IRI ENSO Forecast
IRI Technical ENSO Update
Published: August 20, 2018
Note: The SST anomalies cited below refer to the OISSTv2 SST data set, and not ERSSTv4. OISSTv2 is often used for real-time analysis and model initialization, while ERSSTv4 is used for retrospective official ENSO diagnosis because it is more homogeneous over time, allowing for more accurate comparisons among ENSO events that are years apart. During ENSO events, OISSTv2 often shows stronger anomalies than ERSSTv4, and during very strong events the two datasets may differ by as much as 0.5 C. Additionally, the ERSSTv4 may tend to be cooler than OISSTv2, because ERSSTv4 is expressed relative to a base period that is updated every 5 years, while the base period of OISSTv2 is updated every 10 years and so, half of the time, is based on a slightly older period and does not account as much for the slow warming trend in the tropical Pacific SST.
Recent and Current Conditions
In mid-August 2018, the NINO3.4 SST anomaly showed neutral ENSO conditions. For July the SST anomaly was 0.30 C, indicating neutral conditions, and for May-Jul it was 0.12 C, also neutral. 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 anomaly in the Nino3.4 region was 0.2, showing neutral conditions. Additionally, most of the key atmospheric variables, including the upper level zonal wind anomalies, the outgoing longwave radiation pattern (convection), and the Southern Oscillation Index suggest neutral conditions over recent weeks. However, during the most recent week the low-level zonal wind anomalies have become fairly strongly westerly. The subsurface temperature anomalies across the eastern equatorial Pacific remain at moderately above-average, and have already been impacting the surface, resulting in slightly above-average temperatures, and also presaging further warming of the SST in the coming months. Given the current and recent SST anomalies, the subsurface profile and the conditions of most key atmospheric variables, we will likely remain in an ENSO-neutral stste at least through the remainder of the Northern Hemisphere summer, with a chance for a warming leading to El Niño development beginning in September.
Expected Conditions
What is the outlook for the ENSO status going forward? The most recent official diagnosis and outlook was issued approximately one week ago in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it stated that ENSO-neutral is expected to continue during the rest of this summer, with about a 60% chance for El Niño during autumn, rising to about 70% for winter. An El Niño watch remains active. The latest set of model ENSO predictions, from mid-August, now available in the IRI/CPC ENSO prediction plume, is discussed below. Those predictions also suggest that the SST is likely to remain in the ENSO-neutral range only until around the Aug-Oct season, when El Niño development is at least 50% likely, rising to higher levels later in the year.
As of mid-July, about 35-40% of the dynamical or statistical models predict neutral conditions for the initial Aug-Oct 2018 season, with about 60-65% showing El Niño conditions. Over the course of the rest of 2018, probabilities for neutral drop to roughly the 5-25% range for Sep-Nov 2018 through Apr-Jun 2019. Meanwhile, the probability for El Niño rises to roughly 75% to 92% for Sep-Nov through Apr-Jun, being highest at 92% for Oct-Nov and Nov-Jan. La Niña probabilities are near zero throughout the forecast period. 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 Nov-Jan 2018-19 season, among models that do use subsurface temperature information, about 10% of models predicts neutral conditions and about 90% predict El Niño conditions.
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 the full range of seasons from Aug-Oct 2018 through to Apr-Jun 2019. Probabilities for neutral conditions begin at 49% for Aug-Oct, fall to 34% for Sep-Nov and to 20-25% from Nov-Jan through Mar-May. Meanwhile, the probabilities for El Niño, which begin at 51% for Aug-Oct, rise to 65% for Sep-Nov and rise further to 70-75% for Oct-Dec to Jan-Mar and 75-80% for Feb-Apr and 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 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.
In summary, the probabilities derived from the models on the IRI/CPC plume describe, on average, approximately even chances for ENSO-neutral or El Niño for Aug-Oct, followed by a tilt of the odds toward El Niño conditions starting in Sep-Nov and increasing to 70% or higher by late 2018 through spring 2019. Probabilities for La Niña are less than 5% throughout the entire forecast period. 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 early next month by CPC and IRI, which will include some human judgment in combination with the model guidance.
Climatological Probabilities
Season |
La Niña |
Neutral |
El Niño |
DJF |
36% |
30% |
34% |
JFM |
34% |
38% |
28% |
FMA |
28% |
49% |
23% |
MAM |
23% |
56% |
21% |
AMJ |
21% |
58% |
21% |
MJJ |
21% |
56% |
23% |
JJA |
23% |
54% |
23% |
JAS |
25% |
51% |
24% |
ASO |
26% |
47% |
27% |
SON |
29% |
39% |
32% |
OND |
32% |
33% |
35% |
NDJ |
35% |
29% |
36% |
IRI/CPC Mid-Month Model-Based ENSO Forecast Probabilities
Season |
La Niña |
Neutral |
El Niño |
ASO 2018 |
0% |
49% |
51% |
SON 2018 |
1% |
34% |
65% |
OND 2018 |
2% |
27% |
71% |
NDJ 2018 |
2% |
24% |
74% |
DJF 2019 |
2% |
24% |
74% |
JFM 2019 |
1% |
24% |
75% |
FMA 2019 |
0% |
22% |
78% |
MAM 2019 |
0% |
22% |
78% |
AMJ 2019 |
0% |
30% |
70% |