MétaCan
Menu
Back to cohort
Record W1963980632 · doi:10.1002/joc.1395

Lagged relationships between North American snow mass and atmospheric teleconnection indices

2006· article· en· W1963980632 on OpenAlexaboutno aff
Stefan Sobolowski, Allan Frei

Bibliographic record

VenueInternational Journal of Climatology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationNorthwestern University
KeywordsTeleconnectionClimatologyNorth Atlantic oscillationSnowPacific decadal oscillationEl Niño Southern OscillationEnvironmental sciencePrincipal component analysisSpatial ecologyGeographyPhysical geographyGeologyMeteorology

Abstract

fetched live from OpenAlex

Abstract Relationships between North American winter (January, February, March or JFM) snow mass, or snow water equivalent (SWE), between 1980 and 1997, and four teleconnection indices are explored at different spatial and temporal scales, with teleconnection indices leading SWE by one to two seasons. Summer (July, August, September, or JAS) and fall (October, November, December, or OND) Pacific North American pattern (PNA), North Atlantic Oscillation (NAO), El‐Nino Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) are included in this analysis. Principal components analysis of the SWE data set results in four components, explaining over 56% of the variance in the SWE signal which have significant relationships to ENSO, PDO, and NAO. Strong spatial components associated with these relationships emerge, with the first component (NAO, ENSO) located in the northcentral to northwestern regions of the United States and the southcentral to southwestern regions of Canada. A third component (PDO) stretches from the midwest to the east coast of the United States, New England, and the Atlantic Provinces. Ranked correlation analyses using the SWE data set, and additional analyses of station observations in order to extend the time domain, corroborate and elucidate the PCA results. Examinations of these relationships at different spatial scales, and over varying time domains, indicate that there may be some scale‐dependant predictive ability for North American snow mass. Copyright © 2006 Royal Meteorological Society.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.306

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 science0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations39
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of ClimatologySame topicClimate variability and modelsFrench-language works237,207