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June 2024 Quick Look

Published: June 13, 2024

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 2024, waning El Niño conditions persist in the central-eastern equatorial Pacific (between 160E to 160W), with important oceanic and atmospheric indicators aligning with ENSO-neutral conditions. All models in the IRI ENSO prediction plume forecast ENSO-neutral for May-Jul, 2024, which then persists during boreal summer seasons of Jun-Aug, and Jul-Sep, 2024. La Niña becomes the most probable category in Aug-Oct, 2024 through Jan-Mar, 2025.

Figures 1 and 3 (the official CPC ENSO probability forecast and the objective model-based IRI ENSO probability forecast, respectively) are often quite similar. However, occasionally they may differ noticeably. There can be several reasons for differences. One possible reason is that the human forecasters, using their experience and judgment, may disagree to some degree with the models, which may have known biases. Another reason is related to the fact that 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, so that between the second and the third Thursday of the month, the official forecast (Fig. 1) has just been updated, while the model-based forecasts (Figs. 3 and 4) are still from the third Thursday of the previous month. On the other hand, from the third Thursday of the month until the second Thursday of the next month, the model-based forecasts are more recently updated, while the official forecasts remain from the second Thursday of the current month.
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

ENSO Forecast

CPC ENSO Update

Published: Jun 13, 2024

El Niño/Southern Oscillation (ENSO) Diagnostic Discussion issued by the Climate Prediction Center/NCEP/NWS

ENSO Alert System Status: Final El Niño Advisory / La Niña Watch

Synopsis: ENSO-neutral conditions are present. La Niña is favored to develop during July-September (65% chance) and persist into the Northern Hemisphere winter 2024-25 (85% chance during November-January).  

ENSO-neutral conditions returned during the past month. Near-to-below average sea surface temperatures (SSTs) expanded across the eastern equatorial Pacific Ocean (Fig. 1). he most recent weekly Niño-3.4 index was +0.1°C, while SST anomalies remained cooler in the far eastern Niño-1+2 region (-0.5°C) and warmer in the western Niño-4 region (+0.8°C; Fig. 2). Below-average subsurface temperatures were mostly unchanged during the past month (area-averaged index in Fig. 3), with negative anomalies persisting in the eastern half of the Pacific (Fig. 4). Low-level wind anomalies were easterly over the east-central equatorial Pacific, and upper-level winds were near average. Convection was mostly average around Indonesia, while below-average rainfall strengthened near the Date Line (Fig. 5). Collectively, the coupled ocean-atmosphere system reflected ENSO-neutral conditions.

The most recent IRI plume indicates La Niña may develop during July-September 2024 and then persist through the Northern Hemisphere winter (Fig. 6). The forecast team is also favoring the development of La Niña during July-September because the rate of cooling has slowed since last month. The team still favors La Niña to emerge sometime during the summer months, given the persistent below-average subsurface ocean temperatures and changes in the tropical atmospheric circulation. In summary, ENSO-neutral conditions are present. La Niña is favored to develop during July-September (65% chance) and persist into the Northern Hemisphere winter 2024-25 (85% chance during November-January; Fig. 7).

This discussion is a consolidated effort of the National Oceanic and Atmospheric Administration (NOAA), NOAA’s National Weather Service, and their funded institutions. Oceanic and atmospheric conditions are updated weekly on the Climate Prediction Center web site (El Niño/La Niña Current Conditions and Expert Discussions). Additional perspectives and analysis are also available in an ENSO blog. A probabilistic strength forecast is available here. The next ENSO Diagnostics Discussion is scheduled for 11 July 2024. To receive an e-mail notification when the monthly ENSO Diagnostic Discussions are released, please send an e-mail message to: ncep.list.enso-update@noaa.gov.


Season La Niña Neutral El Niño
MJJ 2 97 1
JJA 39 60 1
JAS 65 34 1
ASO 75 24 1
SON 81 18 1
OND 84 15 1
NDJ 85 14 1
DJF 81 18 1
JFM 73 26 1

IRI ENSO Forecast

IRI Technical ENSO Update

Published: May 20, 2024

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.

