Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign
Bibliographic record
Abstract
Abstract. Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a well-established ground-based measurement technique for the detection of aerosols and trace gases particularly in the boundary layer and the lower troposphere: ultraviolet- and visible radiation spectra of skylight are analysed to obtain information on different atmospheric parameters, integrated over the light path from space to the instrument. An appropriate set of spectra recorded under different viewing geometries ("Multi-Axis") allows retrieval of tropospheric aerosol and trace gas vertical distributions by applying numerical inversion methods. The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (The Netherlands) in September 2016 with the aim of assessing the consistency of MAX-DOAS measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, Long-Path DOAS, sun photometer and others). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations. The profiles were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions, however sometimes at different altitudes and of different intensity. Under clear sky conditions, the root-mean-square differences of aerosol optical thicknesses, trace gas (NO2, HCHO) vertical columns and surface concentrations among the results of individual participants vary between 0.01–0.1, (1.5–15) x 1014 molec cm-2 and (0.3–8) x 1010 molec cm-3, respectively. For the comparison against supporting observations, these values increase to 0.02–0.2, (11–55) x 1014 molec cm-2 and (0.8–9) x 1010 molec cm-3. It is likely that a large part of this increase is caused by imperfect spatio-temporal overlap of the different observations. In contrast to what is often assumed, the MAX-DOAS vertically integrated extinction profiles and the sun photometer total aerosol optical thickness were found to not necessarily being comparable quantities, unless information on the real aerosol vertical distribution is available to account for the low sensitivity of MAX-DOAS observations at higher altitudes.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".