Quantifying the local predictability of the 2021 sudden stratospheric warming event using a novel nonlinear method

Abstract. Sudden stratospheric warming (SSW) is identified as a key role in improving the winter subseasonal-to-seasonal prediction, for its surface impacts up to two weeks through stratosphere troposphere coupling. A better understanding of the predictability of the SSW itself, thus, is fundamental. Most of the previous studies investigate the predictability of SSW events using linear approaches and give the approximate predictability.

In the study, we quantify the local predictability limit the 2021 SSW event, which caused cold extremes across East Asia and North America, by applying a nonlinear method, Backward Searching for the Initial Condition (BaSIC), within ERA5 reanalysis data and the S2S reforecasts. The nonlinear method BaSIC is advanced because the nature of SSW is a chaotic system with intrinsic properties, making it difficult to measure its predictability with traditional linear methods. The local predictability limit of this 2021 SSW event is estimated to be 17 days using BaSIC method, exceeding previous estimations by one to two weeks using linear methods.

To gain further insight into where the errors may originate and propagate, we trace the sources of forecast errors of this SSW to the area of the fastest error growth. At the beginning of the SSW forecast, the overall forecast errors are relatively small over the whole polar stratosphere; the errors grow slowly in the first 2 weeks, but increase rapidly in the mid-high latitudes over central Eurasia (30°–60° E) and propagate into the rest of Eurasia. This indicates that the forecast errors in the 2021 SSW event mainly originate from the high altitude over central Eurasia.