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Climate Extreme and Atmospheric Rivers with Machine Learning

Name: Climate Extreme and Atmospheric Rivers with Machine Learning
Brand: Springer, Berlin
SKU: 9783031634772
Price: 262.82 RON
Availability: InStock

Autor: Manish Kumar Goyal, Shivam Singh

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Legare: Carte broșată

Editura: Springer, Berlin

Disponibilitate: În depozitul extern

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262.82 lei

This book delves into the characterization, impacts, drivers, and predictability of atmospheric rive...

Informații despre carte

Autor

Manish Kumar Goyal, Shivam Singh

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2024

Pagini

100

EAN

9783031634772

Enbook ID

46020604

Editura

Springer, Berlin

Greutate

143

Dimensiuni

155 x 235

Descriere completă

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

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Climate Extreme and Atmospheric Rivers with Machine Learning

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