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Record W2892948131 · doi:10.1029/2018gl079327

Strong Influence of Eddy Length on Boreal Summertime Extreme Precipitation Projections

2018· article· en· W2892948131 on OpenAlexafffundabout
Neil F. Tandon, Ji Nie, Xuebin Zhang

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsYork UniversityEnvironment and Climate Change Canada
FundersEnvironment and Climate Change Canada
KeywordsClimatologyPrecipitationEnvironmental scienceNorthern HemisphereAtmospheric sciencesEddy covarianceSouthern HemisphereBorealSubtropicsGeologyMeteorologyGeographyEcosystem

Abstract

fetched live from OpenAlex

Abstract Previous research has shown that projected changes in the horizontaleddy lengthof ascending anomalies likely drive subtropical changes in large‐scale ascent during extreme precipitation events (extreme ascent), which in turn strongly influence regional projections of extreme precipitation. Here we present evidence that this eddy length effect extends into the Northern Hemisphere extratropics during the summer season. This is shown by analyzing output from a large ensemble of the Canadian Earth System Model version 2 as well as models participating in the Coupled Model Intercomparison Project phase 5. As found previously, the changes in eddy length are associated with changes in aneffective stabilityquantity that combines dry and moist effects. It is shown that the change of extreme ascent associated with a projected change of eddy length agrees with expectations based on analysis of internal variability of extreme ascent and eddy length during the historical period.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.078
GPT teacher head0.344
Teacher spread0.266 · 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

Citations9
Published2018
Admission routes3
Has abstractyes

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