Artificial intelligence and machine learning: revolutionizing weather forecasting

Pappenberger, F., Wedi, N., Chantry, M., Lessig, C., Lang, S., Deuben, P., Clare, M., Magnusson, L., Gascón, E., Rabier, F., McGovern, A., Badjana, H. M., de Burgh-Day, C., Luterbacher, J., Kuglitsch, M. M. and Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X (2024) Artificial intelligence and machine learning: revolutionizing weather forecasting. In: Stuart, L., Pusch, C., Bhasin, I. and Gallo, I. (eds.) United in Science 2024. World Meteorological Organization, pp. 16-21.

Abstract/Summary

Artificial intelligence (AI) and machine learning (ML) can make skillful weather modelling faster, cheaper and more accessible, enabling a paradigm shift in predicting extreme and hazardous weather events. Gaps in data availability, inadequate model resolution and concerns about ethics, such as insufficient transparency and unequal access, are challenges that limit the application of AI/ML for weather forecasting. Scientific advancements, capacity development and global collaboration can unlock the full potential of AI/ML in supporting climate change adaptation, disaster risk reduction and sustainable development while bridging global technological disparities.

Item Type	Book or Report Section
URI	https://reading-clone.eprints-hosting.org/id/eprint/118548
Item Type	Book or Report Section
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	World Meteorological Organization
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