We analyse extreme daily minimum temperatures in winter months over the island of Ireland from 1950-2022. We model the marginal distributions of extreme winter minima using a generalised Pareto distribution (GPD), capturing temporal and spatial non-stationarities in the parameters of the GPD. We investigate two independent temporal non-stationarities in extreme winter minima. We model the long-term trend in magnitude of extreme winter minima as well as short-term, large fluctuations in magnitude caused by anomalous behaviour of the jet stream. We measure magnitudes of spatial events with a carefully chosen risk function and fit an r-Pareto process to extreme events exceeding a high-risk threshold. Our analysis is based on synoptic data observations courtesy of Met Éireann and the Met Office. We show that the frequency of extreme cold winter events is decreasing over the study period. The magnitude of extreme winter events is also decreasing, indicating that winters are warming, and apparently warming at a faster rate than extreme summer temperatures. We also show that extremely cold winter temperatures are warming at a faster rate than non-extreme winter temperatures. We find that a climate model output previously shown to be informative as a covariate for modelling extremely warm summer temperatures is less effective as a covariate for extremely cold winter temperatures. However, we show that the climate model is useful for informing a non-extreme temperature model.

翻译：本研究分析了1950年至2022年间爱尔兰岛冬季月份的极端日最低气温。我们采用广义帕累托分布（GPD）对极端冬季最低气温的边缘分布进行建模，捕捉了GPD参数中的时空非平稳性。我们探究了极端冬季最低气温中两种独立的时序非平稳性：既模拟了极端冬季最低气温强度的长期趋势，也模拟了由急流异常行为引起的短期大幅度波动。通过精心选择的风险函数度量空间事件的强度，并对超过高风险阈值的极端事件拟合r-帕累托过程。本分析基于爱尔兰气象局和英国气象局提供的天气观测数据。研究表明，在研究期间极端寒冷冬季事件的发生频率正在下降。极端冬季事件的强度亦呈减弱趋势，表明冬季正在变暖，且其变暖速率明显快于极端夏季气温。我们还发现极端寒冷冬季气温的变暖速率快于非极端冬季气温。研究发现，先前被证明可作为极端炎热夏季气温建模协变量的气候模型输出，在作为极端寒冷冬季气温的协变量时效果较差。然而，该气候模型在构建非极端气温模型时仍具有参考价值。