IRI ENSO Forecast
IRI Technical ENSO Update
Published: March 17, 2016
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 usually shows stronger anomalies than ERSSTv4, and during very strong events the two datasets may differ by as much as 0.5 C. Therefore, the anomalies cited below for this strong 2015-16 event are likely larger than those that will later be cited officially, particularly in comparisons with other strong El Niño events like 1982-83 and 1997-98.
Recent and Current Conditions
The SST anomaly in the NINO3.4 region has been at a strong El Niño level since around mid-July 2015. For February 2016 the average NINO3.4 SST anomaly was 2.40 C, indicative of strong El Niño conditions, and for Dec-Feb it was 2.61 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 1.8 C, in the category of strong El Niño. Accompanying this SST has been a clear and strong El Niño atmospheric pattern, including westerly low-level wind anomalies and positive anomalies of convection near and east of the dateline. The Southern Oscillation Index (SOI) and the equatorial SOI have also been negative, indicative of El Niño conditions.
Expected Conditions
What is the outlook for the ENSO status going forward? The most recent official diagnosis and outlook was issued one week ago in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it called for this strong El Niño to weaken, and return to neutral by late spring or early summer 2016, with about a 50% possibility for La Niña development by fall. The latest set of model ENSO predictions, from mid-March, now available in the IRI/CPC ENSO prediction plume, is discussed below. Currently, although the most recent Nino3.4 SST anomalies are in the strong El Niño category, subsurface temperature anomalies across the eastern equatorial Pacific have weakened substantially over the last few months and are only slightly above average. With the return toward average of the subsurface temperatures, the SST is poised to continue retreating toward average in the coming few months. During January, February and early March the SST anomalies have indeed been weakening, although not rapidly so far, and February’s SST anomaly is just over one-half degree weaker than the peak value in November. In the atmosphere, the basin-wide sea level pressure anomaly pattern (e.g. the SOI) has been clearly at El Niño levels, but with some fairly large week-to-week variations. Anomalous convection (as measured by OLR) has been above average near and somewhat east of the dateline, and in the latest month extended farther to the far eastern part of the basin but not to the extent observed during the 1997-98 event. Together, the oceanic and atmospheric features reflect continuing strong El Niño conditions for late February through mid-March.
As of mid-March, none of the dynamical or statistical models models predicts La Niña or neutral SST conditions for the initial Mar-May 2016 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 Jun-Aug 2016 season, among models that do use subsurface temperature information, about 30% predicts El Niño SST conditions, about 30% predicts ENSO-neutral conditions, and about 40% predicts La Niña conditions. For all model types, the probabilities for El Niño are near 100% (i.e., higher than 99.5%) for only Mar-May, and drop to about 80% by Apr-Jun, and less than 30% for the remainder of the seasons through Nov-Jan 2016-17. No model predicts La Niña conditions until May-Jul 2016, when the chance becomes just 4%, but the chances rise to just over 30% by Jun-Aug and to 50% or more beginning in Aug-Oct, reaching 60% or more for Oct-Dec and Nov-Jan 2016-17. Chances for neutral ENSO conditions rise to over 60% for May-Jul, and then fall back to about 40%, or lower, beginning in Jul-Sep and continuing through the remainder of the forecast period.
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-zero for Mar-May and Apr-Jun 2016, rising to near 40% by Jul-Sep and to near 50% by Nov-Jan 2016-17. Model probabilities for neutral ENSO conditions are near zero for Mar-May, rising to at least 60% for May-Jul and Jun-Aug, and then drop to 40% or less for Sep-Nov through Nov-Jan 2016-17. Probabilities for El Niño are near 100% for Mar-May 2016, near 80% for Apr-Jun, near 30% for May-Jul, and less than 20% from Jun-Aug through the final season of Nov-Jan 2016-17. 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, extremely high certainty for El Niño conditions for the Mar-May 2016 season, then promptly dropping thereafter. The models indicate weakening El Niño levels through spring, a return to neutral ENSO by early summer, and then suggest the possibility of La Nina development by autumn 2016. 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 October 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 |
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 |
MAM 2016 |
~0% |
~0% |
100% |
AMJ 2016 |
~0% |
20% |
80% |
MJJ 2016 |
4% |
65% |
31% |
JJA 2016 |
26% |
60% |
14% |
JAS 2016 |
40% |
49% |
11% |
ASO 2016 |
43% |
44% |
13% |
SON 2016 |
45% |
39% |
16% |
OND 2016 |
46% |
36% |
18% |
NDJ 2016 |
52% |
32% |
16% |