Artificial Intelligence for Atmospheric Sciences: A Research Roadmap
It offers a roadmap for researchers in atmospheric and computer sciences to address current and emerging challenges in applying AI, though it is incremental as it synthesizes existing knowledge rather than presenting new methods.
This paper tackles the integration of Artificial Intelligence (AI) into atmospheric sciences by providing a critical interdisciplinary overview and research roadmap, addressing challenges like big data and infrastructure to enhance understanding of environmental phenomena and disaster prediction.
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.