IRI ENSO Forecast
IRI Technical ENSO Update
Published: February 19, 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-February 2018, the NINO3.4 SST anomaly was in the upper portion of the weak La Niña range. For January the SST anomaly was -0.75 C, indicating weak La Niña, and for November-January it was -0.79 C, also in that range. 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 -0.9, showing weak La Niña but not far from the borderline of moderate La Niña. The pertinent atmospheric variables, including the lower level zonal wind anomalies, the Southern Oscillation Index and the anomalies of outgoing longwave radiation (convection), have been showing patterns suggestive of La Niña, although the Southern Oscillation has been weak and variable and the enhanced trade winds in the western Pacific have ceased. Subsurface temperature anomalies across the eastern equatorial Pacific, while recently weakening significantly, are also still mildly negative and not inconsistent with a La Niña nearing the end of its duration. Given the current and recent SST anomalies, the subsurface profile and the La Niña patterns in most key atmospheric variables, it appears we are in the later stage of a weak (but nearly moderate) La Niña.
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 the La Niña is likely to transition to ENSO-neutral during spring. A La Niña Advisory was once again issued with that Discussion. The latest set of model ENSO predictions, from mid-February, now available in the IRI/CPC ENSO prediction plume, is discussed below. Those predictions suggest that the SST is likely to remain in the weak La Niña range just for the February-April season, followed by a likely return to neutral starting with the March-May season.
As of mid-February, about 60% of the dynamical or statistical models predicts La Niña conditions for the initial Feb-Apr 2018 season, dropping to only around 25% for Mar-May and Apr-Jun. 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 May-Jul 2018 season, among models that do use subsurface temperature information, about 75% of models predicts neutral conditions and about 15% predicts La Niña conditions. For all models, starting with the second lead time of Mar-May 2018 and lasting through most of the forecast range, predictions for ENSO-neutral conditions have more than a 50% probability, with probabilities peaking around 75-80% for May-Jul. However, near the end of the forecast range, Sep-Nov and Oct-Dec, the probability for El Niño rises to over 40% and La Niña probabilities are only about 10%, leaving only about 45% for neutral.
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 about 55% for Feb-Apr, dropping to near 35% for Mar-May, and decreasing thereafter to less than 20% for Apr-Jun through Oct-Dec. Probabilities for neutral conditions begin around 45% for Feb-Apr, rise to a peak around 80% for Apr-Jun, after which they drop to about 50% for Jul-Sep and to about 40% or less for Aug-Oct to Oct-Dec as El Niño probabilities rise, reaching nearly 50% by Oct-Dec. 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, a slight preference for weak La Niña conditions for Feb-Apr 2018, followed by the period from Mar-May through Jun-Aug with neutral having more than a 50% chance. Chances for El Niño are small through May-Jul 2018, rising to near 35% for Jul-Sep and nearly 50% by the final period of Oct-Dec. 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 |
| FMA 2018 |
52% |
48% |
0% |
| MAM2018 |
31% |
69% |
0% |
| AMJ 2018 |
17% |
81% |
2% |
| MJJ 2018 |
16% |
68% |
16% |
| JJA 2018 |
15% |
56% |
29% |
| JAS 2018 |
14% |
49% |
37% |
| ASO 2018 |
15% |
42% |
43% |
| SON 2018 |
18% |
37% |
45% |
| OND 2018 |
18% |
33% |
49% |
