Mobile ground-based remote sensing of atmospheric CO2, CH4, and CO column densities above the Pacific Ocean
Bibliographic record
Abstract
Validation opportunities for model data and satellite observations in the short-wave infra-red spectral range are still sparse above the oceans. To provide such opportunities, we qualify a Fourier-transform spectrometer (FTS) for the regular use on ships. We use the EM27/SUN FTS [1] in direct-sunlight measurement geometry to retrieve total column densities of carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) [2] with solar absorption spectroscopy. Performing direct-sunlight measurements from a moving platform poses significant challenges to the solar tracking. We use a solar tracker that compensates the vessel's movements in real time, keeping the pointing of the instrument relative to the center of the sun better than 0.05° for more than 99 % of the time [3]. The solar tracker is part of a newly developed enclosure that allows automated measurements and withstands environmental factors such as rain, humidity, and sea spray. The instrument was deployed on board the German research vessel RV Sonne during the MORE-2 (Measuring Oceanic REferences 2) campaign on a longitudinal transect from Vancouver (Canada) to Singapore in June 2019. During the campaign we recorded 33800 direct sunlight spectra from which column-averaged dry-air mole fractions of CO2, CH4, and CO are retrieved. Our results are calibrated against World Meteorological Organization standards and the columns achieve a relative precision of 0.06 %, 0.06 %, and 1.02 % for CO2, CH4, and CO, respectively. We compare our records to coincident observations of the Greenhouse gases Observing SATellite (GOSAT), the Orbiting Carbon Observatory-2 (OCO-2), and the TROPOspheric Monitoring Instrument (TROPOMI). Our CO2 records show a mean offset of -3.2 ± 1.1 ppm to OCO-2 and -1.4 ± 1.7 ppm to GOSAT observations. Furthermore, we find a mean CH4 offset of 17 ± 6 ppb to GOSAT and a mean CO offset of 3.5 ± 2.6 ppb to TROPOMI. The Copernicus Atmosphere Monitoring Service (CAMS) provided us with model data of CH4 and CO. We could show that the CO data agree well with our measurements, showing an offset of 3.5 ± 3.6 ppb. [1] Gisi, M. et al.: XCO2-measurements with a tabletop FTS using solar absorption spectroscopy, Atmos. Meas. Tech., 5, 2969-2980, 2012 [2] Hase, F. et al.: Addition of a channel for XCO observations to a portable FTIR spectrometer for greenhouse gas measurements, Atmos. Meas. Tech., 9, 2303-2313, 2016 [3] Klappenbach, F. et al.: Accurate mobile remote sensing of XCO2 and XCH4 latitudinal transects from aboard a research vessel, Atmos. Meas. Tech., 8, 5023–5038, 2015
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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 | 0.001 | 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) | 0.003 | 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".