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ENSO Forecast

May 2026 Quick Look

Published: May 19, 2026

A monthly summary of the status of El Niño, La Niña, and the Southern Oscillation, or ENSO, based on the NINO3.4 index (120-170W, 5S-5N)

As of mid-May 2026, the equatorial Pacific is rapidly transitioning into El Niño conditions. While monthly SST anomalies remain near the borderline El Niño threshold, weekly values have surged well above it, with the last three weekly pentads firmly reaching +0.9 °C in the Niño3.4 region. This sharp warming strongly indicates that the currently near neutral seasonal averages will rise substantially in the coming months, marking a clear shift from ENSO neutral to El Niño conditions. The latest CCSR/IRI ENSO plume forecast further supports this evolution, assigning a 98% probability to El Niño during May–July 2026 compared to only 2% for continued neutrality. El Niño conditions are then likely to persist through the remainder of 2026, with forecast probabilities consistently maintained within a remarkably high and narrow 97–98% range.

Figures 1 ((the official CPC ENSO probability forecast) and 3 (the objective model-based IRI ENSO probability forecast) are often quite similar. However, occasionally they may differ noticeably. There can be several possible reasons for differences. One is the human forecasters, using their experience and judgment, may disagree to some degree with the models, which may have known biases. Another reason is the models are not run at the same time that the forecasters make their assessment, so that the starting ENSO conditions may be slightly different between the two times. The charts on this Quick Look page are updated at two different times of the month, typically about a week apart, with the IRI forecast run later. Also note that the CPC forecast starts on the previous season while the IRI forecast starts on the current season.
Click on the for more information on each figure.

Historically Speaking

Tend to reach their maximum strength during October - February
Typically persist for 9-12 months, though occasionally persisting for up to 2 years
Typically recur every 2 to 7 years

IRI ENSO Forecast

IRI Technical ENSO Update and Model-Based Probabilistic ENSO Forecast

Published: May 19, 2026

Note: The SST anomalies cited below refer to the OISSTv2 SST data set, and not ERSSTv5. OISSTv2 is often used for real-time analysis and model initialization, while ERSSTv5 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. These two products may differ, particularly during ENSO events. The difference between the two datasets may be as much as 0.5 °C. Additionally in some years, the ERSSTv5 may tend to be cooler than OISSTv2 in the context of warming trends, because ERSSTv5 is expressed relative to a base period that is updated every 5 years, while the base period of OISSTv2 is updated every 10 years. In February 2021, both datasets were updated to reflect the 1991-2020 climatology period.

Recent and Current Conditions

The observed sea-surface temperature (SST) anomaly in the NINO3.4 region was +0.1 °C during the February–April 2026 season, increasing to +0.47 °C in April 2026. The latest weekly NINO3.4 index, centered on May 13, 2026, reached +0.9 °C. Together, these values suggest that Pacific Ocean conditions are currently near the El Niño threshold and are strengthening rapidly toward a developing El Niño event. The CCSR/IRI’s definition of El Niño, requires that the monthly SST anomaly in the NINO3.4 region (5°S-5°N; 170°W-120°W) exceed +0.5 °C. Similarly, for La Niña, the anomaly must be -0.5 °C or colder.

Both oceanic and atmospheric indicators are now beginning to align, pointing to a rapid transition from ENSO neutral conditions toward a developing El Niño state. On the atmospheric side, the Southern Oscillation Index (SOI) fell to -11.2 in April 2026, while the latest 30-day SOI value through 16 May remained strongly negative at -11.1, reflecting a clear weakening of the Walker circulation consistent with El Niño development. In addition, the Equatorial SOI declined to -0.3 during April 2026, further indicating that the atmosphere is starting to respond to the warming Pacific Ocean, a sign that ocean-atmosphere coupling associated with El Niño is becoming established. In parallel, there are early but still uncertain indications of reduced trade wind strength and subtle changes in cloudiness across the equatorial Pacific. A sustained weakening of the trade winds would likely accelerate the development and intensification of El Niño conditions, whereas a strengthening of the trades would act in the opposite direction and could slow or disrupt further evolution at this early stage. Further, the subsurface temperature structure in the central–eastern equatorial Pacific shows a pronounced and noteworthy warming signal. Between approximately 150°W and 80°W, temperatures at depths of 50–150 meters have increased substantially, with anomalies locally reaching up to 6°C. This represents a significant reservoir of subsurface heat that could act as a critical energy source for the further development and intensification of El Niño conditions, provided that atmospheric coupling remains favorable. In addition, the ocean heat content anomaly (averaged over 0–300 meters depth) between the Date Line and 80°W is also markedly elevated. For context, current values are more than twice those observed during the same period in mid-May 2023 (during the El Niño event of 2023).

