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I train deep neural networks on data of the Earth system. More specifically, I am focusing on two applications. On the one hand, I am interested in the applicability of large-scale AI to Early Warning Systems. Within the EarthNet initiative we are leveraging high resolution satellite imagery to build data-driven impact early warning systems – with applications to anticipatory action for droughts and heat waves. On the other hand, I study the carbon cycle with neural network emulators. In particular, I am assessing the use of AI for atmospheric transport and inverse modeling – analogous to how recent works have revolutionized numerical weather prediction and other areas of scientific machine learning.
I believe solving global challenges requires working together. Let us do just that!
I believe solving global challenges requires working together. Let us do just that!
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ENVIRONMENTAL RESEARCH LETTERSno. 2 (2024): 024029
Vitus Benson, Claire Robin,Christian Requena-Mesa,Lazaro Alonso, Nuno Carvalhais,José Cortés,Zhihan Gao,Nora Linscheid,Mélanie Weynants,Markus Reichstein
arXiv (Cornell University) (2023)
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