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Abstract

Hot temperature extremes have increased substantially in frequency and magnitude over
past decades. A widely used approach to quantify this phenomenon is standardizing temperature data
relative to the local mean and variability of a reference period. Here we demonstrate that this conventional
procedure leads to exaggerated estimates of increasing temperature variability and extremes. For example,
the occurrence of “two-sigma extremes” would be overestimated by 48.2% compared to a given reference
period of 30 years with time-invariant simulated Gaussian data. This corresponds to an increase from a 2.0%
to 2.9% probability of such events. We derive an analytical correction revealing that these artifacts prevail
in recent studies. Our analyses lead to a revision of earlier reports: For instance, we show that there is no
evidence for a recent increase in normalized temperature variability. In conclusion, we provide an analytical
pathway to describe changes in variability and extremes in climate observations and model simulations.