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Record W4281740959 · doi:10.1007/s00382-022-06307-z

Climate change impacts on linkages between atmospheric blocking and North American winter cold spells in CanESM2 and CanESM5

2022· article· en· W4281740959 on OpenAlexaffabout
Dae Il Jeong, Bin Yu, Alex J. Cannon

Bibliographic record

VenueClimate Dynamics · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsClimatologyEnvironmental scienceBaseline (sea)Blocking (statistics)Cold weatherAtmospheric sciencesSpellAdvectionClimate changeGeologyOceanographyPhysicsMathematics

Abstract

fetched live from OpenAlex

Abstract This study investigates changes in linkages between atmospheric blocking and winter (December–February) cold spells over the Pacific-North America region in two large-ensembles of Canadian Earth System Models (CanESM2 and CanESM5 under high-emission scenarios). The two ensembles show decreases in winter blocking frequency over the North Pacific from 1981–2010 baseline to 2071–2100, with larger decreases in CanESM5 (− 3.08%/decade) than CanESM2 (− 1.73%/decade). Using a time-invariant (stationary) threshold estimated from the baseline to define cold days, the two ensembles project a decline in cold spell events as future air temperature increases; the occasional occurrence of cold spell events is still projected to occur at the end of the century. Using a time-dependent (nonstationary) climatological threshold, CanESM2 and CanESM5 ensembles project modest decreases in cold spell days over North America (− 2.0 and − 2.3%/decade). With the nonstationary threshold, the two ensembles project decreases in winter cold spell frequency during blocking, with larger decreases in CanESM5 (13%) than CanESM2 (3%) for 2071–2100 period compared to the baseline. The two ensembles display similar blocking-cold spell linkages between the baseline and future periods; however, the linkage is weaker and exhibits larger uncertainty in the future. Moreover, temperature advection and net heat flux anomalies during blocking are generally weaker for the future period, resulting in weaker impacts on North American cold spells with larger uncertainty associated with increases in internal-variability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.017
GPT teacher head0.236
Teacher spread0.218 · 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.

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

Citations7
Published2022
Admission routes2
Has abstractyes

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