Meteorological conditions intensely influence building performance, particu-larly energy use, thermal comfort, and thermal behaviour. Fluctuations in air temperature, relative humidity, solar radiation, wind, and precipitation can affect energy demand and indoor conditions, while conventional weather da-tasets may not fully capture extreme climatic conditions. This review exam-ines how meteorological conditions and weather-data representation influ-ence building performance. It reviews different approaches for developing weather data, including interpolation, statistical and dynamical downscaling, and weather-data generation. Methods for identifying extreme events, such as threshold-based approaches, anomaly detection, and Extreme Value Theo-ry, are also discussed in relation to building-performance assessment. The reviewed studies show that meteorological parameters can affect energy de-mand, thermal performance, and thermal comfort, while extreme events such as heatwaves can increase overheating and place additional stress on buildings. Typical Meteorological Year datasets are useful for representing typical climate conditions, whereas Representative Meteorological Year da-tasets can better capture unusual and extreme conditions and help assess peak loads, thermal stress, natural ventilation, and outdoor comfort. The re-view also highlights the importance of suitable performance indicators and future heatwave weather files for understanding building response under changing climatic conditions. Overall, appropriate representation of meteoro-logical conditions is important for reliable building-performance assessment and for developing climate-responsive designs.