A fully autonomous ozone, aerosol and nighttime water vapor lidar: a synergistic approach to profiling the atmosphere in the Canadian oil sands region
Bibliographic record
Abstract
Abstract. Lidar technology has been rapidly advancing over the past several decades. It can be used to measure a variety of atmospheric constituents at very high temporal and spatial resolutions. While the number of lidars continues to increase worldwide, there is generally a dependency on an operator, particularly for high-powered lidar systems. Environment and Climate Change Canada (ECCC) has recently developed a fully autonomous, mobile lidar system called AMOLITE (Autonomous Mobile Ozone Lidar Instrument for Tropospheric Experiments) to simultaneously measure the vertical profile of tropospheric ozone, aerosol and water vapor (nighttime only) from near the ground to altitudes reaching 10 to 15 km. This current system uses a dual-laser, dual-lidar design housed in a single climate-controlled trailer. Ozone profiles are measured by the differential absorption lidar (DIAL) technique using a single 1 m Raman cell filled with CO2. The DIAL wavelengths of 287 and 299 nm are generated as the second and third Stokes lines resulting from stimulated Raman scattering of the cell pumped using the fourth harmonic of a Nd:YAG laser (266 nm). The aerosol lidar transmits three wavelengths simultaneously (355, 532 and 1064 nm) employing a detector designed to measure the three backscatter channels, two nitrogen Raman channels (387 and 607 nm) and one cross-polarization channel at 355 nm. In addition, we added a water vapor channel arising from the Raman-shifted 355 nm output (407 nm) to provide nighttime water vapor profiles. AMOLITE participated in a validation experiment alongside four other ozone DIAL systems before being deployed to the ECCC Oski-ôtin ground site in the Alberta oil sands region in November 2016. Ozone was found to increase throughout the troposphere by as much as a factor of 2 from stratospheric intrusions. The dry stratospheric air within the intrusion was measured to be less than 0.2 g kg−1. A biomass burning event that impacted the region over an 8-day period produced lidar ratios of 35 to 65 sr at 355 nm and 40 to 100 sr at 532. Over the same period the Ångström exponent decreased from 1.56±0.2 to 1.35±0.2 in the 2–4 km smoke region.
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 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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".