Note: This month, a new deep learning-based ensemble forecast model (TONGJI-ML) for ENSO prediction has been added to the IRI-ENSO Plume. This model is developed by the climate research team at Tongji University, China. Further details can be found here: https://iri.columbia.edu/our-expertise/climate/enso/enso-prediction-models/

Recent and Current Conditions

The SST anomaly for NINO3.4 during the Feb-Apr 2024 season was +1.19 °C, and for the month of April 2024 it was +0.81 °C. The most recent weekly (week centered on 08 May 2024) anomaly in the NINO3.4 region was +0.30 °C, indicating that the El Niño conditions are now rapidly declining in the tropical Pacific. The IRI’s definition of El Niño, like NOAA/Climate Prediction Center’s, requires that the monthly 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 colder.

The oceanic and atmospheric conditions across the tropical Pacific indicate the continued decline of the El Niño event. As of May 16, 2024, the 30-day Southern Oscillation Index stands within the ENSO-neutral range, with a value of -3.0, while the equatorial Southern Oscillation Index registers a value of 0.6 for the month of April 2024. The Trade winds (at 850 hPa) are now normal across the tropical Pacific, while the upper-level winds (at 200 hPa) are also close to average over the equatorial Pacific. In the equatorial Pacific Ocean, negative subsurface temperature anomalies have intensified and extended further westward across the Pacific Ocean, persisting both below 50 meters and near the surface east of 140 W. Warm subsurface temperature anomalies (~ +1 °C) remain prevalent above 50 meters depth between 160E to 160W. These observed conditions in the coupled ocean-atmosphere system indicate a weak El Niño state that is diminishing, and a future transition to ENSO-neutral conditions.

Expected Conditions
Note – Only models that produce a new ENSO prediction every month are considered in this statement.
What is the outlook for the ENSO status going forward?

The El Niño/Southern Oscillation (ENSO) Diagnostic Discussion released on 09 May 2024 by the Climate Prediction Center/NCEP/NWS continued the current El Niño advisory, and issued a La Niña watch with 49% likelihood for Jun-Aug, increasing to 69% in Jul-Sep 2024.

The latest set of ENSO prediction models from mid-May 2024 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 forecast issued by the IRI, ENSO-neutral conditions are forecasted for next three overlapping 3-month seasons with 89% likelihood in May-Jul, 71% in Jul-Sep, and 54% in Jul-Sep, 2024. In Aug-Oct 2024, La Niña onset is most likely though the probability for that is just 49%, while the continuation of ENSO-neutral is estimated at 44%. La Niña then remains the dominant category for the remainder of the forecast period, with probabilities of 55% in Sep-Nov, 61% in Oct-Dec, 62% in Nov-Jan, 58% in Dec-Feb, and 54% in Jan-Mar, 2025. A plot of the probabilitiessummarizes 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.

In summary, the forecast indicates continued ENSO-neutral conditions until Jul-Sep, 2024. The forecast shows La Niña onset in Aug-Oct (49%), while the continuation of ENSO-neutral conditions is estimated with 44% chances. La Niña then remains the most likely category until the end of the forecast period in Jan-Mar 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
MJJ 2 89 9
JJA 21 71 8
JAS 39 54 7
ASO 49 44 7
SON 55 38 7
OND 61 32 7
NDJ 62 31 7
DJF 58 35 7
JFM 54 40 6

ENSO Forecast

IRI Model-Based Probabilistic ENSO Forecast

Published: May 20, 2024

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
MJJ 2 89 9
JJA 21 71 8
JAS 39 54 7
ASO 49 44 7
SON 55 38 7
OND 61 32 7
NDJ 62 31 7
DJF 58 35 7
JFM 54 40 6

ENSO Forecast

CPC Official Probabilistic ENSO Forecast

Published: Jun 13, 2024

The official CPC ENSO probability forecast, based on a consensus of CPC and IRI forecasters. It is updated during the first half of the month, in association with the official CPC ENSO Diagnostic Discussion. It is based on observational and predictive information from early in the month and from the previous month. It uses human judgment in addition to model output, while the forecast shown in the Model-Based Probabilistic ENSO Forecast relies solely on model output. This is updated on the second Thursday of every month.


