Skill of Multimodel ENSO Probability Forecasts

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Improved ensemble-mean forecasting of ENSO events by a zero-mean stochastic error model of an intermediate coupled model (2016, background): “These authors indicated that ENSO forecasts should be probabilistic and that ensemble forecasts must necessarily include some quantitative assessment of the model uncertainties (e.g., Mason and Mimmack 2002; Tippett and Barnston 2008).”
Toward an Improved Multimodel ENSO Prediction (2015, methodology): “…30 or fewer years of hindcast data are available, use of variable model weighting based on model hindcast skill has not been shown to result in higher cross-validated MME skill than equal weighting (Tippett and Barnston 2008; Peña and van denDool 2008; Barnston et al. 2012; DelSole et al. 2013).”
Ensemble flood forecasting: a review. (2009, methodology): “However, techniques to deal with the combination of models with different error structure have to be developed (see examples and discussions in Berliner and Kim, 2008; Bhowmik and Durai, 2008; Doblas-Reyes et al., 2005; Kantha et al., 2008; Ke et al., 2008; Krishnamurti et al., 1999, 2001; Tippett a”