Technical ENSO Update

15 December 2011

Recent and Current Conditions

Expected Conditions

What is the outlook for the ENSO status going forward? The official diagnosis and outlook was issued earlier this month in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion. Now that we have reached the middle of November, a new set of model ENSO predictions is available as shown in the IRI/CPC ENSO prediction plume, to be discussed below. The current La Niña SSTs and continued below average (but slightly weakened) subsurface temperatures across the equatorial Pacific imply a strong likelihood of maintaining at least weak La Niña conditions in the short term, with a chance for slightly further strengthening, during the coming month before beginning to weaken more steadily beginning in about February.

As of mid-November, most of the dynamical and statistical models predict La Niña conditions for the Dec-Feb season and for the subsequent seasons in early 2012. For the Dec-Feb season, 84% of the models indicate La Niña conditions, and 16% indicate neutral conditions. For Jan-Mar, these figures become 68% and 32%, respectively. At lead times of 4 or more months into the future, statistical and dynamical models that incorporate information about the ocean's observed subsurface thermal structure generally exhibit higher predictive skill than those that do not. Among models that do use subsurface temperature information, 67%  predict ENSO-neutral SSTs for the Apr-Jun 2012 season, 28% predict La Niña conditions, and 6% predict El Niño conditions. (Note 1). Caution is advised in interpreting the distribution of model predictions as the actual probabilities. At longer leads, the skill of the models degrades, and skill uncertainty must be convolved with the uncertainties from initial conditions and differing model physics, leading to more climatological probabilities in the long-lead ENSO Outlook than might be suggested by the suite of models.  Furthermore, the expected skill of one model versus another has not been established using uniform validation procedures, which may cause a difference in the true probability distribution from that taken verbatim from the raw model predictions.

An alternative way to assess the probabilities of the three possible ENSO conditions is more quantitatively precise and less vulnerable to sampling errors than the categorical counting method used above. This alternative method uses the mean of the predictions of all models, equally weighted, and constructs a standard error function centered on that mean. The standard error is Gaussian in shape, and has its width determined by an estimate of overall expected model skill for the season of the year and the lead time. Higher skill results in a relatively narrower error distribution, while low skill results in an error distribution with width approaching that of the historical observed distribution. This method shows probabilities for La Niña at 98% for Dec-Feb, decreasing to 86% for Jan-Mar, 63% for Feb-Apr, and down to 32% by Apr-Jun. Model probabilities for El Niño are near 0% for Dec-Feb through Feb-April and remain below 10% through Apr-Jun 2012. Probabilities for ENSO-neutral conditions are 2% for Dec-Feb and rise to 14% by Jan-Mar and more quickly thereafter, exceeding 50% beginning in Mar-May. A plot of the probabilities generated from this most recent IRI/CPC ENSO prediction plume using the multi-model mean and the Gaussian standard error method summarizes the model consensus out to about 3 seasons into the future. The same cautions mentioned above for the distributional count of model predictions apply to this Gaussian standard error method of inferring probabilities, due to differing model biases and skills. In particular, this approach considers only the mean of the predictions, and not the total range across the models, nor the ensemble range within individual models.

The probabilities derived from the more than 20 models on the IRI/CPC plume describe a dissipation of the La Niña during the northern spring 2012. Past experience has shown that some models are biased in the direction of prolonging ENSO episodes for somewhat too long a period at the end of the typical ENSO cycle. If such a bias exists in the present case, this weak to moderate La Niña may end in the February to April timeframe rather than the March to May timeframe as indicated by the models collectively. Factors such as known model biases and recent changes that the models may have missed are taken into account in the official outlook generated by IRI/CPC to be issued at the beginning of the next month.

See also: 

• Summary of model predictions