Abstract

Abstract Meteorological extremes on the seasonal time scale have received increased attention due to their relevance for society and economy. A recently developed approach to identify seasonal extremes is applied here to ERA5 reanalyses from 1950 to 2020 to identify hot and cold, wet and dry, and stormy and calm extreme seasons globally. The approach consists of (i) fitting a statistical model to seasonal mean values (of temperature, precipitation, and wind speed) at each grid point, (ii) selecting a local return period threshold above which seasonal mean values are deemed extreme, and (iii) forming spatially coherent extreme season objects. The paper introduces the ERA5 extreme season explorer, an open-access web portal enabling researchers to visualize and download extreme season objects of any of the six types in their region of interest, for further investigating their underlying dynamics, statistical properties, and impacts. To illustrate the potential of our extreme season objects, we first discuss the top 10 cold winters in ERA5 globally and then focus on an unusual triple-compound extreme season in winter 1953/54 in Europe, which was simultaneously extremely cold, dry, and calm. We show that detailed analysis of weather system dynamics, including cyclones, blocks, jets, and Rossby waves, provides important insight into the processes leading to extreme seasons. In summary, this study presents for the first time a catalogue of objectively identified extreme seasons in the last decades, shows exemplarily how large-scale dynamics can lead to such seasons, and with the help of the explorer supports the community in accelerating research in this important area at the interface of weather and climate dynamics.

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