Rainfall regimes are experiencing variations due to climate change, and these variations are adequately simulated by Earth System Models at a daily scale for most regions. However, there are not enough raw outputs to study extreme and sub-daily precipitation patterns on a local scale. To address this challenge, Monjo developed the n-index by characterizing the intensity and concentration of precipitation based on mono-fractal theory. In this study, we explore the use of a multi-fractal approach to establish a more accurate method of time scaling useful to study extreme precipitation events at a finer temporal resolution. This study was carried out on the reference station of Barcelona (Spain) and its surroundings in order to be representative of the Mediterranean climate. For return periods between 2 and 50 years, two variables were analyzed: the n-index and the reference intensity $I_0$. Moreover, a new parameter, the so-called “breaking point”, was designed here to describe the reference intensity $I_0$, which is predominant for low time ranges. The results showed that both parameters are dependent on the time steps and the return period, and the scores confirmed the validity of our approach. Finally, the n-index was projected under downscaled CMIP6 climate scenarios by 2100, showing a sustained increase of up to +10%.

El Niño–Southern Oscillation (ENSO) mainly influences the North Atlantic and European (NAE) climate through its teleconnection with the North Atlantic Oscillation. A strengthening of this teleconnection has been found under greenhouse warming, but its evolution across the seasonal cycle, its interplay with other tropical ocean basins, and its impacts on NAE predictability in future scenarios remain unclear. Using CMIP6 models, we show that this teleconnection intensifies and expands eastward under greenhouse warming scenarios, being robust in late winter and spring, systematically increasing potential predictability. In late winter, jet stream changes expand the predictable regions, while amplified ENSO amplitude and equatorial rainfall increase the magnitude of skill. Conversely, spring potential predictability is associated with changes in ENSO variability combined with a plausible enhancement of Tropical North Atlantic influence. These results provide multimodel evidence that greenhouse warming enhances ENSO-driven NAE potential predictability, with implications for climate adaptation in the region.