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.

柏林峰会关于地球虚拟化引擎（EVEs）的参与者讨论了改进我们应对气候变化能力的思想和概念。EVEs旨在为广泛用户提供互动且易于访问的气候模拟和数据。它们结合高分辨率的基于物理的模型与机器学习技术，以改进气候预测的准确性、效率和可解释性。作为核心，EVEs提供了一个联邦数据层，通过简单的接口快速访问以拍字节数计的气候数据。在本文中，我们总结了开发EVEs面临的技术挑战和机遇，并认为它们对应对气候变化的后果至关重要。

地球虚拟化引擎--技术视角