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Other literature type . 2025
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Project deliverable . 2025
License: CC BY
Data sources: Datacite
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Project deliverable . 2025
License: CC BY
Data sources: Datacite
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AD4GD D5.2 Artificial intelligence resources for Earth system modelling

Authors: Lazcano, Raquel; Di Pietro, Franco; García-Gómez, Joaquín; Galiana, Mar; Berwanger, Kristian; Mebus, Lina; Crettaz, Cédric; +3 Authors

AD4GD D5.2 Artificial intelligence resources for Earth system modelling

Abstract

This deliverable builds upon D5.1 and outlines progress in applying Artificial Intelligence and High-Performance Computing within the AD4GD project. It details the use of AI models in pilot studies, such as water level prediction in Berlin lakes and connectivity mapping in Catalonia, highlighting the AI models ability to process complex environmental data efficiently. The document also presents the development of user-friendly interfaces that make these advanced tools accessible to non-expert stakeholders, promoting informed decision-making. Additionally, it reports on the integration of HPC resources to support AI model training and execution, enhancing performance and scalability. The deliverable concludes with reflections on the benefits, limitations, and future directions of these technologies in AD4GD pilots.

Keywords

Artificial intelligence, Artificial Intelligence, High Performance Computing, Artificial Intelligence/trends, User interface

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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