IRI ENSO Forecast
IRI Technical ENSO Update
Published: March 19, 2019
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-March 2019, weak to moderate strength El Niño SST conditions were observed in the NINO3.4 region. The February SST anomaly was 0.66 C, in the weak El Niño range, and for Dec-Feb it was 0.71 C, also indicative of a weak El Niño. 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 1.0 C, indicating weak/moderate El Niño conditions. Since late February, SSTs became more strongly positive in the east-central tropical Pacific, due in part to a downwelling Kelvin wave associated with a favorable MJO phase during recent weeks. Moreover, since late January, some important atmospheric variables finally became El Niño-like, including westerly low-level zonal wind anomalies and above-average convection near the dateline. Thus, the coupling of the atmosphere to the oceanic conditions commenced and continues to the present. The subsurface temperature anomalies across the eastern equatorial Pacific became more strongly above-average in February and continue to the present. These warmed waters at depth are extending to the surface, and presage likely continuation of above-average SST in the coming few months.
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 gave a 80% chance for El Niño for Mar-May, dropping to 60% for Jun-Aug. An El Niño advisory is in effect. The latest set of model ENSO predictions, from mid-March, now available in the IRI/CPC ENSO prediction plume, is discussed below. As of mid-March, 90 to 95% of the dynamical or statistical models predict El Niño conditions for the Mar-May through May-Jul seasons. After May-Jul, the percentage of models forecasting El Niño gradually decreases, dropping to 80% for Jul-Sep and to near 70% for Sep-Nov through Nov-Jan. No model predicts La Niña for any season.
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 near 0% from Mar-May through Jun-Aug, rising only to 5% by Sep-Nov and to 11% by Nov-Jan. Probabilities for neutral conditions begin at 6% for Mar-May, rise to 22% for Jun-Aug, and and then settle in the 25-30% range from Jul-Sep through Nov-Jan. Probabilities for El Niño begin at 94% for Mar-May, thereafter slowly declining to 83% for May-Jul, 69% for Aug-Oct, and near 60% for Oct-Dec and Nov-Jan. The failure to drop below 50% throughout 2019 suggests a possibility for a two-year El Niño event, but at this time, with the northern spring predictability barrier upon us, this idea is mainly speculative. 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 substantial tilt of the odds toward El Niño conditions from Mar-May through Jul-Sep 2019, becoming weaker but still at least 60% through the Nov-Jan season. Probabilities for La Niña are close to zero through Jul-Sep. 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.
IRI/CPC Mid-Month Model-Based ENSO Forecast Probabilities
Season |
La Niña |
Neutral |
El Niño |
MAM 2019 |
0% |
6% |
94% |
AMJ 2019 |
0% |
10% |
90% |
MJ 2019 |
0% |
17% |
83% |
JJA 2019 |
1% |
22% |
77% |
JAS 2019 |
2% |
25% |
73% |
ASO 2019 |
4% |
27% |
69% |
SON 2019 |
5% |
27% |
68% |
OND 2019 |
10% |
29% |
61% |
NDJ 2019 |
11% |
29% |
60% |