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Record W1907759116 · doi:10.1002/2014jd021677

Land‐atmosphere coupling over North America in CRCM5

2014· article· en· W1907759116 on OpenAlexaffabout
G. T. Diro, Laxmi Sushama, Andrey Martynov, Dae Il Jeong, Diana Verseghy, Katja Winger

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change CanadaUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsAtmosphere (unit)PrecipitationEnvironmental scienceMoistureCoupling (piping)Atmospheric sciencesClimatologyWater contentPeriod (music)GeologyMeteorologyGeographyMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Abstract Land‐atmosphere coupling and its impact on extreme precipitation and temperature events over North America are studied using the fifth generation of the Canadian Regional Climate Model (CRCM5). To this effect, two 30 year long simulations, spanning the 1981–2010 period, with and without land‐atmosphere coupling, have been performed with CRCM5, driven by the European Centre for Medium‐Range Weather Forecasts reanalysis at the boundaries. In the coupled simulation, the soil moisture interacts freely with the atmosphere at each time step, while in the uncoupled simulation, soil moisture is replaced with its climatological value computed from the coupled simulation, thus suppressing the soil moisture‐atmosphere interactions. Analyses of the coupled and uncoupled simulations, for the summer period, show strong soil moisture‐temperature coupling over the Great Plains, consistent with previous studies. The maxima of soil moisture‐precipitation coupling is more spread out and covers the semiarid regions of the western U.S. and parts of the Great Plains. However, the strength of soil moisture‐precipitation coupling is found to be generally weaker than that of soil moisture‐temperature coupling. The study clearly indicates that land‐atmosphere coupling increases the interannual variability of the seasonal mean daily maximum temperature in the Great Plains. Land‐atmosphere coupling is found to significantly modulate selected temperature extremes such as the number of hot days, frequency, and maximum duration of hot spells over the Great Plains. Results also suggest additional hot spots, where soil moisture modulates extreme events. These hot spots are located in the southeast U.S. for the hot days/hot spells and in the semiarid regions of the western U.S. for extreme wet spells. This study thus demonstrates that climatologically wet/dry regions can become hot spots of land‐atmosphere coupling when the soil moisture decreases/increases to an intermediate transitional level where evapotranspiration becomes moisture sensitive and large enough to affect the climate.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.517

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.311
Teacher spread0.283 · 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

Citations45
Published2014
Admission routes2
Has abstractyes

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