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Record W2030398713 · doi:10.1080/07055900.2000.9649660

An examination of the spring 1997 mid‐latitude east pacific sea surface temperature anomaly

2000· article· en· W2030398713 on OpenAlexvenueno aff
L-L. Fu

Bibliographic record

VenueATMOSPHERE-OCEAN · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsAnomaly (physics)Spring (device)LatitudeClimatologyGeologySea surface temperatureOceanographyGeodesyPhysics

Abstract

fetched live from OpenAlex

Abstract We seek to document and explain the lifecycle of the warm Sea Surface Temperature (SST) anomaly that intensified and weakened off the west coast of the United States to peak anomalies of 4°C during April‐June 1997. We use remotely sensed observational data and model analyses to compute an energy budget for the warm anomaly. The bulk of the anomalous warming was confined to the top 50 m of ocean and occurred during May. The immediate cause for the warming was twofold: latent heat fluxes decreased in magnitude as a result of both lower wind speeds and positive moisture anomalies, while the net radiative flux into the ocean increased as a result of lower than normal fractional cloud coverage. During June, the wind speed strengthened and became northerly, resulting in larger than normal latent and sensible heat fluxes that weakened the SST anomaly. Examination of the National Centers for Environmental Prediction (NCEP) 1000‐mb geopotential height for May shows that the Aleutian low extended far south of its usual position and was responsible for the weaker southerly winds and suppressed latent heat fluxes in the warm anomaly area. Finally, we note that the near simultaneous appearance of this warm anomaly in conjunction with warm El Niño waters off Peru makes El Niño an unlikely trigger for the northeast Pacific warm anomaly. We suggest a possible alternative scenario in which both events are remotely triggered by the intraseasonal oscillation.

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 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 score0.215
Threshold uncertainty score0.997

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)0.0040.000

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 head0.009
GPT teacher head0.204
Teacher spread0.196 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

Explore more

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