A set of 44‐year seasonal ensemble coupled model forecasts performed with annually updated greenhouse gas concentrations is compared to a standard seasonal ensemble forecast experiment performed with fixed concentrations. The former shows more realistic temperature variability and better forecast quality. The improvement in model variability is due to a better simulation of climate trends and suggests that realistic initial conditions are not enough to reproduce this long‐term variability. The better probabilistic forecast quality is mostly due to the increased ability to reliably discriminate the occurrence of events and non‐events. These results are relevant for the improvement of operational seasonal forecasts and provide new evidence of the effects of anthropogenic changes in atmospheric composition.
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Doblas‐Reyes et al. (2006) studied this question.
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