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August 2025 Quick Look

Published: August 19, 2025

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-August 2025, the equatorial Pacific remains in an ENSO-neutral state, with sea surface temperatures in the Niño 3.4 region close to average. The IRI ENSO plume forecast indicates a moderate probability (68%) of ENSO-neutral conditions for Aug–Oct 2025. These neutral conditions are expected to persist through the end of the forecast period. However, during Sep–Nov and Oct–Dec, the probabilities for ENSO-neutral decrease slightly to 49% and 50%, respectively, but remain higher than those for either La Niña or El Niño. During these two overlapping seasons (SON and OND), the probability of La Niña development increases to 39% and 44%, respectively. Looking ahead to the 2025/2026 winter and spring periods, ENSO-neutral once again becomes the dominant category, with gradually increasing probabilities.

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

    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

IRI ENSO Forecast

IRI Technical ENSO Update

Published: August 19, 2025

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 SST anomaly in the NINO3.4 region during May-July 2025 season was -0.02 °C, and for July, it was -0.06 °C. The most recent weekly average (week centered on August 13, 2025) of the NINO3.4 index was -0.3 °C. The latest seasonal, monthly, and weekly values indicate that the tropical Pacific has been experiencing ENSO-neutral conditions. The IRI’s definition of El Niño, similar to NOAA/Climate Prediction Center’s, 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.

As of mid-August 2025, both atmospheric and oceanic indicators continue to show ENSO-neutral conditions; however, there are indications that in the coming months the tropical Pacific is potentially evolving towards the development of La Niña conditions. The traditional and equatorial Southern Oscillation Index (SOI) for July 2025 was +6.8 and +0.9 respectively, falling within the ENSO-neutral ranges. Low-level (850-hPa) wind anomalies were easterly across small parts of the east-central and eastern Pacific, in contrast to the upper-level (200-hPa) wind anomalies, which were westerly over the eastern equatorial Pacific. Below-average OLR, reflecting stronger convection and precipitation, was observed over parts of Indonesia, while above-average OLR, indicating weaker convection and less precipitation, was present over the western equatorial Pacific Ocean. Over the past few months, below-average surface temperatures have intensified in the east-central and eastern Pacific. Should these cooler anomalies strengthen further in conjunction with enhanced trade winds, it may indicate the potential onset of La Niña conditions. Meanwhile, above-average subsurface temperatures have continued in the western and central Pacific. The current conditions overall indicate the persistence of ENSO-neutral status; however, there are gradual developments and signs in both the ocean and atmosphere suggesting the possible onset of La Niña conditions in the coming months.

Expected Conditions

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

The El Niño/Southern Oscillation (ENSO) Diagnostic Discussion released on 14 August 2025 by the Climate Prediction Center/NCEP/NWS issued a “La Niña Watch”, forecasting that ENSO-neutral conditions are most likely to persist through late Northern Hemisphere summer 2025, with 56% probability during August–October, 2025. Thereafter, a brief period of La Niña conditions is favored in the fall and early winter of 2025–26, before reverting back to ENSO-neutral.

The latest set of ENSO prediction models from mid-August 2025 is now available in the IRI ENSO prediction plume. 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.

According to the ENSO plume forecast issued by the IRI in August 2025, there is a moderate probability (68%) of ENSO-neutral conditions continuing during Aug–Oct 2025, while the chances for La Niña and El Niño are 30% and 2%, respectively. For the periods September–November and October–December, the probability of ENSO-neutral conditions decreases to 57% and 49%, respectively, while the likelihood of La Niña increases to 39% and 44%. Subsequently, the probability for ENSO-neutral conditions gradually increases again from 50% in Nov-Jan, 52% in Dec-Feb, 58% in Jan-Mar, 66% in Feb-Apr, 73% in Mar-May, and 71% in Apr-Jun, 2026. During this same period, the probabilities for El Niño and La Niña range from 8% to 42%. During the Northern Hemisphere fall, the odds may shift slightly toward the development of the La Niña conditions (currently 44% chances during Oct-Dec 2025 and 42% in Nov-Jan), depending on how conditions evolve in the coming months. 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 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.

It is worth noting that the Relative Oceanic Niño Index (RONI: https://www.cpc.ncep.noaa.gov/data/indices/RONI.ascii.txt), which measures sea surface temperature anomalies in the Niño 3.4 region (5°N–5°S, 120°W–170°W) relative to the rest of the equatorial band, has exceeded the -0.5 La Niña threshold for the past several overlapping seasons (with values of -0.50 for Jun–Aug 2024, -0.63 for Jul–Sep, -0.75 for Aug–Oct, -0.81 for Sep–Nov, -0.92 for Oct–Dec, -1.07 for Nov–Jan, -1.12 for Dec–Feb, -0.89 for Jan–Mar 2025, -0.67 for Feb–Apr, -0.53 for Mar–May, and -0.49 for Apr–Jun 2025). However, it is currently showing values ENSO-neutral values (-0.40 for May–Jul 2025).

A caution regarding the model-based ENSO plume predictions (released mid-month) is that factors such as known specific model biases and recent changes in the tropical Pacific that the models may have missed, are not considered. This approach is purely objective. Those issues are taken into account in CPC’s official outlooks, which are issued early in the month, and which will include some human judgment in combination with the model guidance.

