Assessment of the Global Climatic Impacts due to El Nino and La Nina Events
Notice bibliographique
Résumé
The El Niño-Southern Oscillation (ENSO), a naturally occurring coupled ocean-atmosphere phenomenon centered in the tropical Pacific Ocean, constitutes a primary driver of interannual climate variability on a global scale. Characterized by its warm (El Niño) and cool (La Niña) phases, ENSO involves significant anomalies in sea surface temperatures (SSTs) and a concomitant disruption of the Pacific trade wind system, which ordinarily governs oceanic upwelling and global atmospheric circulation. This cutting-edge research synthesizes a comprehensive body of existing knowledge, derived from an exhaustive literature review across prominent academic and research repositories, to delineate the complex interplay between El Nino and La Nina and their far-reaching impacts on worldwide weather regimes and climate patterns. The study elucidates the mechanisms through which ENSO-induced perturbations in oceanic upwelling and the resultant SST anomalies act as critical instigators of global extreme weather events. The analysis shows that a significant reorganization of tropical convective patterns occurs during El Nino occurrences due to the unusual eastward displacement of warm oceanic waters. In the central and eastern equatorial Pacific and along the western coast of South America, this eastward shift increases precipitation, which frequently results in episodes of catastrophic floods and coastal erosion. On the other hand, in the western Pacific, which includes places like Australia and Indonesia, it suppresses rainfall, which frequently leads to severe and protracted drought conditions, water scarcity, and increased wildfire hazards. Moreover, the course and intensity of upper-level jet streams are altered by these ENSO-driven changes in atmospheric circulation patterns. In the Northern Hemisphere winter, El Nino conditions are associated with the development of the Pacific North American (PNA) teleconnection pattern, which typically manifests as milder winter temperatures across western North America and Canada, while the southeastern United States experiences increased rainfall and cooler temperatures. The study also highlights the observed attenuation of the Indian monsoon rainfall during El Nino events, underscoring the extensive reach of ENSO's atmospheric teleconnections. Conversely, the La Niña phase, characterized by anomalously cool SSTs in the central and eastern equatorial Pacific, generally intensifies the Walker circulation. In Australia and Southeast Asia, this intensification frequently results in increased monsoonal rainfall, raising the risk of flooding. At the same time, La Nina's influence frequently causes extended periods of dryness and drought-like conditions in places like Peru and Ecuador along the western coast of South America. While the Pacific Northwest and western Canada typically experience harsher and stormier winter conditions, the Southern United States frequently experiences winter droughts during La Nina episodes. Notably, because of less vertical wind shear in the tropical Atlantic basin, La Nina is often linked to more active Atlantic hurricane seasons. This research emphasizes that both El Nino and La Nina serve as significant amplifiers of natural climate variability, increasing the frequency and intensity of extreme weather events globally. In certain places, El Nino can make heat waves and heavy rains worse, but in other places, it can make droughts and wildfires more likely. More active Atlantic hurricane seasons and a higher danger of flooding in Australia and Southeast Asia are associated with La Nina. Developing successful adaptation and mitigation strategies to counteract ENSO's detrimental global climatic effects requires an understanding of the complex dynamics of ENSO, including its teleconnections and impacts on temperature, precipitation, and storm activity, especially in the context of long-term anthropogenic climate change. Clarifying the intricate relationship between ENSO and climate change, enhancing the accuracy and lead time of ENSO forecasts by integrating observational data and improved climate models, and examining the regional implications and predictability of ENSO-linked extreme weather events for better disaster preparedness and resilience should be the main goals of future research.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».