Technical ENSO Update

20 October 2011

Current Conditions

Expected Conditions

Presently, the models and observations taken together indicate probabilities of approximately 78% for maintaining at least weak La Niña conditions, 22% for returning to ENSO-neutral conditions, and near 0% for developing El Niño conditions, during the Oct-Dec 2011 season in progress. Probabilities for La Niña stay at 70% or higher through the Dec-Feb 2011/11 season. Probabilities for El Niño conditions remain below 10% through Feb-Apr 2012. La Niña conditions are the most likely scenario during the remainder of 2011 and into early 2012, although a return to neutral conditions during this time period also has a slight possibility. La Niña probabilities decrease to 51% by Feb-Apr 2012 before returning to the climatological value of 25% by the May-Jul season 2012. During the remainder of 2011, the probability for neutral conditions is at roughly 25%.

The above assessment was made in part on the basis of an examination of the current predictions of ENSO prediction models as well as the observed conditions. For purposes of this discussion, El Niño SST conditions are defined as SSTs in the NINO3.4 region being in the warmest 25% of their climatological distribution for the 3-month period in question over the 1950-present timeframe. The corresponding cutoff in terms of degrees C of SST anomaly varies seasonally, being close to 0.40 degrees C in boreal late-spring to early-summer season and as high as 0.75 degrees C in late boreal autumn. La Niña conditions are defined as NINO3.4 region SSTs being in the coolest 25% of the climatological distribution. Neutral conditions occupy the remaining 50% of the distribution. These definitions were developed such that the most commonly accepted El Niño and La Niña episodes are reproduced.

Even though La Niña conditions have already been observed for a few months, a slight majority of the dynamical and statistical models continue to forecast neutral ENSO conditions for the Oct-Dec season and for most of the subsequent seasons into early 2012. For both the Oct-Dec and Nov-Jan seasons, 40% of the models indicate La Niña conditions, and 60% indicate neutral conditions. For Dec-Feb, 48% show neutral conditions, 48% show La Niña conditions, and 4% show El Niño development. 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, 10 of 18 (56%)  predict ENSO-neutral SSTs for the Feb-Apr 2012 season, 7 of 18 (39%) predict La Niña conditions, and 1 of 18 (6%) predict El Niño conditions. (Note 1). (Note that La Niña conditions for Feb-Apr require a NINO3.4 SST anomaly of -0.45 or stronger, and El Niño conditions require 0.40 or stronger.) 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 to use the mean of the predictions of all models, and to construct a standard error function centered on that mean. The standard error would be Gaussian in shape, and would have its width determined by an estimate of overall expected model skill for the season of the year and the lead time. Higher skill would result in a relatively narrower error distribution, while low skill would result in an error distribution with width approaching that of the historical observed distribution. This method shows probabilities for La Niña at 41% for Oct-Dec, increasing to 50% for Dec-Feb and hovering between 46 and 51% into early 2012. Model probabilities for El Niño are near 0% for Nov-Jan and remain below 10% through Apr-Jun 2012. Probabilities for ENSO-neutral conditions are 59% for Oct-Dec and hover near 50% through Jan-Mar 2012, rising slightly toward 55% through northern spring 2012. The same cautions mentioned above for the distribution of model predictions apply to this alternative 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 range across the models, nor the ensemble range within individual models.

The IRI's probabilistic ENSO prediction takes into account the indications of this set of models, the outcome of the standard error approach described above, and additional factors such as the very latest observations that may have developed after the initialization times of some of the models. In the case of this forecast, the forecasters have increased the probability of continuation of La Niña above the levels indicated by the models, based on the recent and current La Niña observations and the increasing negative heat content anomaly in the central and eastern tropical Pacific. It indicates a 78% probability for La Niña conditions in the Oct-Dec season in progress, dropping slowly to 70% by Dec-Feb 2011-12 and to 51% by Mar-May 2012. Probabilities for ENSO-neutral conditions are between 22% and 29% through Dec-Feb 2011-12, rising to 50% or higher from Mar-May 2012 onward. This indicates that continuation of La Niña is more likely than neutral conditions until early 2012, and that a return to neutral conditions during the remainder of 2011, while possible, is relatively less likely than persistence of at least weak La Niña conditions. Probabilities for El Niño conditions do not rise to 5% until Feb-Apr 2012, and remain below 10% until Mar-May 2012.

See also: 

• Summary of model predictions