Abstract/Summary

Global warming involves changes not only in the mean atmospheric temperature, but also in its variability and extremes. Here we use a feature-tracking technique to investigate the dynamical contribution to temperature anomalies in the northern hemisphere in CMIP5 climate-change simulations. We develop a simple theory to explain how temperature variance and skewness changes are generated dynamically from mean temperature gradient changes, and demonstrate the crucial role of regional warming patterns in shaping the distinct response of cold and warm anomalies. We also show that skewness changes must be taken into account, in addition to variance changes, in order to correctly capture the projected temperature variability response. These changes in variability may impact humans, agriculture and animals, as they experience not only a warmer mean climate, but also a new likelihood of temperature anomalies within that climate.