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Independent a priori information for reduced intercomparison errors between TROPOMI and TCCON retrievals of methane and carbon monoxide

2020· article· en· W3042508783 on OpenAlexaff
Johannes Lutzmann, Ralf Sussmann, Huilin Chen, Frank Hase, Rigel Kivi, Kimberly Strong, Aki Tsurata, Thorsten Warneke

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnvironmental scienceTroposphereSatelliteTrace gasData assimilationStratosphereSCIAMACHYAtmospheric chemistryAtmospheric sciencesMeteorologyRemote sensingOzonePhysicsGeology

Abstract

fetched live from OpenAlex

Ground-based column measurements of trace gases by FTIR spectrometers within the Total Carbon Column Observing Network (TCCON) provide accurate ground reference for the validation of the nadir-viewing hyperspectral Tropospheric Monitoring Instrument (TROPOMI) on-board the ESA satellite Sentinel 5 Precursor (S-5P). In such intercomparisons of two independent remote soundings, errors can occur as the a priori profiles used in the respective retrievals are i) differing from each other, and ii) both different from the true atmospheric state at the moment of observation. In certain conditions of atmospheric dynamics, e.g. polar vortex subsidence or stratospheric intrusions, which strongly alter the shape of vertical concentration profiles, these intercomparison errors can become considerable (Ostler et al., 2014). In our work funded by the German Space Agency DLR and performed as part of the ESA AO project TCCON4S5P, we search for potential sources of realistic common a priori profiles for S-5P and TCCON CH4 and CO measurements which reduce these large errors. We examine the performance of a number of chemical transport models and data assimilation systems in reproducing dynamical effects and in minimizing intercomparison errors. In-situ profiles measured by AirCores are used as validation where they are available. We present the status and results of our ongoing work. Reference: Ostler, A., Sussmann, R., Rettinger, M., Deutscher, N. M., Dohe, S., Hase, F., Jones, N., Palm, M., and Sinnhuber, B.-M.: Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability, Atmos. Meas. Tech., 7, 4081–4101, doi:10.5194/amt-7-4081-2014, 2014. Ostler, A., Sussmann, R., Rettinger, M., Deutscher, N. M., Dohe, S., Hase, F., Jones, N., Palm, M., and Sinnhuber, B.-M.: Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability, Atmos. Meas. Tech., 7, 4081–4101, doi:10.5194/amt-7-4081-2014, 2014.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.229
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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