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July 2026 Quick Look

Published: July 20, 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)

El Niño conditions are strengthening across the tropical Pacific, with sea surface temperature (SST) anomalies in the Niño 3.4 region showing a steady upward trend. The observed SST anomaly averaged +0.98 °C during April–June 2026 and increased to +1.55 °C in June 2026. The latest weekly Niño 3.4 index, centered on July 15, 2026, climbed further to +2.1 °C. Together, these Pacific Ocean SST observations indicate that El Niño conditions continue to intensify, suggesting the event is evolving toward a very strong El Niño.

Figures 1 ((the official CPC ENSO probability forecast) and 3 (the objective model-based CCSR/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 CCSR/IRI forecast run later. Also note that the CPC forecast starts on the previous season while the CCSR/IRI forecast starts on the current season.
Click on the for more information on each figure.

Historically Speaking

    El Niño and La Niña events tend to develop during the period Apr-Jun and they
  • 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

CCSR/IRI ENSO Forecast

CCSR/IRI Technical ENSO Update and Model-Based Probabilistic ENSO Forecast

Published: July 20, 2026

ENSO Current State: Ocean–Atmosphere Overview

El Niño conditions are strengthening across the tropical Pacific, with sea surface temperature (SST) anomalies in the Niño 3.4 region showing a steady upward trend. The observed SST anomaly averaged +0.98 °C during April–June 2026 and increased to +1.55 °C in June 2026. The latest weekly Niño 3.4 index, centered on July 15, 2026, climbed further to +2.1 °C. Together, these Pacific Ocean SST observations indicate that El Niño conditions continue to intensify, suggesting the event is evolving toward a very strong El Niño.

Both oceanic and atmospheric indicators are becoming increasingly aligned, supporting further intensification of the ongoing El Niño event. On the atmospheric side, the Southern Oscillation Index (SOI) declined to -24.9 in June 2026, while the latest 30-day SOI value through July 18 remained strongly negative at -30.0. These persistently negative SOI values reflect a further weakening of the Walker circulation, consistent with continued El Niño development and intensification. In addition, the Equatorial SOI declined to -1.4 during June 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. During the past 30 days (18 June–17 July 2026), 850-hPa low-level wind anomalies were predominantly westerly across the western to east-central equatorial Pacific Ocean, while weak easterly wind anomalies persisted over the eastern equatorial Pacific. Consistent with the atmospheric response to the strengthening El Niño, below-average outgoing longwave radiation (OLR)—indicating enhanced convection and precipitation—was observed along the equator near the Date Line and across the east-central equatorial Pacific Ocean. In contrast, above-average OLR, indicating suppressed convection and precipitation, persisted over the Philippines, Indonesia, and Papua New Guinea. Further, the subsurface temperature structure in the central–eastern equatorial Pacific exhibits a pronounced warming. Between approximately 150°W and 80°W, temperatures at depths of 50–150 m have increased substantially, with anomalies locally reaching up to 6 °C. This substantial subsurface heat reservoir could serve as an important energy source for the continued development and intensification of El Niño conditions, provided that favorable atmospheric coupling is maintained.

ENSO Prediction Plume: Model-by-Model Outlook (Traditional Nino3.4 index)

The mid-July 2026 CCSR/IRI ENSO prediction plume has been updated with the latest model forecasts. The outlook shows strong agreement among the 26 participating models (15 dynamical and 11 statistical) that El Niño conditions will strengthen further during 2026 and persist into early 2027. All models maintain positive Niño3.4 anomalies throughout the forecast period, indicating a high level of confidence in the ongoing warming of the central and eastern tropical Pacific. Most dynamical models forecast Niño3.4 anomalies exceeding +2.0°C by Jul-Sep. Statistical models indicate a somewhat weaker but still substantial warming signal. Despite some uncertainty in the projected peak intensity, the forecast consensus is clear: a strong El Niño is highly likely to develop and persist through late 2026.

ENSO Probabilities

To generate the ENSO probability outlook, forecasts from all 26 participating models (15 dynamical and 11 statistical) are combined into an equally weighted multi-model average of Niño3.4 SST anomalies. A Gaussian error distribution is then applied to the ensemble-mean forecast, with its width determined by the expected forecast skill for the season and lead time. Higher forecast skill results in a narrower distribution and greater confidence, while lower skill produces a broader range of possible outcomes. Probabilities are calculated based on the likelihood of Niño3.4 SST anomalies falling within the standard ENSO thresholds: El Niño (≥ +0.5°C), ENSO-neutral (-0.5°C to +0.5°C), and La Niña (≤ -0.5°C). This methodology translates the multi-model forecast into probabilities for each ENSO category.

