Climate change manifests itself not only in shifts of long-run averages but also in changes to the entire distribution of environmental variables such as temperature, precipitation, and wind speed. This paper proposes a simple, rank-based regime shift index (RSI) to quantify how much an observed climate regime departs from a reference distribution, such as a historical baseline or a policy target. The index compares cumulative distributions rather than densities and is therefore invariant under strictly increasing transformations of the underlying variable. Empirically, it can be estimated from daily or monthly data through a closed form expression that depends only on the reference cumulative distribution function (CDF) evaluated at observed outcomes. We illustrate the method with a case study for Geneva-Cointrin (Switzerland), using homogeneous daily mean temperature data from 1864 to 2024 provided by MeteoSwiss. The regime-shift index is computed for successive decades relative to the 1961-1990 WMO normal period and summarizes the extent to which recent temperature distributions deviate from that baseline. The resulting one-number summaries complement standard climate indicators and yield clear, interpretable visualizations of regime shifts over time and across locations.