학술논문

Earth Virtualization Engines: A Technical Perspective
Document Type
Periodical
Source
Computing in Science & Engineering Comput. Sci. Eng. Computing in Science & Engineering. 25(3):50-59 Jun, 2023
Subject
Computing and Processing
Bioengineering
Communication, Networking and Broadcast Technologies
Earth
Climate change
Machine learning
Data models
Virtualization
Meteorology
Meetings
Language
ISSN
1521-9615
1558-366X
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 its 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.