MétaCan
Menu
Back to cohort
Record W2496442738 · doi:10.1080/07055900.2016.1209156

Different Impacts of Typical and Atypical ENSO on the Indian Summer Rainfall: ENSO-Developing Phase

2016· article· en· W2496442738 on OpenAlexvenueno aff
Lei Zhang, Zhiwei Wu, Yefan Zhou

Bibliographic record

VenueATMOSPHERE-OCEAN · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsEl Niño Southern OscillationClimatologyLatitudeSouthern HemisphereMonsoonWalker circulationNorthern HemisphereAnomaly (physics)Environmental sciencePeninsulaGeographyGeologyPhysics

Abstract

fetched live from OpenAlex

The El Niño–Southern Oscillation (ENSO) is a main driving force of the northern hemisphere summer monsoon rainfall, including the Indian Summer Rainfall (ISR). The impacts of typical ENSO and atypical ENSO events on the ISR remain unclear during their developing summers. This study examines the different linkages between a typical ENSO and the ISR and between an a typical ENSO and the ISR. During the developing summer of a typical El Niño, negative rainfall anomalies are seen over the northeastern Indian subcontinent, while the anomalous rainfall pattern is almost the opposite for a typical La Niña; as for an atypical ENSO, the approximate “linear opposite” phenomenon vanishes. Furthermore, an anomalous global zonal wave train is found at mid-latitudes, with a local tripole circulation pattern over central–eastern Eurasia during the developing summer of a typical ENSO, which might explain the corresponding rainfall response over the Indian Peninsula. By contrast, such features are not obvious during the developing summer of an atypical ENSO. Among 106-year historical runs (1900–2005) of nine state-of-the-art models from the Coupled Model Intercomparison Project, Phase 5 (CMIP5), HadGEM2-ES exhibits promising skill in simulating the anomalous circulation pattern over mid-latitudes and central–eastern Eurasia. Probably, it is the model’s ability to capture the linkage between a typical ENSO and the ISR and the characteristics of a typical ENSO that makes the difference.

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 score0.058
Threshold uncertainty score0.999

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)0.0020.000

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 head0.024
GPT teacher head0.262
Teacher spread0.238 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueATMOSPHERE-OCEANSame topicClimate variability and modelsFrench-language works237,207