Earth Virtualization Engines -- A Technical Perspective
Torsten Hoefler
B. Stevens
A. Prein
Johanna Baehr
T. Schulthess
Thomas F. Stocker
John Taylor
Daniel Klocke
Pekka Manninen
P. Forster
Tobias Kölling
N. Gruber
H. Anzt
Claudia Frauen
F. Ziemen
Milan Klöwer
K. Kashinath
Christoph M. Schär
O. Fuhrer
Bryan Lawrence

Abstract
Participants of the Berlin Summit on Earth Virtualization Engines (EVEs) discussed ideas and concepts to improve our ability to cope with climate change. EVEs aim to provide interactive and accessible climate simulations and data for a wide range of users. They combine high-resolution physics-based models with machine learning techniques to improve the fidelity, efficiency, and interpretability of climate projections. At their core, EVEs offer a federated data layer that enables simple and fast access to exabyte-sized climate data through simple interfaces. In this article, we summarize the technical challenges and opportunities for developing EVEs, and argue that they are essential for addressing the consequences of climate change.
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