With the rapid expansion of wind and solar integration capacity

the inherent uncertainties of these renewable energy sources pose significant operational challenges to new power systems. Moreover

the stochasticity of wind and solar generation is profoundly influenced by meteorological conditions. Recent frequent occurrence of high-impact weather events has further intensified the volatility of wind and solar resources

exacerbating system-level uncertainties in new power systems. Improving the prediction accuracy of wind and solar time series is critical to mitigating these uncertainties. However

existing researches primarily focus on short- and medium-term forecasting under normal operating conditions

with limited attention to long-term prediction methodologies under high-impact weather conditions. To address this gap

this paper presents a systematic review of long-term wind and solar time series prediction in new power systems

explicitly accounting for high-impact weather influences. First

we summarize the effects of high-impact weather events on new power systems and their forecasting methods. Next

we categorize and analyze long-term prediction methods for wind and solar time series under both normal and high-impact weather conditions. Then

we discuss key application scenarios for such predictions in power system planning and operation

along with specific application examples. Finally

we identify critical research gaps in current studies and propose future directions

providing methodological insights for improving the resilience and supporting the long-term planning of new power systems under high-impact weather conditions.