IRI ENSO Forecast
IRI Technical ENSO Update
Published: May 21, 2015
Recent and Current Conditions
The SST anomaly in the NINO3.4 region has been at a weak El Niño level from late February through mid-May 2015. For April the average NINO3.4 SST anomaly was 0.78 C, indicative of weak Niño conditions, and for Feb-Apr it was 0.64 C. The IRI’s definition of El Niño, like NOAA/Climate Prediction Center’s, requires that the SST anomaly in the Nino3.4 region (5S-5N; 170W-120W) exceed 0.5 C. Similarly, for La Niña, the anomaly must be -0.5 C or less. The climatological probabilities for La Niña, neutral, and El Niño conditions vary seasonally, and are shown in a table at the bottom of this page for each 3-month season. The most recent weekly SST anomaly in the Nino3.4 region was 1.0 C, in the category of weak to low-moderate El Niño. Accompanying this SST has been an atmospheric pattern with supporting indications of an El Niño condition, including westerly low-level wind anomalies and positive anomalies of convection in the vicinity of the dateline. The Southern Oscillation Index (SOI) and the equatorial SOI have also been indicative of at least weak El Niño 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 called for an approximately 90% likelihood for El Niño conditions continuing through summer 2015, and at least 80% to last through the duration of 2015. The latest set of model ENSO predictions, from mid-May, now available in the IRI/CPC ENSO prediction plume, is discussed below. Currently, Nino3.4 SST anomalies are in the weak to moderate El Niño cagtegory. Subsurface temperature anomalies across the eastern equatorial Pacific have been well above average levels during the past 3 months as the downwelling phase of a Kelvin wave has moved eastward at depth in response to westerly low-level wind anomalies during the last 3 to 4 months. The positive heat content anomaly has promoted increases in SST over the last month, and is likely to lead to further SST increases in the coming few months, depending on the strength and nature of the atmospheric response to the El Niño. The subsurface heat content, while still substantially above average, has begun decreasing as it has been discharging in the form of far above average SST in the far eastern tropical Pacific. In the atmosphere, the basin-wide sea level pressure anomaly pattern (e.g. the SOI) has been at El Niño levels, and anomalous convection (as measured by OLR) has been above average near the dateline. Together, the oceanic and atmospheric features reflect the weak to moderate El Niño condition during late April and through mid-May.
As of mid-April, none of the dynamical or statistical models models predicts La Niña or neutral SST conditions for the initial May-Jul 2015 season; 100% predicts El Niño conditions. 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 Aug-Oct 2015 season, among models that do use subsurface temperature information, 95% predicts El Niño SST conditions, 5% predicts ENSO-neutral conditions and none predicts La Niña conditions. For all model types, the probabilities for El Niño are 96% for Jun-Aug, 84% for Jul-Sep, and 88-94% from Aug-Oct through to the beginning of 2016. No models predict La Niña conditions for any forecast period during 2014. Aside from May-Jul and Jun-Aug, when 100% and 96% of models predict El Niño SST conditions, respectively, the season having highest probability for El Niño SST conditions is Dec-Feb 2015-16, when the probability is 94%. (Note that at that long lead time, some of the models do not make forecasts, leaving a smaller set of models.)
Note – Only models that produce a new ENSO prediction every month are included in the above statement.
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 La Niña at 2% or less for all periods from May-Jul through Jan-Mar 2015. Model probabilities for neutral ENSO conditions are less than 10% for May-Jul and Jun-Aug, rising to 10-15% from Jul-Sep through Sep-Nov, and first exceeding 20% for Jan-Mar 2016. Probabilities for El Niño are 90% or higher from May-Jul to Jul-Sep, 85-89% for Aug-Oct and Sep-Nov 2015, dropping below 80% for the first time by Dec-Feb 2015-16. 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 models on the IRI/CPC plume describe, on average, very high certainty for El Niño conditions for the May-Jul and Jun-Aug seasons, and still high certainty through Sep-Nov. In terms of magnitude, the models suggest strengthening El Niño conditions through northern autumn season, reaching at least moderate strength. However, model spread is high, reflecting the continued presence of the northern spring ENSO predictability barrier. A caution regarding this latest set of model-based ENSO plume predictions, is that 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 March by CPC and IRI, which will include some human judgement in combination with the model guidance.
Climatological Probabilities
| Season |
La Niña |
Neutral |
El Niño |
| DJF |
37% |
28% |
35% |
| JFM |
34% |
37% |
29% |
| FMA |
30% |
48% |
22% |
| MAM |
26% |
54% |
20% |
| AMJ |
24% |
54% |
22% |
| MJJ |
25% |
51% |
24% |
| JJA |
25% |
50% |
25% |
| JAS |
27% |
46% |
27% |
| ASO |
29% |
40% |
31% |
| SON |
32% |
34% |
34% |
| OND |
34% |
31% |
35% |
| NDJ |
37% |
27% |
36% |
IRI/CPC Mid-Month Plume-Based ENSO Forecast Probabilities
| Season |
La Niña |
Neutral |
El Niño |
| MJJ 2015 |
~0% |
3% |
97% |
| JJA 2015 |
~0% |
7% |
93% |
| JAS 2015 |
~0% |
10% |
90% |
| ASO 2015 |
1% |
11% |
88% |
| SON 2015 |
1% |
12% |
87% |
| OND 2015 |
2% |
16% |
82% |
| NDJ 2015 |
2% |
16% |
82% |
| DJF 2015 |
2% |
19% |
79% |
| JFM 2016 |
2% |
23% |
75% |
