Abstract

AbstractThis study explores seasonal forecast skill and signal‐to‐noise (SN) ratio for stratospheric polar vortex (SPV) variations during Northern winter using hindcast (HC) data of six systems initialized around early November in the Copernicus Climate Change Service database. Results show high skill for December‐January‐February (DJF) mean El Niño/Southern Oscillation and Quasi‐Biennial Oscillation (QBO) variations, although it is suggested that some systems underestimate the QBO amplitude. The ENSO and QBO variations in the HC data are also suggested to be underdispersive having too high SN ratio due to too strong signal and/or too weak noise (spread). The skill for DJF mean SPV variations is limited, with four systems having marginal skill near the 95% level, whereas the SN ratio is suggested to be realistic. It is also shown that no system has skill (evaluated using the Brier Score) at the 95% level in forecasting if each DJF winter experiences one or more major sudden stratospheric warmings, when a bias of the polar vortex strength in each system is simply considered. A comparison of the ensemble members for each system, when divided into two groups by the strength of the QBO‐SPV teleconnection, suggests an increase in the skill for SPV variations for the group of stronger teleconnection. This confirms the idea that the QBO‐SPV teleconnection contributes to the skill for SPV variations, and also suggests that the skill for SPV variations can be improved as the HC QBO and QBO‐SPV teleconnection are better simulated.

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