Expected Conditions

Note – Only models that produce a new ENSO prediction every month are considered in this statement.

The mid-May 2026 ENSO prediction plume from CCSR/IRI has now been updated with the latest model forecasts. These are used to assess the probabilities of the three ENSO categories by using the average value of the NINO3.4 SST anomaly predictions from all models in the plume, equally weighted. A standard Gaussian error is imposed over that averaged forecast, with 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.

The May 2026 CCSR/IRI ENSO plume forecast paints a strikingly confident El Niño outlook, with probabilities peaking at 98% for May–July (MJJ) 2026 and remaining exceptionally high at 97–98% throughout the forecast period (MJJ 2026 to JFM 2027). ENSO-neutral conditions are reduced to a mere 2–3%, while the probability of La Niña development is effectively zero. Although the May 2026 ENSO forecasts indicate exceptionally high confidence in El Niño development, with probabilities remaining remarkably elevated throughout the forecast period, caution is still advised when interpreting these longer-range outlooks. The forecasts are being issued near the end of the boreal spring predictability barrier, a time of year historically associated with lower ENSO forecast skill, meaning some uncertainty remains despite the very strong probabilistic signal. A plot of the probabilities summarizes the forecast evolution. The climatological probabilities for La Niña, ENSO-neutral, and El Niño conditions vary seasonally, and are shown by the lines on the plot, and are given in a table at the bottom of this page for each 3-month season.

Caution is also advised in interpreting the forecast distribution from the Gaussian standard error as the actual probabilities, due to differing biases and performance of the different models. 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. At longer leads, the skill of the models degrades, and uncertainty in skill must be convolved with the uncertainties from initial conditions and differing model physics, which leads 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.

ENSO Forecast

IRI ENSO Predictions Plume

Published: May 19, 2026

Note on interpreting model forecasts

The following graph and table show forecasts made by dynamical and statistical models for SST in the Nino 3.4 region for nine overlapping 3-month periods. Note that the expected skills of the models, based on historical performance, are not equal to one another. The skills also generally decrease as the lead time increases. Thirdly, forecasts made at some times of the year generally have higher skill than forecasts made at other times of the year--namely, they are better when made between June and December than when they are made between February and May. Differences among the forecasts of the models reflect both differences in model design, and actual uncertainty in the forecast of the possible future SST scenario.

Interactive Chart

You can highlight a specific model by hovering over it either on the chart or the legend. Selecting an item on the legend will toggle the visibility of the model on the page. You can also select DYN MODELS or STAT MODELS to toggle them all at once. Clicking on the "burger" menu above the legend will give you options to download the image or expand to full screen. If you have any feedback on this new feature, please let us know at webmaster@iri.columbia.edu.

List of Models Used

Discussion of Current Forecasts

The multimodel mean of statistical and dynamical ENSO forecasts indicates a very high likelihood of El Niño duringMay–July 2026, with probabilities reaching 98%, compared to only 2% for continued ENSO neutral conditions. El Niño remains the dominant ENSO phase throughout the remainder of 2026 and into early 2027, with forecast probabilities consistently maintained within a remarkably elevated and narrow 97–98% range. Despite this exceptionally strong model consensus, some caution is still warranted, as the current forecasts are being issued near the end of the boreal spring predictability barrier period in May, when ENSO forecast uncertainty can still remain elevated. Based on the multi-model mean (Dynamical and Statistical models) prediction, and the expected skill of the models by start time and lead time, the probabilities (in %) for La Niña, ENSO-neutral and El Niño conditions (using -0.5 °C and 0.5 °C thresholds) over the coming 9 seasons are:

Summary of forecasts issued over last 22 months

The following interactive plot shows the model forecasts issued not only from the current month (as in the plot above), but also from the 21 months previous to this month. The observations are shown up to the most recently completed 3-month period. The plots allow comparison of plumes from the previous start times, or examination of the forecast behavior of a given model over time.
Hovering over any single model will highlight that particular model in the chart.
Clicking a particular model will hide/show that model in the chart.
At the bottom of the plot, you can select which models to show in the chart: all the models, the dynamical models only, or the statistical models only.

