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Record W4288758690 · doi:10.5194/amt-15-4339-2022

Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products

2022· article· en· W4288758690 on OpenAlexafffund
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, A. Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crévoisier, Jérôme Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen M. Roehl, P. O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David Griffith, Voltaire A. Velazco, David F. Pollard

Bibliographic record

VenueAtmospheric measurement techniques · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaEurostarsHorizon 2020 Framework ProgrammeUniversité de Versailles Saint-Quentin-en-YvelinesEnvironment and Climate Change CanadaMinistry of Business, Innovation and EmploymentDeutsche ForschungsgemeinschaftNational Science FoundationEuropean Space AgencyNational Aeronautics and Space AdministrationMinisterium für Wissenschaft, Forschung und Kunst Baden-WürttembergStrongInstituto Tecnológico y de Energías RenovablesCentre National d’Etudes SpatialesBundesministerium für Wirtschaft und EnergieSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungKarlsruhe Institute of TechnologyBundesministerium für Bildung und ForschungMinisterio de Economía y Competitividad
KeywordsTroposphereTrace gasRemote sensingEnvironmental scienceSpectroradiometerColumn (typography)MethaneMeteorologyChemistryComputer sciencePhysicsOpticsGeology

Abstract

fetched live from OpenAlex

Abstract. The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near-infrared and/or shortwave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument), offer higher sensitivity near the ground and are used for the retrieval of total-column-averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total-column level 2 retrieval products. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach has strong theoretical similarities to applying the spectra of the different sensors together in a single retrieval procedure but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total-column-averaged CH4 product (XCH4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the high-quality upper troposphere–lower stratosphere (UTLS) CH4 partial-column information of the corresponding IASI product. As a consequence, the combined product offers additional sensitivity for the tropospheric CH4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effect is verified by comparisons to CH4 reference data obtained from collocated XCH4 measurements at 14 globally distributed TCCON (Total Carbon Column Observing Network) stations, CH4 profile measurements made by 36 individual AirCore soundings, and tropospheric CH4 data derived from continuous ground-based in situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect the actual variations of atmospheric XCH4, CH4 in the UTLS, and CH4 in the troposphere. A similar good reliability for the latter is not achievable by the individual TROPOMI and IASI products.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.035
GPT teacher head0.212
Teacher spread0.177 · 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 teacher head, not a consensus.

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

Citations27
Published2022
Admission routes2
Has abstractyes

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