Studies addressing the response of glaciers to climate change have so far analyzed the effect of long-term trends in a particular set of meteorological variables only, implicitly assuming an unaltered climatic variability. Here a framework for distinguishing between year-to-year, month-to-month and day-to-day variability is proposed. Synthetically generated temperature and precipitation time series following the same long-term trend but with altered variability are then used to force an ice-dynamics model set up for Rhonegletscher, Swiss Alps. In the case of temperature, variations in the day-to-day variability are shown to have a larger effect than changes at the yearly scale, while in the case of precipitation, variability changes are assessed as having negligible impact. A first set of scenarios is used to show that compared to reference, doubling the temperature variability can reduce glacier ice volume by up to 64% within half a decade. A second set derived from the results of the European ENSEMBLES project, however, shows that such changes are expected to remain below 8% even for extreme scenarios. Although the latter results relativize the importance of the effect in the near future, the analyses indicate that at least caution is required when assuming ‘unchanged variability’.