The July 2026 outlook strongly favors the persistence of El Niño conditions throughout the forecast period. El Niño probabilities are 100% from JAS 2026 through JFM 2027. From FMA to MAM 2027, the probabilities remain exceptionally high at 99% and 94%, respectively, with the remaining probability assigned to ENSO-neutral conditions. No probability is assigned to La Niña development during this period. As this outlook is issued in July, the boreal spring predictability barrier has already passed. Therefore, the high-confidence outlook is supported by strong model consensus and indicates a very high likelihood that El Niño will persist into early 2027. The accompanying probability plot summarizes the forecast evolution and the changing likelihood of each ENSO phase throughout the forecast period.

ENSO Strength

Forecasts of ENSO strength are estimated through a consensus-based model counting approach using a set of Niño 3.4 sea surface temperature anomaly thresholds, to indicate weak, moderate, strong and very strong El Nino and La Nina categories.

The mid-July 2026 CCSR/IRI model ensemble overwhelmingly supports the development of a strong El Niño, with every model maintaining El Niño conditions throughout the forecast period. The event is projected to peak during OND 2026, when 23 of 26 models forecast a very strong El Niño (Niño 3.4 ≥ +2.0 °C). Overall, the forecast signal is clear, consistent, and supported by exceptional model agreement.

Notes:

The SST anomalies cited below are based on the NOAA Optimum Interpolation Sea Surface Temperature (OISSTv2)dataset. The climatology period is 1991–2020.

The primary metric used to monitor the El Niño–Southern Oscillation (ENSO) is the traditional Niño3.4 index (TONI), defined as the area-averaged sea surface temperature anomaly over the Niño3.4 region (5°S–5°N, 170°W–120°W).

According to the CCSR/IRI definition, El Niño conditions occur when monthly TONI exceeds +0.5 °C, while La Niña conditions occur when monthly TONI falls below −0.5 °C.

An ENSO “event” is considered established when the TONI threshold (±0.5 °C) persists for at least five consecutive overlapping 3-month seasons (e.g., SON, OND, NDJ, DJF, JFM).

CCSR/IRI ENSO Forecast Histogram Image

ENSO Forecast

CCSR/IRI ENSO Predictions Plume

Published: July 20, 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

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 a CCSR/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 CCSR/IRI ENSO Prediction Plume

Published: July 20, 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.

  • Model Based Prediction Percentiles Image

    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.

  • Model Based Prediction Distribution Image

    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: July 20, 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 June 2026, the observed Dipole Mode Index was -0.46 °C, indicating negative 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 (based on July 2026 initialization) from CESM1, CanESM5, GEM-NEMO, GFDL-SPEAR, and NASA along with their equally weighted multi-model mean (MME). Observations show that the DMI (black line) has remained in a neutral state since January 2026, before turning negative in May and June 2026, as reflected by the observed DMI values for those two months. Forecasts indicate that the IOD is expected to remain neutral during July 2026, with a gradual transition toward positive IOD conditions. By August 2026, three of the five models exceed the positive IOD threshold and remain in positive territory through the end of the forecast period in January 2027. The multi-model ensemble likewise indicates a transition to positive IOD conditions beginning in August 2026, with those conditions persisting through the remainder of the forecast period.

Probabilistic IOD Forecasts from the NMME

Based on July 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, 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 July 2026, neutral IOD conditions dominate, while the probability of positive IOD remains low (~6%). By August, the probability of positive IOD increases sharply to ~68%. From September through November 2026, positive IOD probabilities exceed 80%, while the likelihood of neutral conditions drops below 20%. During December 2026 and January 2027, positive IOD probabilities gradually decline to 70% and 54%, respectively, as the likelihood of neutral conditions increases to 26% and 36%.

Overall, the forecast favors the development and persistence of a positive IOD through late 2026.

Figure: IOD Plume and Probabilities (July, 2026).

July 20, 2026 IOD Model Based Forecast
Historical SST Anomalies Image

Contact Us

Please contact us for opportunities to collaborate on research using the CCSR/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:

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 CCSR/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.

We are no longer providing forecast data. If you would like to collaborate with us on ENSO research, please fill out this form, and we can get back to you regarding your interests:
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