Lang, Simon; Alexe, Mihai; Chantry, Matthew; Dramsch, Jesper; Pinault, Florian; Raoult, Baudouin; Clare, Mariana C. A.; Lessig, Christian; Maier-Gerber, Michael; Magnusson, Linus; Bouallègue, Zied Ben; Nemesio, Ana Prieto; Dueben, Peter D.; Brown, Andrew; Pappenberger, Florian; Rabier, Florence · 2024-08-07
The Artificial Intelligence Forecasting System (AIFS), developed by ECMWF, leverages graph neural networks and transformers to produce highly skilled medium-range weather forecasts, running alongside traditional numerical models and providing open-access predictions.
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This paper introduces a proof-of-concept system that combines a curated knowledge graph with AI agents to overcome persistent barriers in climate data science, such as fragmented datasets and high technical skill requirements. By enabling natural-language interaction, automated data access, and cloud-native workflows, the system lowers entry barriers, improves reproducibility, and demonstrates how a knowledge-graph-driven approach can democratize climate data science and support scalable human–AI collaboration.
arXiv
Shared topics: Education and skills; Climate and greenhouse gases; Weather, hazards, and adaptation
This study presents a machine learning framework for high-resolution regional weather forecasting using boundary-forced graph-based models, demonstrating strong predictive skill and lower computational costs compared to traditional methods.
arXiv
Shared topics: Education and skills; Climate and greenhouse gases; Weather, hazards, and adaptation
Using natural language processing and interviews, this study finds that vague definitions and geographic inaccessibility of green jobs in Worcester, MA hinder the development of a climate-ready workforce and the implementation of local climate adaptation plans.
Frontiers in Sociology
Shared topics: Education and skills; Climate and greenhouse gases; Weather, hazards, and adaptation
There is a growing need to prepare students to address complex environmental challenges, particularly climate change and the expanding role of artificial intelligence (AI). This article examines the adaptation of the Artificial Intelligence for Social Good (AI4SG) Ideation module, a pitch- and project-based teaching framework designed to integrate AI literacy and sustainability education.
