Understanding Atmospheric Rivers Using Machine Learning

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Details

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


Presents interdisciplinary approach and global and regional focus Provides large-scale climate influence and AI applications Shows practical relevance

Autorentext

Prof. Manish Kumar Goyal is a Chair Professor- BIS Standardization and Dean, Infrastructure Development at the Indian Institute of Technology Indore. His research interests include water, air, and soil, with a focus on GIS and remote sensing applications in water, environment, and climate change. Mr. Shivukumar Rakkasagi is a PhD Scholar and DST INSPIRE Fellow at the Indian Institute of Technology Indore. He holds a Bachelor's degree in Civil Engineering from VTU University and an MSc in Geoinformatics from KSRDPR University. His research spans a wide array of domains, including Geospatial Intelligence, Climate Risk Analytics, Sustainable Development, Wetlands, Key Biodiversity Areas, Multi-Hazard Disaster Management, Techno-Societal Frameworks, and Water Resources Management.


Inhalt

Understanding Atmospheric Rivers and Exploring Their Role as Climate Extremes.- Characterization and Impacts of Atmospheric Riversharacterization and Impacts of Atmospheric Rivers.- Key Characteristics of Atmospheric Rivers and Associated Precipitation.- Major Large-Scale Climate Oscillations and their Interactions with Atmospheric Rivers.- Role of Machine Learning in Understanding and Managing Atmospheric Rivers.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031634772
    • Genre Aeronautical Engineering
    • Lesemotiv Verstehen
    • Anzahl Seiten 74
    • Herausgeber Springer
    • Gewicht 143g
    • Untertitel SpringerBriefs in Applied Sciences and Technology
    • Autor Manish Kumar Goyal , Shivam Singh
    • Titel Understanding Atmospheric Rivers Using Machine Learning
    • ISBN 978-3-031-63477-2
    • Format Kartonierter Einband
    • EAN 9783031634772
    • Jahr 2024
    • Größe H4mm x B155mm x T235mm
    • Sprache Englisch

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