589 / 2026-03-23 14:11:42

Ensemble-based Assimilation of Sounding Observations with AI Weather Models

AI weather model,data assimilation,weather forecasts

主题1 天气、气候、全球变化、行星大气 > 专题1.20 灾害性天气的资料同化与发生发展机理

The artificial intelligence (AI)-based weather models have shown great promise for weather forecasts. But they rely on the initial conditions provided by traditional paradigm of numerical weather prediction, which has a cycled data assimilation (DA) to combine short-term forecasts and observations. This study demonstrates the ability of AI weather models within the framework of cycling DA, achieving a successful and stable cycling DA with assimilation of real-time sounding observations. For FengWu, assimilation of wind observations can better constrain the atmospheric state than assimilation of temperature observations, and both produce more accurate analyses and 6-h forecasts than assimilation of specific humidity observations. But when Pangu-Weather is applied, assimilating wind observations cannot constrain the state variables of temperature and specific humidity as well as that with FengWu. This indicates that the influences of observation types on cycling DA with AI weather models are model-dependent, associated with the intrinsic error characteristics.