Calibration and validation of water vapour lidar measurements from Eureka, Nunavut using radiosondes and the Atmospheric Chemistry Experiment fourier transform spectrometer
Bibliographic record
Abstract
Abstract. The Canadian Network for the Detection of Atmospheric Change and Environment Canada DIAL lidar located at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut has been upgraded to measure water vapour mixing ratio profiles at 150 m vertical resolution. The system is capable of measuring water vapour in the dry arctic atmosphere up to the tropopause region. Measurements were obtained in the February to March polar sunrise during 2007, 2008 and 2009 as part of the Canadian Arctic ACE Validation Campaign. Before such measurements can be used to address important questions in understanding dynamics and chemistry, the lidar measurements must be calibrated against an independent determination of water vapour. Here, radiosonde measurements of relative humidity have been used to calibrate the lidar measurements. It was found that the calibration varied significantly between each campaign. However, the calibration of the lidar during an individual polar sunrise campaign agrees with the local radiosonde measurements to better than 12% below 6 km altitude. To independently validate the calibration of the lidar derived from the radiosondes, comparisons are made between the calibrated lidar measurements and water vapour measurements from the Atmospheric Chemistry Experiment satellite-borne Fourier Transform Spectrometer. The comparisons between the lidar and satellite for both campaign averages and single overpasses show favourable agreement between the two instruments and help validate the comparison with the radiosondes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".