Extreme precipitation events are projected to become more frequent and intense in Europe under climate change. In recent decades, cut-off lows (COLs) – cold-core, upper-level low-pressure systems originating from polar regions – have caused severe impacts across several European countries, leading to unprecedented rainfall totals. Understanding how the influence of COLs on extreme precipitation may evolve in a warming climate is therefore a key scientific challenge. To address this issue, we develop an objective detection algorithm based on 500 hPa geopotential height (Z500) fields to identify COLs.</p> <p>Using the ERA5 reanalysis for both daily precipitation and Z500 fields, we construct a climatology of COLs affecting Europe over the period 1940–2024. We first show that the total number of COLs exhibits no significant long-term trend. We then attribute daily precipitation events to potential COL influence. Our results indicate that approximately 49% of the most extreme European precipitation events are associated with a COL. Furthermore, we find that the statistical significance of trends in the annual number of COLs associated with precipitation extremes depends on both the precipitation threshold used to define extremes and the season considered.</p> <p>In a second step, the same detection algorithm is applied to Z500 fields from six Earth System Models (ESMs) participating in the CMIP6 experiments recommended for EURO-CORDEX downscaling. We show that these state-of-the-art ESMs exhibit a negative bias in the simulated number of COLs over the historical period (1981–2014), which is particularly pronounced over the Mediterranean basin. Using bias-adjusted precipitation fields, precipitation events in each ESM are then attributed to COLs under the SSP5-8.5 scenario. As in the reanalysis, trends in the number of COL-associated events depend on the precipitation threshold.</p> <p>Overall, this study provides new insights into the past and future synoptic-scale impacts of COLs over Europe and supports the interpretation that observed trends in extreme precipitation are primarily thermodynamically driven rather than dynamically. Because the proposed algorithm relies solely on Z500 fields – an accessible and widely available dataset – it can be readily applied to other reanalysis products or climate model outputs, offering a practical tool for assessing model performance in representing COL occurrence over specific regions.