and a mean bias of −0.09 ± 0.16 g cm −2 (9%). Furthermore, it is shown that the use of GPS for determining the 940-nm channel calibration constants for the solar radiometers improves IWV retrievals (rmse reduced by about 35% and bias by a factor of 3–10) without any knowledge of the 940-nm filter characteristics. These results are discussed within the context of the new AERONET IWV processing procedure (V2), which accounts for solar 940-nm region filter characteristics. The GPS receiver technique appears to be a powerful calibration tool because of its continuous observation capability, its robustness, and its operational simplicity.
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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) | 0.001 | 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".