Best Practices for Estimating Forecast Uncertainty in Seasonal-to-Decadal Predictions

The proposal describes a systematic framework to recalibrate seasonal-to-decadal predictions, taking into account that predictions across these timescales carry various model biases, including probabilistic unreliability, unless they are recalibrated. The proposal intends to obtain estimates of forecast uncertainty that can be used to inform decisions such as planning and risk management. The group intends to demonstrate the benefit of recalibrating seasonal-to-decadal ensemble predictions and quantify how forecast performance depends on ensemble design and the choice of the recalibration scheme. They intend to illustrate with existing ensemble experiments how prediction centers can improve the reliability of their seasonal-to-decadal predictions, and add value to their products.The proposal is interesting and innovative, has clear impact for the IRI community and is expected to lead to three publications.