WeatherBench 2：下一代数据驱动全球天气模型的基准

摘要

WeatherBench 2 是 Rasp等人（2020）提出的全球中程（1-14天）天气预报基准的更新版本，旨在加快数据驱动天气建模的进展。WeatherBench 2 包括一个开源评估框架，公开可用的训练、基准数据以及一个持续更新的网站，提供最新的指标和最先进的模型：https://sites.research.google/weatherbench。本文描述了评估框架的设计原则，并展示了当前最先进的物理和数据驱动天气模型的结果。这些指标基于评估领先操作性气象中心的天气预报的已建立实践。我们定义了一组主要得分，以提供模型性能的概览。此外，我们还讨论了当前评估设置中的警告和数据驱动天气预报未来面临的挑战。

English

WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an open-source evaluation framework, publicly available training, ground truth and baseline data as well as a continuously updated website with the latest metrics and state-of-the-art models: https://sites.research.google/weatherbench. This paper describes the design principles of the evaluation framework and presents results for current state-of-the-art physical and data-driven weather models. The metrics are based on established practices for evaluating weather forecasts at leading operational weather centers. We define a set of headline scores to provide an overview of model performance. In addition, we also discuss caveats in the current evaluation setup and challenges for the future of data-driven weather forecasting.

WeatherBench 2：下一代数据驱动全球天气模型的基准

WeatherBench 2: A benchmark for the next generation of data-driven global weather models

摘要

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