Abstract. Temporal (serial) clustering of extreme precipitation events on sub-seasonal timescales is a type of compound event. It can cause large precipitation accumulations and lead to floods. We present a novel, count-based procedure to identify episodes of sub-seasonal clustering of extreme precipitation. We introduce two metrics to characterise the prevalence of sub-seasonal clustering episodes and their contribution to large precipitation accumulations. The procedure does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this procedure to daily precipitation from the ERA5 reanalysis data set, we identify regions where sub-seasonal clustering occurs frequently and contributes substantially to large precipitation accumulations. The regions are the east and northeast of the Asian continent (northeast of China, North and South Korea, Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the sub-seasonal time window (here 2–4 weeks). This procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different timescales (sub-seasonal to decadal). The code is available at the listed GitHub repository.

Warm and moist air masses are transported into the Arctic from lower latitudes throughout the year. Especially in winter, such moist intrusions (MIs) can trigger cloud formation and surface warming. While a typical cloudy state of the Arctic winter boundary layer has been linked to the advection of moist air masses, direct observations of the transformation from moist midlatitude to dry Arctic air are lacking. Here, we have used observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) project to compile Eulerian observations along the trajectories of warm and cold air masses in a Lagrangian sense, showing the cooling and drying of air masses over sea ice and moistening over the open ocean. Air masses originating mostly over open water generate cloudy conditions over the observation site, whereas air masses originating over continents or sea ice generate radiatively clear conditions. We recommend using our case‐studies and the method of linking expeditions to station soundings via back‐trajectories for modelling work in future campaigns.