The NINO-34 ensemble forecast of EMR model is based on data from January 1950 through December 2018 (blue), and ensemble mean (red) predicts weak El-Niño conditions during winter 2018-19. The error bars (black) correspond to one standard deviation of the ensemble plume. You can also check a multi-model plume of Nino-34 forecasts from different statistical and dynamical models maintained by IRI, and compare predictions for the past 22 months, including also the UCLA-TCD model. IRI analysis of real-time 2002-2011 forecast skill of IRI multi-model plume of Nino-34 forecasts shows that UCLA-TCD model is highly competitive.
Kaplan, A., M. Cane, Y. Kushnir, A. Clement, M. Blumenthal,
and B. Rajagopalan, 1998:
Analyses of global sea-surface temperature 18561991.
J. Geophys. Res., 103, 18 56718 589.
Kravtsov S, Kondrashov D, Ghil M, 2005:
Multilevel regression modeling of nonlinear processes: Derivation and applications to climatic variability.
J. Climate, 18 (21): 4404-4424.
Kondrashov D, Kravtsov S, Robertson AW and Ghil M., 2005:
A hierarchy of data-based ENSO models .
J. Climate, 18 (21): 4425-4444.
Barnston, Anthony G., Michael K. Tippett, Michelle L. L'Heureux, Shuhua Li, David G. DeWitt, 2012: Skill of Real-Time Seasonal ENSO Model Predictions during 2002–11: Is Our Capability Increasing?. Bull. Amer. Meteor. Soc., 93, 631–651.