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Record W2072940160 · doi:10.1029/2004jd004892

Model thermal response to minor radiative energy sources and sinks in the middle atmosphere

2004· article· en· W2072940160 on OpenAlexafffundabout
V. I. Fomichev, Chao Fu, J. de Grandpré, S. R. Beagley, V. P. Ogibalov, J. C. McConnell

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsMcGill UniversityYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyCanadian Foundation for Climate and Atmospheric Sciences
KeywordsAtmosphere (unit)Atmospheric sciencesRadiative transferThermalForcing (mathematics)SphericityEnergy balanceAtmospheric modelRadiative forcingEnvironmental sciencePhysicsMeteorologyThermodynamicsOpticsAerosol

Abstract

fetched live from OpenAlex

This paper presents the thermal response of the Canadian middle atmosphere model (CMAM) to minor radiative energy sources and sinks. These include chemical heating, infrared (IR) H 2 O cooling, sphericity effect in solar heating, and solar heating in the near‐IR CO 2 bands. All of these energy sources/sinks can be considered as minor ones either in terms of their magnitude or in terms of the limited height region where they are of importance or both. To examine the thermal response of the middle atmosphere, a version of the CMAM with an interactive gas phase chemistry scheme has been used in a series of multiyear experiments for conditions of perpetual July. Each of the analyzed mechanisms may provide a noticeable contribution into the model energy balance that results in a statistically significant model response. Various forcing terms due to minor energy sources/sinks have different spatial and temporal distributions. Their magnitudes vary from tenths K d −1 for the sphericity effect up to ∼10 K d −1 for chemical heating that provides corresponding thermal responses of a few to about 20 K in the middle atmosphere. The model thermal response depends on the magnitude of the applied forcing but is not always local and can be spread beyond the regions where the forcing terms are initially applied. On a globally averaged basis the local strength of the model response is nearly proportional to the magnitude of the small forcing terms but shows nonlinearity when forcing due to chemical heating exceeds ∼1 K d −1 in the mesosphere. Accounting for the combined effects of the minor energy sources and sinks leads to a better agreement between the model temperature field and observations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.284
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations30
Published2004
Admission routes3
Has abstractyes

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