Notes on the data

Only models producing forecasts on a monthly basis are included. This means that some models whose forecasts appear in the Experimental Long-Lead Forecast Bulletin (produced by COLA) do not appear in the table.

Once an IRI ENSO probability forecast has been published, the results stand even if a model reports an error and changes their data. When this happens we will update the plume with the model's correct values even though our forecast hasn't changed. What this means is that our forecast is always the same, but the underlying data may be different from what we based our forecast on.

The SST anomaly forecasts are for the 3-month periods shown, and are for the Nino 3.4 region (120-170W, 5N-5S). Often, the anomalies are provided directly in a graph or a table by the respective forecasting centers for the Nino 3.4 region. In some cases, however, they are given for 1-month periods, for 3-month periods that skip some of the periods in the above table, and/or only for a region (or regions) other than Nino 3.4. In these cases, the following means are used to obtain the needed anomalies for the table:

Temporal averaging
Linear temporal interpolation
Visual averaging of values on a contoured map

The anomalies shown are those with respect to the base period used to define the normals, which vary among the groups producing model forecasts. They have not been adjusted to anomalies with respect to a common base period. Discrepancies among the climatological SST resulting from differing base periods may be as high as a quarter of a degree C in the worst cases. Forecasters are encouraged to use the standard 1991-2020 period as the base period, or a period not very different from it.

ENSO Forecast

Forecast Probability Distribution Based on the IRI ENSO Prediction Plume

Published: May 19, 2026

The plots on this page show predictions of seasonal (3-month average) sea surface temperature (SST) anomaly in the Niño3.4 region in the east-central tropical Pacific (5°N-5°S, 120°-170°W), covering the nine overlapping seasons beginning with the current month. The predictions are based on the large (20+) set of dynamical and statistical models in the plume of model ENSO predictions.

Figure 5

Predictions of ENSO are probabilistic. The ensemble mean prediction is only a best single guess. On either side of that prediction, there is a substantial uncertainty distribution, or error tolerance. The second plot (Figure 2) shows the estimated probability distribution of the predictions, showing a set of percentiles within that distribution for each lead time. The distribution is modeled as a normal (Gaussian) distribution, so that the overall mean forecast represents the center, or 50 percentile, in the distribution. The overall mean is formed using equal weighting among all models. On either side, other percentile values are shown symmetrically, ranging from 1 to 99 and including some intermediate percentiles (5 and 95, 15 and 85, and 25 and 75). The plot enables a user to estimate the probability of the Niño3.4 SST anomaly to be greater or less than some critical value, or within some interval. If, for example, the 85 percentile falls at 1.8° C above average, the probability of the SST exceeding 1.8° C can be estimated at 15%. Probabilities for exceeding or not exceeding values not exactly on percentile line can be roughly interpolated by eye. The overall width of the probability distribution is derived from the historical skill of the hindcasts of the models, from 1982 to present, for the specific forecast start time and lead time. This method of defining the probability distribution represents one of two general approaches, the other approach being a direct counting of ensemble members within each of the percentile bands. This second approach assumes that the ensemble spreads of the models are true representations of the uncertainty. Individual model spreads have often been found to be somwehate narrower than they should be, although in multi-model ensembles this tendency has been shown to be milder or even eliminated.
Figure 6

Figure 6, sometimes called a spaghetti diagram, shows synthetically generated prediction scenarios that are equally likely. Here, 100 scenarios are shown; any number can be generated for such a diagram. Each scenario is produced using a random number generator, combined with knowledge of the mean forecast and its uncertainty, as well as the amount of persistence of anomalies. The degree of persistence of anomalies is based on the correlation of prediction errors from one lead time to another. In other words, the individual lines are designed to show the correct amount of persistence as expected in nature, rather than jumping around more randomly from one lead time to the next. The uncertainty and persistence statistics are based on the set of 7 NMME (North American Multimodel Ensemble) models, as it is assumed that these statistics are approximately applicable to all of the models. Sometimes the “spaghetti density” may appear asymmetric about the mean of all the forecasts or outside of the 85 and 15 percentile lines. This is purely sampling variability, and would not occur if many thousands of such lines were plotted. But with that many lines, most of the plot would be too crowded to get a sense of the behavior of the lines near the center of the distribution. The main purpose of the diagram is to serve users who want to assess realistic individual scenarios of ENSO behavior rather than statistical summaries of the forecast like the percentiles shown in the second plot.

