Following strong westerly wind bursts in boreal winter and spring of 2014, both the scientific community and the popular press were abuzz with the possibility of a major El Niño developing. However, during the boreal summer of 2014, the Bjerknes feedback failed to kick in, aided and abetted by a strong easterly wind burst. The widely anticipated major 2014–2015 El Niño event failed to materialize and even failed to qualify as an El Niño by conventional definitions. However, the boreal summer easterly wind burst had the effect of not only inhibiting the growth of the El Niño event but also preventing and then reversing the discharge of the equatorial heat content that typically occurs during the course of an El Niño event. This head start of equatorial heat content helped push the 2015–2016 El Niño event to extreme magnitude.
current predictive skill is also needed. Improving predictions and projections requires improvements in the quality, quantity, and length of instrumental and paleoclimate records, in the performance of climate models and data assimilation methods used to make predictions.
The spring predictability barrier increases the uncertainty in ENSO forecasts starting before and during the boreal spring. Recent work has shown that the annual cycle of ENSO growth rate is responsible for phase locking of peak ENSO development to the boreal winter, suggesting that this annual cycle may play a role in the spring predictability barrier. To test this hypothesis, the annual cycle of ENSO growth rate is added to a damped, noise‐driven conceptual recharge oscillator model. When the annual cycle of ENSO growth rate is included, a spring predictability barrier develops, whereas without it ENSO predictability is independent of the forecast start date. When state‐dependent noise is included in the simulations in addition to the annual cycle of the growth rate, the spring predictability barrier is enhanced and more realistic.
The conceptual El Niñ o-Southern Oscillation (ENSO) recharge oscillator model is used to study the linear stability of ENSO under state-dependent noise forcing. The analytical framework developed by Jin et al. is extended to more fully study noise-induced instability of ENSO. It is shown that in addition to the noise-induced positive contribution to the growth rate of the ensemble mean (first moment) evolution of the ENSO cycle, there is also a noise-induced instability for the ensemble spread (second moment). These growth rates continue to increase as the strength of the multiplicative noise increases. In both the analytical solution and the numerical model, the criticality threshold for instability of the second moment occurs at a lower value of the parameter that measures multiplicative forcing than the threshold for the first moment. The noise-induced instability not only enhances ENSO activity but also results in a large ensemble spread and thus may reduce the effectiveness of ENSO prediction. As in the additive noise forcing case, the low-frequency variability in the forcing is the important part for forcing El Niñ o events and the high-frequency forcing alone cannot effectively excite ENSO.
Multidecadal shifts in El Niño–Southern Oscillation (ENSO) variability have been observed, but it is unclear if this variability is just a random variation in the ENSO cycle or whether it is forced by other modes of climate variability. Here we show a strong influence of the Atlantic on the multidecadal variability of ENSO. The Atlantic Multidecadal Oscillation (AMO) is the dominant mode of multidecadal sea surface temperature (SST) variability in the Atlantic Ocean. Changes in AMO‐related tropical Atlantic SSTs are known to force changes in the Walker circulation in the tropical Pacific Ocean. Using conceptual and coupled model experiments, we show that these changes to the Walker circulation modify ENSO stability on both annual and multidecadal time scales leading to a distinctive pattern of multidecadal ENSO variability that we find in observations and ocean reanalyses.
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