A new paper on identifying and investigating seasonal extremes accepted in J. Climate

Seasonal extremes are difficult to study in the observational record because, by the definition of the word extreme, only very few such seasons occurred at any location on the globe. In a new INTEXseas study led by Matthias Röthlisberger and in collaboration with colleagues from the group of Reto Knutti at ETH as well as with Christoph Frei from MeteoSwiss we propose to tackle this problem by spatially pooling extreme season events. We use a statistical modeling approach to quantify the local return period of any summer or winter seasonal mean two meter temperature value in the ERA-Interim data set from 1979 to 2018 and identify contiguous spatial extreme season objects from these return periods. Applying the same methodology to 1200 years of data from the Community Earth System Model Large Ensemble (CESM-LENS) then yields large samples of extreme season events with comparable characteristics to even the most extreme observed ones. These large samples of events allows studying extreme seasons in hitherto unexplored ways. We reveal a striking co-occurrence of El Niño to La Niña transitions and the largest mid-latitude extreme summer objects and evaluate CESM with regard to  extreme season characteristics. Finally, we quantify regional return periods of extreme season, which inform about the occurrence of an extreme season with particular size and intensity characteristics within a predefined region, e.g., how often does a winter with comparable area and intensity characteristics as the cold North American 2013/14 winter occur in Europe. The approach is currently being extended to other variables such as seasonal mean precipitation and wind, and will thus serve as a basis for several subsequent INTEXseas studies.
The Figure above shows the six largest ERA-Interim hot summer and cold winter objects in the mid-latitudes. Shading depicts the local return period of the respective seasonal mean T2m value and stippling shows the identified extreme season objects.