Understanding Atmospheric Rivers Using Machine Learning

Goyal, Manish Kumar, Singh, Shivam

Understanding Atmospheric Rivers Using Machine Learning
  • 出版商: Springer
  • 出版日期: 2024-06-23
  • 售價: $2,270
  • 貴賓價: 9.5 折 $2,157
  • 語言: 英文
  • 頁數: 74
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031634772
  • ISBN-13: 9783031634772
  • 相關分類: Machine Learning

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商品描述

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

商品描述(中文翻譯)

本書深入探討大氣河流（AR）的特徵、影響、驅動因素及可預測性。書中首先介紹了大氣河流形成的歷史背景及機制，並提供了全球及區域視角的見解，觀察其在不同地理環境中的多樣表現。書中探討了大氣河流的關鍵特徵，包括其頻率、持續時間及強度，揭示了大氣河流與降水之間的複雜關係。此外，本書還聚焦於大氣河流與大型氣候振盪的交集，例如厄爾尼諾和拉尼娜事件、北大西洋振盪（NAO）及太平洋十年振盪（PDO）。各章節幫助讀者理解這些氣候現象如何影響大氣河流的行為，並提供對氣候模型及預測的細緻見解。本書還涵蓋了人工智慧（AI）的應用，從模式識別到預測建模及早期警報系統。利用深度學習模型進行大氣河流預測的案例研究，展示了AI在此領域的實際應用。最後，本書強調了大氣河流研究的跨學科特性，以及大氣科學、氣候學與人工智慧之間的協同作用。

作者簡介

Prof. Manish Kumar Goyal is a Chair professor- BIS Standardization and Dean, Infrastructure Development at Indian Institute of Technology Indore. His research interests include water resources engineering, GIS, and remote sensing applications in water and environment and climate change. He received a B.Tech. degree in Civil Engineering from the National Institute of Technology Warangal with distinction and an M.Tech. degree from the Indian Institute of Technology Roorkee. After a brief stint in corporate, he pursued a Ph.D. degree at IIT Roorkee in collaboration with the University of Waterloo, Canada. He went on to pursue further research as a postdoctoral fellow at Nanyang Technological University, Singapore, and McGill University, Canada. He holds more than 100 publications in different domains of GIS and Remote Sensing, Water Resources, Climate Change, Hydrological and Hydrodynamic Modeling, Snow and Glacier Melt, Soil Carbon Sequestration, Anthropogenic Changes, Risk, and Resilience.His name has appeared in Top 2% scientist, list prepared by Stanford University in 2020, 2021, 2022 and 2023.

作者簡介(中文翻譯)

曼尼什·庫馬爾·戈亞爾教授是印度理工學院印多爾分校的BIS標準化講座教授及基礎設施發展院長。他的研究興趣包括水資源工程、地理資訊系統（GIS）以及水環境和氣候變遷中的遙感應用。他在國立技術學院瓦朗加爾獲得了土木工程的優異學士學位（B.Tech.），並在印度理工學院魯爾基獲得碩士學位（M.Tech.）。在短暫的企業工作後，他在魯爾基的印度理工學院攻讀博士學位，並與加拿大滑鐵盧大學合作。他隨後在新加坡南洋理工大學和加拿大麥吉爾大學進行了博士後研究。他在GIS和遙感、水資源、氣候變遷、水文和水動力建模、雪和冰川融化、土壤碳封存、人為變化、風險和韌性等不同領域擁有超過100篇出版物。他的名字出現在斯坦福大學於2020、2021、2022和2023年編制的前2%科學家名單中。

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