ArchesWeather 系模型接受数十年气候模拟检验 Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations

精读摘要

ArchesWeather 与 ArchesWeatherGen 原本是为天气预报训练的机器学习模型，此前只评估到 10 天预报时效。这项研究把它们改造为受迫大气模型——用月平均海表温度做额外条件——检验其在数十年气候模拟中的技能与稳定性。确定性模型 ArchesWeather 与概率流匹配模型 ArchesWeatherGen 的长期表现，将决定 AI 天气模型能否从「预报」走向「气候」应用。 ArchesWeather and ArchesWeatherGen are ML weather models originally evaluated up to a 10-day lead time. This work adapts them as forced atmospheric models using additional conditioning on monthly mean sea surface temperature, then evaluates their skill and stability under multi-decadal climate simulations. It tests whether AI weather models can move beyond forecasting into climate applications.