Season-dependent predictability and error growth dynamics of Pacific Decadal Oscillation-related sea surface temperature anomalies

Abstract

By performing perfect model predictability experiments in a coupled general circulation model from the point of view of initial error growth, it is demonstrated that there may exist a “summer prediction barrier” (SPB) in the predictions of Pacific Decadal Oscillation-related sea surface temperature anomalies (PDO-related SSTA), which refers to the phenomenon that initial errors exhibit a significant season-dependent evolution, with the largest error growth occurring in the August–September–October (ASO) season. Due to the effect of the SPB, the prediction error of PDO-related SSTA events starts to grow rapidly during the ASO season and yields a positive (negative) prediction error for the warm (cold) events, essentially inducing a delay of the events. The SPB may be one of the main factors limiting the predictability of North Pacific sea surface temperature. The physical and dynamical mechanisms of the SPB are explored from two aspects: thermodynamics and dynamics. In terms of thermodynamics, we demonstrate that the fastest error growth of PDO-related SST cold (warm) events during the ASO season is mainly due to the largest anomalous release (absorption) of the latent heat flux in this season; while for dynamics, the effect of the vertical gradient of climatological mean sea temperature on the anomalous upwelling (downwelling) dominates the contribution of the dynamical temperature advections to the error growth of the PDO-related SST cold (warm) events during the ASO season. The anomalous release (absorption) of the latent heat flux and anomalous upwelling (downwelling) of the ocean currents are both related to the anomalous northwesterly or cyclonic (southeasterly or anticyclonic) wind over the PDO-related SSTA region, which indicates that the error growth associated with the SPB of PDO-related SST cold (warm) events is mainly driven by anomalous wind stress. The error growth associated with the SPB for PDO-related SSTA may also explain why the SSTA in the Kuroshio–Oyashio Extension is much less predictable than in other regions of the North Pacific, as shown by some state-of-the-art climate models.