IRI ENSO Forecast Histogram Image
Season La Niña Neutral El Niño
ASO 30 68 2
SON 39 57 4
OND 44 49 7
NDJ 42 50 8
DJF 38 52 10
JFM 32 58 10
FMA 24 66 10
MAM 17 73 10
AMJ 13 71 16

ENSO Forecast

IRI Model-Based Probabilistic ENSO Forecast

Published: August 19, 2025

A purely objective ENSO probability forecast, based on regression, using as input the model predictions from the plume of dynamical and statistical forecasts shown in the ENSO Predictions Plume. Each of the forecasts is weighted equally. It is updated near or just after the middle of the month, using forecasts from the plume models that are run in the first half of the month. It does not use any human interpretation or judgment. This is updated on the third Thursday of the month.

IRI ENSO Forecast Histogram Image

Season La Niña Neutral El Niño
ASO 30 68 2
SON 39 57 4
OND 44 49 7
NDJ 42 50 8
DJF 38 52 10
JFM 32 58 10
FMA 24 66 10
MAM 17 73 10
AMJ 13 71 16

ENSO Forecast

IRI ENSO Predictions Plume

Published: August 19, 2025

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

Forecast SST Anomalies (deg C) in the Nino 3.4 Region

Seasons (2025 – 2026)
Model ASO SON OND NDJ DJF JFM FMA MAM AMJ
Dynamical Models
AUS-ACCESS -0.18 -0.17 -0.10 0.03
BCC DIAP 0.05 0.07 0.09 0.11 0.15 0.19 0.13 0.12 0.07
CMC CANSIP -0.26 -0.28 -0.26 -0.15 -0.03 0.09 0.20 0.33 0.47
COLA CCSM4 -0.37 -0.58 -0.78 -0.72 -0.47 -0.17 0.13 0.38 0.57
CS-IRI-MM -0.11 -0.14 -0.18 -0.15 -0.06 0.04
ECMWF -0.25 -0.21 -0.19 -0.16 -0.08
IOCAS ICM -0.18 -0.31 -0.50 -0.64 -0.64 -0.54 -0.37 -0.23 -0.13
JMA -0.36 -0.43 -0.41 -0.34 -0.17
KMA -0.54 -0.62 -0.64 -0.54
LDEO -0.12 -0.15 -0.18 -0.19 -0.22 -0.23 -0.21 -0.12 0.05
MetFRANCE -0.54 -0.59 -0.59 -0.47 -0.32
NASA GMAO -0.81 -0.91 -0.85 -0.72 -0.47 -0.18 0.09
NCEP CFSv2 -0.46 -0.65 -0.80 -0.72 -0.50 -0.24 0.00
SINTEX-F -0.15 -0.14 -0.12 -0.05 0.07 0.18 0.33 0.43 0.54
UKMO -0.68 -0.79 -0.74 -0.59
Average, Dynamical models -0.331 -0.393 -0.417 -0.353 -0.229 -0.095 0.038 0.152 0.261
Statistical Models
BCC_RZDM -0.45 -0.60 -0.76 -0.80 -0.72 -0.55 -0.40 -0.28 -0.21
CPC CA -0.20 -0.26 -0.29 -0.34 -0.35 -0.25 -0.07 0.10 0.30
CPC MRKOV -0.82 -0.90 -0.93 -0.86 -0.74 -0.62 -0.54 -0.46 -0.37
CSU CLIPR -0.16 -0.14 -0.11 -0.09 -0.09 -0.08 -0.08 0.03 0.14
IAP-NN -0.12 -0.18 -0.23 -0.23 -0.21 -0.16 -0.11 -0.05 0.01
NTU CODA -0.15 -0.16 -0.17 -0.18 -0.17 -0.15 -0.11 -0.05 0.04
UCLA-TCD -0.05 -0.15 -0.22 -0.23 -0.20 -0.12 0.00 0.14 0.27
UW PSL-CSLIM -0.14 -0.31 -0.50 -0.68 -0.77 -0.75 -0.66 -0.53 -0.43
UW PSL-LIM -0.20 -0.28 -0.34 -0.36 -0.38 -0.41 -0.47 -0.53 -0.55
XRO -0.15 -0.24 -0.34 -0.43 -0.47 -0.44 -0.39 -0.34 -0.32
Average, Statistical models -0.244 -0.322 -0.389 -0.420 -0.409 -0.354 -0.283 -0.196 -0.112
Average, All models -0.296 -0.365 -0.406 -0.380 -0.311 -0.231 -0.140 -0.066 0.028

Discussion of Current Forecasts

The IRI ENSO prediction plume indicates a high likelihood of ENSO-neutral conditions during Aug–Oct 2025 (68% chance). The multimodel mean of statistical and dynamical models shows ENSO-neutral conditions remaining dominant throughout the forecast period, with a slight decrease in probability during Sep-Nov and Oct–Dec, followed by an increase from Nov-Jan through the end of the forecast period. These forecasts show a slightly preference for La Niña as compared to El Niño. 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:

Season La Niña Neutral El Niño
ASO 30 68 2
SON 39 57 4
OND 44 49 7
NDJ 42 50 8
DJF 38 52 10
JFM 32 58 10
FMA 24 66 10
MAM 17 73 10
AMJ 13 71 16

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.

Historical SST Anomalies Image

ENSO Forecast

Forecast Probability Distribution Based on the IRI ENSO Prediction Plume

Published: August 19, 2025

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.

New Article

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.

Forecast and model data used in our probabilistic forecast can be accessed by submitting a Request to Access IRI ENSO Data.

All data from this website is covered under the Creative Commons Attribution 4.0 License. When citing IRI ENSO images or data, please use "Images [or Data] provided by The International Research Institute for Climate and Society, Columbia University Climate School", with a link to https://iri.columbia.edu/ENSO.