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

A major sudden stratospheric warming (SSW) occurred in the Northern Hemisphere in early 2021, which caused extreme cold events across East Asia and North America, with record-breaking cold temperatures, notably 151 deaths in Texas. A better understanding of the SSW predictability for an improved surface seasonal to subseasonal (S2S) forecast is a pressing issue. Here we quantify the practical local predictability limit and find sensitive areas of forecast errors of 2021 SSW event within ERA5 reanalysis data and subseasonal to seasonal (S2S) reforecasts. A novel nonlinear method, Backward Searching for the Initial Condition (BaSIC), is used to estimate the local predictability of the SSW. This method is advanced because the nature of SSW is 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.

We also trace the sensitive areas of forecast errors of this SSW. At the beginning, the overall forecast errors are relatively small, but with increase of time, errors increased more in the high altitude over central Eurasia (30°E-60°E). This indicates that this area is sensitive to forecast error growth, which limits the forecast skills of the 2021 SSW event. And it suggests that the central Eurasia is a key area for the improvements of the SSW forecast.