Short weather forecasts inform long-term climatology of sudden stratospheric warming

The sub-seasonal-to-seasonal (S2S) time horizon is a frontier of weather forecasting, exemplified by sudden stratospheric warming (SSW): a breakdown of the winter polar vortex, altering surface weather for months. SSW events are complex and diverse, unpredictable beyond 2 weeks, and often analyzed case by case. The historical scarcity of observations, and an unusually SSW-rich 2000's decade, lead to uncertain SSW climatology: when do they occur, how often, and how predictably? Long, expensive model runs could answer these statistical questions, but with a tradeoff between cost and bias. We instead utilize weather forecast ensembles that are high-resolution, but short (subseasonal) in duration. A simple coarse-graining procedure chains them together to estimate key climate statistics, such as annual frequencies and timing distributions of SSW events, as formulated in Transition Path Theory. We use S2S forecasts between 1996-2018, but find that the SSW statistics match well with 20th-century reanalysis. Our method extrapolates the climatology well beyond what is possible with the short observational dataset that initialized the forecasts, yielding accurate estimates of 1 in a century events. This suggests exciting new uses for ensemble forecasts in rare event analysis.