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Record W7073931511

An evaluation of IASI-NH3 with ground-based Fourier transform infrared spectroscopy measurements:

2016· article· en· W7073931511 on OpenAlexfundno aff

Bibliographic record

VenueTNO Repository · 2016
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
FundersDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche ScientifiqueUniversity of TorontoConsejo Nacional de Ciencia y TecnologíaNederlandse Organisatie voor Wetenschappelijk OnderzoekBelgian Federal Science Policy OfficeJet Propulsion LaboratoryUniversité de La RéunionCentre National d’Etudes SpatialesFonds De La Recherche Scientifique - FNRSMinistry of Business, Innovation and EmploymentCanadian Space AgencyUniversity of WollongongNew Zealand GovernmentNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyNational Science Foundation
KeywordsSatelliteTerrainInfraredFourier transformInterferometryAtmospheric correctionFourier transform spectroscopyDepth soundingSpatial distribution
DOInot available

Abstract

fetched live from OpenAlex

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground-based instruments. Due to their large spatial coverage and (bi-)daily overpasses, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface measurements without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier transform infrared spectroscopy (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008 and 2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs Combining double low line 547) give a mean relative difference of g'32.4g€±g€(56.3)g€%, a correlation r of 0.8 with a slope of 0.73. These results give an improved estimate of the IASI-NH3 product performance compared to the previous upper-bound estimates (-50 to +100%). © Author(s) 2016.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.298
Teacher spread0.259 · 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
Published2016
Admission routes1
Has abstractyes

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