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Record W2079261398 · doi:10.1029/2006gl026549

The tropopause inversion layer in models and analyses

2006· article· en· W2079261398 on OpenAlexafffundabout
Thomas Birner, David Sankey, T. G. Shepherd

Bibliographic record

VenueGeophysical Research Letters · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyNational Oceanic and Atmospheric AdministrationScheme for Promotion of Academic and Research CollaborationCanadian Foundation for Climate and Atmospheric Sciences
KeywordsTropopauseRadiosondeClimatologyGCM transcription factorsGeneral Circulation ModelAtmospheric sciencesData assimilationInversion (geology)Atmospheric modelEnvironmental scienceStratification (seeds)GeologyMeteorologyStratosphereClimate changeGeography

Abstract

fetched live from OpenAlex

Recent high‐resolution radiosonde climatologies have revealed a tropopause inversion layer (TIL) in the extratropics: temperature strongly increases just above a sharp local cold point tropopause. Here, it is asked to what extent a TIL exists in current general circulation models (GCMs) and meteorological analyses. Only a weak hint of a TIL exists in NCEP/NCAR reanalysis data. In contrast, the Canadian Middle Atmosphere Model (CMAM), a comprehensive GCM, exhibits a TIL of realistic strength. However, in data assimilation mode CMAM exhibits a much weaker TIL, especially in the Southern Hemisphere where only coarse satellite data are available. The discrepancy between the analyses and the GCM is thus hypothesized to be mainly due to data assimilation acting to smooth the observed strong curvature in temperature around the tropopause. This is confirmed in the reanalysis where the stratification around the tropopause exhibits a strong discontinuity at the start of the satellite era.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.074
GPT teacher head0.329
Teacher spread0.254 · 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 designSimulation or modeling
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

Citations99
Published2006
Admission routes3
Has abstractyes

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