Daily maximum, TX, and minimum, TN, temperatures recorded at Fabra Observatory, for the period 1914–2020 (from June to September), have permitted to identify the daytime and night time heatwaves, HWs, at the Barcelona Metropolitan Region, BMR, along 107 years. Four heatwaves indices have been computed both for maximum and minimum temperatures: the number of events per season, HWN; their maximum duration, HWD; their frequency of occurrence, HWF; and the amplitude of the hottest day event, HWA. Trends in these indices have been obtained and their statistical significance quantified by means of the Mann-Kendall test. For the whole period (1914–2020), positive significant trends have been detected for the four indices, with a marked positive trend since year 2000 for TX, and since 1985 for TN. Nevertheless, when 31-year moving windows have been analysed, both positive and negative significant trends are obtained, being remarkable the change in trend signs around 1960s. The convenience of using the four HW indices is evaluated applying a Principal Component Analysis, PCA, obtaining two principal components. Additionally, the spatial distributions of the MODIS land surface temperatures, LST, corresponding to some extreme heatwaves, permits the detection of two hotspots in the BMR, one for TX and the other for TN. It is also worth mentioning that correlations between the Western Mediterranean Oscillation index, WeMOi, and HW episodes are detected, being notable that, at the beginning of these episodes, WEMOi values are usually lower. These correlations could improve the HWs forecasting.

法布拉天文台在 1914 年至 2020 年（6 月至 9 月）期间记录的每日最高温度 TX 和最低温度 TN，已允许识别巴塞罗那大都市区的白天和夜间热浪，BMR，走过了107年。计算了最高和最低温度的四个热浪指数：每个季节的事件数量，HWN；它们的最大持续时间，HWD；它们的出现频率，HWF；以及最热日事件 HWA 的幅度。已经获得了这些指数的趋势，并通过曼-肯德尔检验量化了它们的统计显着性。在整个时期（1914年至2020年），四个指数均呈显着正向趋势，其中TX自2000年以来呈显着正向趋势，TN自1985年以来呈显着正向趋势。然而，当分析31年的移动窗口时，得到了积极和消极的显着趋势，特别是1960年代左右趋势迹象的变化。使用主成分分析 (PCA) 评估使用四个 HW 指数的便利性，获得两个主成分。此外，MODIS 陆地表面温度 (LST) 的空间分布（对应于一些极端热浪）允许在 BMR 中检测两个热点，一个用于 TX，另一个用于 TN。还值得一提的是，检测到西地中海涛动指数、WeMOi 和 HW 事件之间的相关性，值得注意的是，在这些事件开始时，WEMOi 值通常较低。这些相关性可以改善 HW 的预测。