IOD Forecast

Published: May 19, 2026

Note: The Dipole Mode Index is calculated based on the ERSSTv5 data. To account for evolving background conditions and long-term warming, SST anomalies were calculated relative to a sliding monthly climatology. For each month in the time series, the climatology was computed as the mean SST for that calendar month over the prior 30 years. The Dipole Mode Index (DMI) is then defined as the difference in sea surface temperature anomalies between the western equatorial Indian Ocean (50°E–70°E, 10°S–10°N) and the southeastern equatorial Indian Ocean (90°E–110°E, 10°S–0°), and is used to quantify the strength and phase of the Indian Ocean Dipole (IOD).

Current Conditions

In April 2026, the observed Dipole Mode Index was +0.31 °C, indicating neutral IOD conditions across the Indian Ocean. According to the CCSR/IRI’s criteria for defining positive and negative Indian Ocean Dipole (IOD) events, a positive IOD phase is defined when the DMI exceeds +0.4 °C, and a negative IOD when it falls below −0.4 °C. The IOD is considered inactive (neutral) when the DMI lies between −0.4 °C and +0.4 °C.

Model-Based IOD Outlook: Deterministic Forecasts from the NMME

Forecasts from the latest set of operational models in the North American Multi-Model Ensemble (NMME) project are used to construct deterministic IOD forecasts from each individual model using its ensemble mean DMI to form an IOD forecast plume. The IOD plume plot shows the latest set of predictions from CESM1, CFSv2, CanESM5, GEM-NEMO, and NASA along with their equally weighted multi-model mean (MME). Observations show that the DMI (shown in black) rose steadily from its negative-phase peak in October 2025, gradually weakening through late 2025 and returning to neutral IOD conditions by February 2026. Neutral conditions persist from January through April 2026. Forecasts indicate that the IOD will remain neutral during May and June 2026, with a gradual tendency toward positive IOD conditions. By July 2026, three out of five models exceed the positive IOD threshold and remain in positive territory through the end of the forecast period in November 2026. The multi-model ensemble also indicates a shift to positive IOD conditions from July 2026 onward, persisting through August, September, October, and November 2026.

Probabilistic IOD Forecasts from the NMME

Based on May 2026 initialization data, the model-based probabilistic forecast of the Indian Ocean Dipole was generated by CCSR/IRI to assess potential phase developments. Probabilities are computed using an ensemble-member counting method, where all ensemble members from the contributing models combined (62 in all), are pooled to determine the likelihood of a negative, neutral, or positive IOD phase for the upcoming months. Climatological probabilities for each IOD phase, based on historical data, are shown as dotted lines for reference. In May and June 2026, neutral IOD conditions dominate, while the likelihood of positive IOD increases from ~5% in May to ~22% in June. From July through November, the probability of positive IOD continues to rise to over 80% by September, while neutral conditions decline to less than 10%. Probabilities of the negative IOD phase remain negligible throughout the forecast period. This transition from neutral toward positive IOD is broadly consistent with the CCSR/IRI ENSO outlook, which indicates a persistently high dominance of El Niño conditions in the May 2026 forecasts.

In summary, May and June 2026 favor neutral IOD conditions, with a rising probability of positive IOD (from ~5% to ~22%), which then continues to strengthen and becomes highly dominant for the remainder of the forecast period.

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Please contact us for opportunities to collaborate on research using the IRI ENSO Forecasts. We are always interested in collaborating with researchers and organizations to advance our understanding of ENSO and its impacts. Please contact us at products@iri.columbia.edu or fill out this form, and we can get back to you regarding your interests:
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References

Real-time ENSO forecast skill evaluated over the last two decades, with focus on the onset of ENSO events. Ehsan, M.A., L’Heureux, M.L., Tippett, M.K., Robertson, A.W, Turmelle, J.P., npj Clim Atmos Sci, 2024.

The IRI ENSO forecast is released on the 19th of each month. If the 19th falls on a weekend or holiday, it is released on the closest business day.

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