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Record W2765131410 · doi:10.1175/jcli-d-17-0202.1

On How the Middle Atmospheric Residual Circulation Responds to the Solar Cycle Close to the Solstices

2017· article· en· W2765131410 on OpenAlexaboutno aff
Bodil Karlsson, Maartje Kuilman

Bibliographic record

VenueJournal of Climate · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersVetenskapsrådet
KeywordsSolsticeAtmospheric sciencesAtmosphere (unit)StratosphereShortwaveMesosphereEnvironmental scienceSolar cycleNorthern HemispherePolar nightClimatologyFlux (metallurgy)Atmospheric circulationSolar maximumSolar irradiancePhysicsMeteorologyGeologyAstronomyRadiative transferLatitudeChemistry

Abstract

fetched live from OpenAlex

Abstract During high solar activity, the atmosphere receives more energy from the sun, particularly in the form of shortwave radiation. Most notable is the effect in the middle and upper atmosphere, which in general shows a positive temperature response due to physical and chemical processes that are intensified at high solar activity. It is thus surprising that a clear solar cycle signal is absent in the summer polar mesosphere region in spite of it being illuminated around the clock. In this study, it is investigated how the circulation in the summer mesosphere is affected by changes in the solar flux using a 30-yr run from the nudged version of the Canadian Middle Atmosphere Model (CMAM30). It is found that—in July—the solar cycle signal from direct solar heating is counteracted by an enhanced residual circulation, which adiabatically cools the region at a higher rate when the solar activity is above average. The dynamical cooling is partly initiated in the Southern Hemisphere winter stratosphere.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.028
GPT teacher head0.255
Teacher spread0.227 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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