Abstract

Abstract The breeding method has been implemented in the NASA Global Modeling and Assimilation Office coupled general circulation model (CGCM) in its operational configuration in which ocean data assimilation is used to initialize the coupled forecasts. Bred vectors (BVs), designed to capture the dominant growing errors in the atmosphere–ocean coupled system, are applied as initial ensemble perturbations. The potential improvement for ensemble prediction is investigated by comparing BVs with the oceanic growing errors, estimated by the one-month forecast error from the nonperturbed forecast. Results show that one-month forecast errors and BVs from the NASA CGCM share very similar features: BVs are clearly related to forecast errors in both SST and equatorial subsurface temperature—in particular, when the BV growth rate is large. Both the forecast errors and the BVs in the subsurface are dominated by large-scale structures near the thermocline. Results suggest that the forecast errors are dominated by dynamically evolving structures related to the variations of the background anomalous state, and that their shapes can be captured by BVs, especially during the strong 1997/98 El Niño. Hindcast experiments starting from January 1997 with one pair of BVs achieve a significant improvement relative to the control (unperturbed) hindcast by capturing many important features of this event, including the westerly wind burst in early 1997.

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