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Record W3210741339

An Explanation for the Nitrous Oxide Layer Observed in the Mesopause Region

2018· article· en· W3210741339 on OpenAlexaff
CW Kelly, M. Chipperfield, J. Plane, Wuhu Feng, PE Sheese, KA Walker, C. D. Boone

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsMesopauseThermosphereAtmospheric sciencesAirglowMesosphereEnvironmental scienceAtmosphere (unit)AeronomyAtmospheric chemistryPrecipitationNitrous oxideIonosphereClimatologyOzonePhysicsChemistryMeteorologyStratosphereAstronomyGeology
DOInot available

Abstract

fetched live from OpenAlex

Recent satellite measurements of a layer of enhanced nitrous oxide (N₂O) in the mesosphere-lower thermosphere (MLT) from the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer have suggested an unexpected, minor high-altitude production source. Here we report the development of a mechanism and the first model simulations, which can explain the formation of this MLT N₂O layer. N₂O production occurs primarily via a reaction route involving the excitation of N₂ from secondary electrons. Simulations using the Whole Atmosphere Community Climate Model, with external forcing from the Global Airglow model, quantitatively reproduce the observed vertical, latitudinal, and seasonal N₂O variations. Sensitivity results indicate that photoelectrons are far more important than previously predicted, causing approximately two thirds of global N₂O production in the MLT. Energetic electron precipitation over high latitudes provides the remaining contribution. Solar cycle analysis reveals N₂O enhancements of up to ×2 at solar maximum compared to solar minimum.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.098
GPT teacher head0.271
Teacher spread0.174 · 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 designTheoretical or conceptual
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
Published2018
Admission routes1
Has abstractyes

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