株式会社極東書店トップ商品一覧Understanding Atmospheric Rivers Using Machine Learning. 2024 ed.

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Understanding Atmospheric Rivers Using Machine Learning. 2024 ed.

Understanding Atmospheric Rivers Using Machine Learning. 2024 ed.

・ISBN 978-3-031-63477-2 paper EUR 49.99

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お気に入り
著者・編者Goyal, Manish Kumar / Singh, Shivam,
シリーズ (SpringerBriefs in Applied Sciences and Technology)
出版社 (Springer International Publishing AG, SZ)
出版年月2024
ページ数74 pp.
言語ENG
ニュース番号<A03-34968>

解説

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 Nino and La Nina 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