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Record W2138159159 · doi:10.1175/2007jas2509.1

On the Climate Impact of Surface Roughness Anomalies

2008· article· en· W2138159159 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsUniversity of Calgary
FundersCarnegie Mellon UniversityNational Science Foundation
KeywordsMagnitude (astronomy)ClimatologySurface roughnessAtmospheric sciencesSurface finishAtmosphere (unit)Roughness lengthAnomaly (physics)Climate modelEnvironmental scienceGeologyCloud coverScale (ratio)MeteorologyClimate changeWind speedMaterials scienceWind profile power lawPhysicsAstrophysicsCloud computing

Abstract

fetched live from OpenAlex

Abstract Large-scale deployment of wind power may alter climate through alteration of surface roughness. Previous research using GCMs has shown large-scale impacts of surface roughness perturbations but failed to elucidate the dynamic mechanisms that drove the observed responses in surface temperature. Using the NCAR Community Atmosphere Model in both its standard and aquaplanet forms, the authors have explored the impact of isolated surface roughness anomalies on the model climate. A consistent Rossby wave response in the mean winds to roughness anomalies across a range of model implementations is found. This response generates appreciable wind, temperature, and cloudiness anomalies. The interrelationship of these responses is discussed, and it is shown that the magnitude of the responses scales with the horizontal length scale of the roughened region, as well as with the magnitude of the roughness anomaly. These results are further elucidated through comparison with results of a series of shallow-water model experiments.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.268
Teacher spread0.235 · 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