Téléchargez le livre : Understanding Atmospheric Rivers Using Machine Learning

Understanding Atmospheric Rivers Using Machine Learning

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Springer


Paru le : 2024-06-22

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Description

This book delves into the characterization, impacts, drivers, and predictability of atmospheric rivers (AR). It begins with the historical background and mechanisms governing AR formation, giving insights into the global and regional perspectives of ARs, observing their varying manifestations across different geographical contexts. The book explores the key characteristics of ARs, from their frequency and duration to intensity, unraveling the intricate relationship between atmospheric rivers and precipitation. The book also focus on the intersection of ARs with large-scale climate oscillations, such as El Niño and La Niña events, the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO). The chapters help understand how these climate phenomena influence AR behavior, offering a nuanced perspective on climate modeling and prediction. The book also covers artificial intelligence (AI) applications, from pattern recognition to prediction modeling and early warning systems. A case study on AR prediction using deep learning models exemplifies the practical applications of AI in this domain. The book culminates by underscoring the interdisciplinary nature of AR research and the synergy between atmospheric science, climatology, and artificial intelligence
Pages
74 pages
Collection
n.c
Parution
2024-06-22
Marque
Springer
EAN papier
9783031634772
EAN PDF
9783031634789
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
7
Taille du fichier
5683 Ko
Prix
47,46 €
EAN EPUB
9783031634789
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
7
Taille du fichier
41431 Ko
Prix
47,46 €

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