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February 2024 Quick Look

Published: February 19, 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-February 2024, moderate-strong El Niño conditions persist in the central-eastern equatorial Pacific, with important oceanic and atmospheric indicators aligning with an ongoing El Niño event that is gradually diminishing. An El Niño advisory from the CPC continues for February 2024, alongside a La Niña watch issued for June to August 2024. Almost all the models in the IRI ENSO prediction plume forecast a continuation of the El Niño event during the rest of the boreal winter and spring of 2024, which rapidly weakens thereafter. ENSO-neutral conditions become the most likely category in Apr-Jun, and May-Jul of 2024. For Jun-Aug 2024, no single category stands out as dominant, with ENSO-neutral and La Niña being almost equally likely. By Jul-Sep 2024, La Niña becomes the most probable category.

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: February 8, 2024

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

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

Synopsis: A transition from El Niño to ENSO-neutral is likely by April-June 2024 (79% chance), with increasing odds of La Niña developing in June-August 2024 (55% chance).

During January 2024, above-average sea surface temperatures (SST) continued across most of the equatorial Pacific Ocean (Fig. 1). SST anomalies weakened slightly in the eastern and east-central Pacific, as indicated by the weekly Niño index values (Fig. 2). However, changes were more pronounced below the surface of the equatorial Pacific Ocean, with area-averaged subsurface temperature anomalies returning to near zero (Fig. 3). Although above-average temperatures persisted in the upper 100 meters of the equatorial Pacific, below-average temperatures were widespread at greater depths (Fig. 4). Atmospheric anomalies across the tropical Pacific also weakened during January.  Low-level winds were near average over the equatorial Pacific, while upper-level wind anomalies were easterly over the east-central Pacific.  Convection remained slightly enhanced near the Date Line and was close to average around Indonesia (Fig. 5). Collectively, the coupled ocean-atmosphere system reflected a weakening El Niño.

The most recent IRI plume indicates a transition to ENSO-neutral during spring 2024, with La Niña potentially developing during summer 2024 (Fig. 6). Even though forecasts made through the spring season tend to be less reliable, there is a historical tendency for La Niña to follow strong El Niño events.  The forecast team is in agreement with the latest model guidance, with some uncertainty around the timing of transitions to ENSO-neutral and, following that, La Niña.  Even as the current El Niño weakens, impacts on the United States could persist through April 2024 (see CPC seasonal outlooks for probabilities of temperature and precipitation).  In summary, a transition from El Niño to ENSO-neutral is likely by April-June 2024 (79% chance), with increasing odds of La Niña developing in June-August 2024 (55% chance; 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 14 March 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
JFM 0 0 100
FMA 0 0 100
MAM 0 25 75
AMJ 2 79 19
MJJ 26 68 6
JJA 55 42 3
JAS 68 30 2
ASO 74 24 2
SON 77 20 3

IRI ENSO Forecast

IRI Technical ENSO Update

Published: February 19, 2023

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 for NINO3.4 during the NovJan 2023 season was +1.89 °C, and for the month of Jan 2024 it was +1.78 °C. The most recent weekly (week centered on 14 Feb 2024) anomaly in the NINO3.4 region was +1.50 °C, indicating that the tropical Pacific is experiencing moderate-strong El Niño conditions but which have started to decline. 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. 

Oceanic and atmospheric conditions over the tropical Pacific are consistent with an ongoing El Niño event, though atmospheric indicators are quite weak as compared to past El Niño events of similar magnitude. The traditional Southern Oscillation Index is in ENSO-neutral range (as of January 2023, the last recorded index value was 3.7). Simultaneously, the equatorial Southern Oscillation Index registers a value of -1.0 for the same month. While the equatorial Southern Oscillation Index suggests El Niño conditions, its present value does not align with the characteristics of a strong event. Indonesia was characterized by positive anomalies in Outgoing Longwave Radiation (OLR), indicating suppressed convection and reduced precipitation. Conversely, negative OLR anomalies, denoting enhanced convection and increased precipitation, were observed near the Date Line, extending into the eastern Pacific just north of the equator. The Trade winds (at 850 hPa) were normal across most of the tropical Pacific, while easterly anomalies characterized the upper-level winds (at 200 hPa) over the equatorial Pacific. Throughout the equatorial Pacific Ocean, there is a widespread presence of warm temperature anomalies, covering the central to eastern Pacific region from surface to 50 meters in depth. Concurrently, negative subsurface temperature anomalies have further intensified and expanded westward across the Pacific Ocean, persisting at depths below 50 meters. Together, the current observed state of the coupled ocean-atmosphere system reflects ongoing El Niño conditions that are gradually declining. 

