Artificial Intelligence for Atmospheric Sciences: A Research Roadmap

TL;DR

This paper provides a comprehensive overview of how AI can revolutionize atmospheric sciences by addressing current challenges and outlining a research roadmap for future integration of AI technologies.

Contribution

It offers an interdisciplinary overview and a detailed research roadmap for integrating AI into atmospheric sciences, highlighting challenges and future directions.

Findings

AI significantly advances atmospheric data analysis and prediction.

Key challenges include data management and infrastructure issues.

A strategic research roadmap is proposed for AI integration in atmospheric sciences.

Abstract

Atmospheric sciences are crucial for understanding environmental phenomena ranging from air quality to extreme weather events, and climate change. Recent breakthroughs in sensing, communication, computing, and Artificial Intelligence (AI) have significantly advanced atmospheric sciences, enabling the generation of vast amounts of data through long-term Earth observations and providing powerful tools for analyzing atmospheric phenomena and predicting natural disasters. This paper contributes a critical interdisciplinary overview that bridges the fields of atmospheric science and computer science, highlighting the transformative potential of AI in atmospheric research. We identify key challenges associated with integrating AI into atmospheric research, including issues related to big data and infrastructure, and provide a detailed research roadmap that addresses both current and emerging challenges.