Measurements of Greenhouse Gases from Near-infrared Solar Absorption Spectra
Bibliographic record
Abstract
This thesis presents improvements to retrievals of greenhouse gas concentrations, with a focus on CO2 and the Arctic. Near-infrared solar absorption spectra were collected at the Polar Environment Research Laboratory (PEARL) in Eureka, Nunavut as part of the Total Carbon Column Observing Network (TCCON), extending the data record to July 2020. Data processing was improved by the application of solar zenith angle corrections to account for pointing offsets of the solar tracker. Issues related to surface pressure records were resolved. TCCON measurements were used to validate simulations of CO2 and CH4 by GEM-MACH-GHG, a model in development at Environment and Climate Change Canada. Vertical profile retrievals of CO2 from TCCON spectra were evaluated, using improved spectroscopy and line shapes. CO2 profiles were obtained from sequential retrievals in five spectral windows using synthetic and real spectra. A sensitivity study showed that the leading source of uncertainty in the retrieved CO2 profiles is errors in the a priori temperature profile as small as 2°C between 600-850 hPa. To distinguish the effect of errors in the instrument alignment and spectroscopic parameters from other error sources, CO2 profiles were retrieved using an a prioriprofile built from coincident in-situ measurements. With real spectra, the deviations in retrieved CO2 profiles were larger than typical vertical variations of CO2. Remaining errors in the forward iiimodel limit the accuracy of the retrieved profiles. Implementing a temperature retrieval or correction is critical to improve CO2 profile retrievals. A study was conducted in support of the proposed Canadian satellite mission AIM-North. The ReFRACtor algorithm was adapted to generate synthetic spectra for a Fourier transform spectrometer and a grating spectrometer. Retrievals were performed on these synthetic spectra to estimate the precision and accuracy of retrieved XCH4, XCO, and XCO2, in different conditions.Over a standard scene corresponding to a boreal forest, the retrieval precision for the given instrument characteristics was ~0.6% for XCH4, ~8% for XCO, and ~0.4% for XCO2. These results can be used by the AIM-North team to decide whether the instrument design should be adapted to meet the mission’s precision and accuracy goals and thresholds over specific scenes.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".