简化开源AI天气预报模型的运行
原标题：Making open-source AI weather forecasting models easy to run
AI 摘要
Hugging Face 与 Earthmover 联合发布博客，旨在简化开源 AI 天气预报模型的运行流程。文章指出，尽管模型权重开放，但计算、存储和带宽问题阻碍了实际应用。他们提供了使用 Earthmover 数据平台和 Hugging Face 的教程，演示如何运行 ECMWF AIFS、Microsoft Aurora 等模型，并对比 ERA5 数据。目标是让气候社区更轻松地运行这些模型。
正文节选
AI weather forecasting models now complement physics-based models while running far faster and on a fraction of the resources. Many of these state-of-the-art models are also open-weights: ECMWF's AIFS models and Microsoft's Aurora publish their weights directly on Hugging Face, and Google DeepMind has open-sourced WeatherNext 2. But open weights don't make a model easy to run. This blog post was written jointly by Earthmover and Hugging Face, and aims to reduce the friction of running open weath