Objective Against the dual backdrop of global climate change and energy transition, the frequent and intense occurrence of extreme weather events poses severe challenges to power systems with a high proportion of renewable energy from wind and solar. This article aims to systematically summarize the evolution trends of extreme weather, impact mechanisms, and advancements in meteorological forecasting technology from the perspectives of meteorology and climatology, providing scientific references for new power systems to cope with climate risks.

Method Focusing on major weather and climate risks such as tropical cyclones, extreme high and low temperatures, severe convection, drought, and compound extreme events, this paper summarized and reviewed relevant domestic and international literature, incorporating research advancements in climate change attribution and prediction, wind and solar power output mechanisms, power grid resilience assessment, numerical weather forecasting, and artificial intelligence forecasting.

Result Research indicates that extreme wind speeds and sudden changes in wind direction caused by typhoons can cause structural damage to wind turbines, high temperatures reduce photovoltaic conversion efficiency, icing, hail, and severe convective weather threaten the safety of power transmission and transformation in the grid, and "low wind-low light" compound events trigger extreme supply-demand imbalances. Various extreme weather conditions pose multiple overlapping threats to the operation of wind and solar systems. Climate change also affects energy meteorological factors such as wind speed, surface solar radiation, and heating and cooling loads, exerting long-term impacts on the assessment of wind and solar resources and system planning. Conceptual frameworks such as the "resilience trapezoid" and various assessment methods provide theoretical tools for understanding system performance degradation and recovery processes under extreme weather conditions. New forecasting methods based on artificial intelligence have demonstrated potential applications in power prediction, extreme weather early warning, and resilience assessment.

Conclusion In the future, it is necessary to strengthen research on the formation mechanism of compound extreme events and the multivariate dependence structure, improve the method of transforming global forecast information into wind speed, irradiance, and power predictions at the station scale, and develop a professional meteorological service system tailored for energy applications, providing scientific support for the safe and stable operation of new power systems.