The journal Frontiers in Climate has officially opened the research topic AI for Good in Climate Science: Real-World Machine Learning and Deep Learning for Climate Monitoring, Adaptation, and Mitigation, which counts on the participation of researcher André Belém, from the Observatório Oceanográfico at the Universidade Federal Fluminense (UFF), as part of its editorial team.
The initiative brings together scientific contributions on the application of artificial intelligence (AI), particularly machine learning and deep learning, to the understanding of climate change and to the development of solutions for monitoring, adapting to, and mitigating its impacts.
Although these technologies offer new possibilities for analyzing large volumes of environmental data, their application under real-world conditions still presents challenges related to transparency, reproducibility, validation of results, and uncertainty assessment.
The research topic seeks to gather works that combine computational innovation with scientific rigor, with particular attention to model interpretability, the applicability of results, and the adoption of FAIR principles (Findable, Accessible, Interoperable and Reusable).
The call welcomes original research, reviews, methodological studies, perspective articles, and interdisciplinary contributions with explicit relevance to climate science.
Interested researchers can consult the full scope and submission instructions on the official research topic page.