NOAA?CPC ENSO Forecast Image
NOAA/CPC ENSO Forecast Graphic, courtesy of NOAA/CPC

Season La Niña Neutral El Niño
MJJ 2 97 1
JJA 39 60 1
JAS 65 34 1
ASO 75 24 1
SON 81 18 1
OND 84 15 1
NDJ 85 14 1
DJF 81 18 1
JFM 73 26 1

ENSO Forecast

IRI ENSO Predictions Plume

Published: May 20, 2024

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 (2024 – 2025)
Model MJJ JJA JAS ASO SON OND NDJ DJF JFM
Dynamical Models
AUS-ACCESS 0.49 0.27 0.07 -0.07
BCC_CSM11m -0.10 -0.05 0.16 0.31 0.35 0.31 0.27 0.23 0.19
CMC CANSIP -0.33 -0.64 -0.80 -0.92 -1.04 -1.19 -1.29 -1.28 -1.19
COLA CCSM4 -0.30 -0.98 -1.50 -1.77 -1.88 -1.96 -2.00 -1.90 -1.61
CS-IRI-MM 0.19 -0.08 -0.38 -0.66 -0.91 -1.13
DWD 0.44 0.31 0.21 0.13
ECMWF -0.10 -0.32 -0.43 -0.49 -0.52
GFDL SPEAR 0.22 0.01 -0.25 -0.51 -0.79 -1.02 -1.07 -0.88 -0.54
IOCAS ICM 0.43 0.30 0.12 -0.03 -0.23 -0.51 -0.75 -0.86 -0.87
JMA -0.03 -0.33 -0.49 -0.62 -0.72
KMA -0.26 -0.63 -1.00 -1.21
LDEO 0.17 -0.18 -0.36 -0.43 -0.43 -0.37 -0.13 0.19 0.41
MetFRANCE 0.40 0.20 0.09 0.00 -0.06
NCEP CFSv2 -0.17 -0.56 -0.85 -1.12 -1.37 -1.53 -1.50
SINTEX-F 0.01 -0.27 -0.45 -0.53 -0.58 -0.64 -0.63 -0.61 -0.54
UKMO -0.25 -0.67 -0.89 -1.01
Average, Dynamical models 0.049 -0.226 -0.422 -0.557 -0.682 -0.893 -0.887 -0.730 -0.593
Statistical Models
BCC_RZDM -0.14 -0.52 -0.73 -1.00 -1.26 -1.57 -1.69 -1.59 -1.38
CPC CA -0.02 -0.41 -0.71 -0.94 -1.07 -1.16 -1.18 -1.12 -0.90
CPC MRKOV -0.23 -0.30 -0.38 -0.44 -0.50 -0.51 -0.46 -0.39 -0.33
CSU CLIPR 0.38 0.33 0.27 0.22 0.15 0.09 0.02 -0.01 -0.05
IAP-NN 0.40 0.10 -0.21 -0.47 -0.65 -0.77 -0.85 -0.87 -0.81
NTU CODA 0.41 0.15 0.02 -0.12 -0.24 -0.34 -0.37 -0.39 -0.38
TONGJI-ML 0.63 0.39 0.15 -0.03 -0.15 -0.12 0.01 0.14 0.15
UCLA-TCD 0.51 0.28 0.06 -0.14 -0.30 -0.40 -0.42 -0.38 -0.32
UW PSL-CSLIM 0.17 -0.04 -0.22 -0.36 -0.49 -0.60 -0.69 -0.73 -0.69
UW PSL-LIM 0.14 -0.10 -0.30 -0.46 -0.59 -0.67 -0.68 -0.67 -0.66
Average, Statistical models 0.225 -0.013 -0.204 -0.373 -0.509 -0.605 -0.631 -0.602 -0.537
Average, All models 0.117 -0.144 -0.338 -0.486 -0.603 -0.741 -0.745 -0.655 -0.560

Discussion of Current Forecasts

The ENSO forecast models in IRI-Plume indicate ENSO-neutral during May-Jul, 2024 (89% chances), which then remains the dominant category during Jun-Aug, Jul-Sep, 2024. In Aug-Oct, the chances of La Niña are 49%, while persistence of the ENSO-neutral state is estimated at 44%, which shows high uncertainty in the ENSO forecasts at this time of the year. Thereafter, La Niña is forecasted to become the most likely category with 55% chances in Sep-Nov, and subsequently with probabilities of low 60s% during boreal fall, and high 50% during boreal winter of 2024/25. Based on the multi-model mean 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
MJJ 2 89 9
JJA 21 71 8
JAS 39 54 7
ASO 49 44 7
SON 55 38 7
OND 61 32 7
NDJ 62 31 7
DJF 58 35 7
JFM 54 40 6

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: May 20, 2024


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.

The CPC ENSO forecast is released at 9am (Eastern Time) on the second Thursday of each month.

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.

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.