Climate variability on Fit for 55 European power systems

temperatures prevail. A different pattern is associated with each day, allowing us to investigate the average deviation of the analysed variables from their normal values. For each of the six indicators we calculate the average daily deviation during a specific pat- tern in relation to the overall mean (Fig 6). In other words, for each of the variables we calcu- late the percentage difference at day t from the average value (i.e., climatology) for all the days t across all the considered years. We then apply a seven-day moving average to each variable for the calculation of the mean, in order to estimate a more robust climatology. The change of CO2 intensity shows that during patterns AT, ScTr, Ar, and EuBL the low- carbon generation across Europe seems to follow the same trend: an increase for all the regions during the cyclonic regimes (first two) and a decrease for the rest. The emission intensity is clearly linked with the availability of wind power, as clearly visible in the patterns AT and ScTR where an increased availability of wind is associated with lower emissions across the entire continent. The same reversed pattern is visible in EuBL. Consistently with the results in [23], we find opposing behaviour for wind power between the northern regions (Northern, CWE, CEE, UK & Ireland) and southern areas (Italy and Ibe- ria) for most of the weather patterns, in particular between the ZO and GL patterns. Indeed, wind and solar power consistently take up opposing positions across most of the patterns,

although the variability of solar power is clearly weaker than that of wind. Some of the patterns are associated with the North Atlantic Oscillation (NAO). The NAO is the most important European weather phenomenon and plays a very important role in Fig 5. The weather regimes used in this study introduced in (Grams et al., 2017). The composite shows the mean 500-hPa geopotential height anomaly in the winter months. The eighth panel represents the ‘climatology’, the lack of other regimes. The percentage near the name of the regime represents the relative frequency of the regimes. Figure taken from Fig 1 in [24], published with CC BY 4.0 license. https://doi.org/10.1371/journal.pone.0289705.g005 PLOS ONE Climate variability on Fit for 55 European power systems PLOS ONE | https://doi.org/10.1371/journal.pone.0289705 December 20, 2023 9 / 16