Technical ENSO Update

20 December 2012

Recent and Current Conditions

Expected Conditions

What is the outlook for the ENSO status going forward? The most recent official diagnosis and outlook was issued earlier this month in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it stated the high likelihood of neutral ENSO condtions enduring through the first quarter of 2013, with probabilities of El Niño or La Niña each less than 30% through May-July 2013. The latest set of model ENSO predictions, from mid-December, is now available in the IRI/CPC ENSO prediction plume, discussed below. The current east-central tropical Pacific SSTs are in the warm half of the ENSO-neutral range (anomaly of 0 to 0.5 C) in most of the central and east-central Pacific, but slightly below average in the eastern portion of the basin. The NINO4 region, farther to the west, which was well above average during late northern summer and early autumn, has now returned to near average. Subsurface temperatures across the equatorial Pacific have decreased to near average in the upper part of the ocean from near the date line eastward. The thermocline depth along the equator is slightly above average in some portions of the tropical Pacific, but slightly below average at other longitudes. In the atmosphere, the basin-wide sea level pressure pattern (e.g. the SOI), low level zonal winds and anomalous convection have generally been near average, and this was even the case during the past late northern summer while the SSTs were at borderline El Niño levels, causing many to consider the total ENSO situation not consistent with the weak El Niño SST state. Lately the pattern of outgoing longwave radiation (OLR) has not exhibited enhanced convection near or east of the dateline, indicative of a neutral ENSO state.

As of mid-December, only 10-15% of the set of dynamical and statistical models models predicts El Niño SST conditions for the Dec-Feb 2012-13 season, and all but one of these predict neutral conditions by Jan-Mar season. For the Dec-Jan 2012-13 season, 12% of models indicate El Niño conditions, 4% indicate La Niña conditions, and 84% indicate neutral ENSO conditions. For Jan-Mar, 92% indicate neutral ENSO conditions, with 4% (i.e., 1 model) indicating each of the other two possibilities. At lead times of 3 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. For the Mar-May season, among models that do use subsurface temperature information, 95% predict ENSO-neutral SSTs, and 5% predict El Niño conditions. For all models, the probability for neutral ENSO conditions exceeds 90% from Jan-Mar until the longest lead time (Aug-Oct) (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 tallying method used above. This alternative method uses the mean of the predictions of all models on the plume, 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 El Niño at 5% for Dec-Feb 2012-13, 5% for Jan-Mar, and 8% for Feb-Apr 2013, rising to near 20% by Apr-Jun and remaining in the 20-25% range through Aug-Oct 2013. Model probabilities for ENSO-neutral conditions are 95% for Dec-Feb 2012-13, 94% for Jan-Mar, and 88% for Feb-Apr 2013, decreasing to below 60% beginning in May-Jul 2013. Probabilities for La Niña are near zero for Dec-Feb 2012-13, rising to 7% by Mar-May and in the 20-25% range for Jun-Aug through Aug-Oct 2013. In words, the models collectively favor neutral ENSO conditions quite strongly straight through to the second quarter of 2013. 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 10 months 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 25 or more models on the IRI/CPC plume describe, on average, maintenance of neutral ENSO conditions during the coming months, continuing through the first half of 2013. Uncertainty increases greatly from around the Mar-May 2013 season onward, when the probablilities for neutral ENSO somewhat decrease as probabilities for both El Niño or La Niña increase to approximately one-in-four. Following this latest model-based ENSO plume prediction, factors such as known specific model biases and recent changes that the models may have missed will be taken into account in the next official outlook to be generated and issued in early January by CPC and IRI, which will include some human judgement in combination with the model guidance.

See also: 

• Summary of model predictions