Abstract: With the rapid growth of the penetration rate of new energy represented by wind and photovoltaic power, the coupling degree between new power systems and meteorological systems continues to deepen, and the analysis and generation of system operation scenarios face severe challenges. The frequent occurrence of extreme weather events has intensified fluctuations in new energy, and the uncertainty of system operation scenarios has increased sharply. However, existing methods need more consideration of the relationship between weather events and new energy output, making it difficult to accurately characterize the new energy output characteristics under the influence of extreme weather events. Therefore, this article proposes a method for generating long-term operational scenarios of systems considering extreme weather conditions. This method models meteorological factors based on the spatiotemporal distribution characteristics of extreme meteorological events. Inserting multiple short-term meteorological events into an annual time series generates a complete annual meteorological scenario through the Gaussian Process Regression (GPR) model, Copula function, and data-knowledge joint driving method. The meteorological scenario is then mapped to the new energy output scenario, and the system operation scenario is obtained by solving the unit combination problem. The proposed method was validated using the SG-126 node system, and the results showed that the method can effectively consider the impact of extreme weather events on system operation.