New insights from the Jülich Ozone Sonde Intercomparison Experiment: calibration functions traceable to one ozone reference instrument
Bibliographic record
Abstract
Abstract. Although in principle ECC (electrochemical concentration cell) ozonesondes are absolute measuring devices, in practice they have several “artefacts” which change over the course of a flight. Most of the artefacts have been corrected in the recommendations of the Assessment of Standard Operating Procedures for Ozone Sondes (ASOPOS) report (Smit et al., 2021), giving an overall uncertainty of 5 %–10 % throughout the profile. However, the conversion of the measured cell current into the sampled ozone concentration still needs to be quantified better, using time-varying background current and more appropriate pump efficiencies. We describe an updated methodology for ECC sonde data processing that is based on the Jülich Ozone Sonde Intercomparison Experiment (JOSIE) 2009/2010 and JOSIE Southern Hemisphere Additional Ozonesondes (JOSIE-SHADOZ) 2017 test chamber data. The methodology resolves the slow and fast time responses of the ECC ozonesonde and in addition applies calibration functions to make the sonde data traceable to the JOSIE ozone reference UV photometer (OPM). The stoichiometry (O3/I2) factors and their uncertainties along with fast and slow reaction pathways for the different sensing solution types used in the global ozonesonde network are determined. Experimental evidence is given for treating the background current of the ECC sensor as the superposition of a constant ozone-independent component (IB0, measured before ozone exposure in the sonde preparation protocol) and a slow time-variant ozone-dependent current determined from the initial measured ozone current using a first-order numerical convolution. The fast sensor current is refined using the time response determined in sonde preparation with a first-order deconvolution scheme. Practical procedures for initializing the numerical deconvolution and convolution schemes to determine the slow and fast ECC currents are given. Calibration functions for specific ozonesondes and sensing solution type combinations were determined by comparing JOSIE 2009/2010 and JOSIE-SHADOZ 2017 profiles with the JOSIE OPM. With fast and slow currents resolved and the new calibration functions, a full uncertainty budget is obtained. The time response correction methodology makes every ozonesonde record traceable to one standard, i.e. the OPM of JOSIE, enabling the goal of a 5 % relative uncertainty to be met throughout the global ozone network.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".