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Record W1980825762 · doi:10.1080/07055900.2012.668851

Influence des flux de chaleur latente et sensible à l'interface air‐mer en Méditerranée sur la pluviométrie et la température dans le nord de l'Algérie

2012· article· fr· W1980825762 on OpenAlexvenueno aff
Lamri Nacef, Nour El Islam Bachari

Bibliographic record

VenueATMOSPHERE-OCEAN · 2012
Typearticle
Languagefr
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesForestryGeographyPhysicsArt

Abstract

fetched live from OpenAlex

RÉSUMÉ Comme objectif principal de ce travail, nous avons étudié les rapports statistiques de causalité entre les flux de chaleur latente et sensible à l'interface air-mer en Méditerranée et la variabilité pluviométrique et thermique dans le nord de l'Algérie. En plus, les relations significatives ont été quantifiées. L'introduction de la notion de causalité au sens de Granger nous a permis d'examiner l'influence des anomalies saisonnières de ces flux sur les anomalies saisonnières de précipitation et de température dans le nord de l'Algérie et donc de sélectionner les régions méditerranéennes ayant le maximum d'influence sur le climat de notre région. Les résultats montrent que les anomalies des flux dans ces surfaces sélectionnées peuvent réduire la variance inexpliquée de la pluviométrie de 19 % à 36 % et celle de la température, de 12 % à 41 %. Ils montrent également que la réponse des anomalies pluviométriques et thermiques aux anomalies des flux de chaleur latente et/ou sensible varie selon les régions et les saisons. La persistance de ces liens dépasse rarement deux saisons. En appliquant la technique de l'analyse en composites, les anomalies saisonnières des flux de chaleur latente et/ou sensible dans les régions méditerranéennes sélectionnées sont utilisées comme prédicteurs dans l'élaboration des prévisions probabilistes saisonnières des précipitations et des températures pour chacune des régions du nord de l'Algérie. L'évaluation de la qualité des prévisions montre que la prévision probabiliste basée sur l'analyse en composites des flux de chaleur latente et/ou sensible à l'interface air-mer en Méditerranée est meilleure que la prévision par la climatologie (par le hasard) et améliore de 11 % à 14 % la prévision saisonnière pour notre région. [Translated by the editor] The principal goal of this study was to examine statistical causality relationships between latent and sensible heat fluxes at the Mediterranean air-sea interface and rainfall and temperature variability in northern Algeria. In addition, significant relationships were quantified. The introduction of the concept of Granger causality allowed us to examine the influence of seasonal anomalies of these fluxes on seasonal precipitation and temperature anomalies in northern Algeria and to select Mediterranean regions that have a maximum influence on our region's climate. Results show that flux anomalies in these selected regions can reduce unexplained variance in rainfall by 19 to 36% and in temperatures, by 12 to 41%. They also show that the response of rainfall and temperature anomalies to latent and/or sensible heat flux anomalies varies according to region and season. These relationships rarely persist beyond two seasons. By applying the technique of composite analysis, seasonal anomalies of latent and/or sensible heat fluxes in the selected Mediterranean regions are used as predictors to develop seasonal probability forecasts for precipitation and temperature for each of the regions in northern Algeria. A forecast quality evaluation revealed that probability forecasting based on a composite analysis of latent and/or sensible heat fluxes at the Mediterranean air-sea interface provides better results than forecasting based on climatology (chance) and improves seasonal forecasting by 11 to 14% for our region.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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