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 on 08 February 2024 by the Climate Prediction Center/NCEP/NWS released the El Niño advisory, and also issued a La Niña watch (55% chance) for Jun-Aug, 2024.

The latest set of ENSO prediction models from mid-Feb 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.  

The forecast from the IRI for ENSO suggests a strong probability of El Niño conditions continuing over the next few months, followed by a shift to ENSO-neutral conditions in the boreal spring, susequently transitioning to La Niña during boreal summer. In particular, El Niño is the dominant category, with values of 83% during Mar-May, 2024. Thereafter, there is a rapid decrease in the probability of El Niño and a transition to ENSO-neutral is likely in Apr-Jun (72%). The ENSO-neutral category remains dominant during May-Jul (71%). During Jun-Aug, ENSO-neutral (46%) and La Niña (49%) are almost equally likely. La Niña then becomes the dominant category for the remainder of the forecast period, with probabilities of 65% in Jul-Sep, 71% in Aug-Oct, 68% in Sep-Nov, and 69% in Oct-Dec, 2024. 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.

In summary, the forecast for Feb-Apr 2024 shows a very high probability of continued El Niño conditions. The chances of a transition to ENSO-neutral conditions then rapidly increases to about 72% in Apr-Jun, and remains so for May-Jul 2024. La Niña becomes the most likely category in Jul-Sep through the end of the forecast period in Oct-Dec 2024 

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 the official outlooks, which are generated and issued early in the month by CPC, and which will include some human judgment in combination with the model guidance.


IRI ENSO Forecast Histogram Image
Season La Niña Neutral El Niño
FMA 0 0 100
MAM 0 17 83
AMJ 1 72 27
MJJ 20 71 9
JJA 49 46 5
JAS 65 32 3
ASO 71 26 3
SON 68 27 5
OND 69 24 7

ENSO Forecast

IRI Model-Based Probabilistic ENSO Forecast

Published: February 19, 2023

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
FMA 0 0 100
MAM 0 17 83
AMJ 1 72 27
MJJ 20 71 9
JJA 49 46 5
JAS 65 32 3
ASO 71 26 3
SON 68 27 5
OND 69 24 7

ENSO Forecast

CPC Official Probabilistic ENSO Forecast

Published: February 8, 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
JFM 0 0 100
FMA 0 0 100
MAM 0 25 75
AMJ 2 79 19
MJJ 26 68 6
JJA 55 42 3
JAS 68 30 2
ASO 74 24 2
SON 77 20 3

ENSO Forecast

IRI ENSO Predictions Plume

Published: February 19, 2023

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 – 2024)
Model FMA MAM AMJ MJJ JJA JAS ASO SON OND
Dynamical Models
AUS-ACCESS 1.43 1.17 0.87 0.60
BCC_CSM11m 1.10 0.71 0.40 0.18 0.09 0.09 0.13 0.18 0.23
CMC CANSIP 1.14 0.58 -0.04 -0.58 -0.97 -1.21 -1.30 -1.33 -1.33
COLA CCSM4 1.21 0.70 0.05 -0.78 -1.54 -2.10 -2.41 -2.58 -2.61
CS-IRI-MM 1.24 0.83 0.41 0.02 -0.24 -0.41
DWD 1.65 1.48 1.14 0.80
ECMWF 1.34 0.92 0.53 0.21 -0.04
GFDL SPEAR 1.23 0.80 0.31 -0.11 -0.33 -0.40 -0.46 -0.59 -0.72
IOCAS ICM 1.25 0.98 0.41 -0.10 -0.52 -0.79 -0.97 -1.14 -1.35
JMA 1.15 0.72 0.32 -0.01 -0.23
KMA 1.44 0.88 0.24 -0.31
LDEO 1.13 0.81 0.46 0.02 -0.36 -0.53 -0.49 -0.36 -0.14
MetFRANCE 1.69 1.24 0.72 0.30 0.05
NASA GMAO 1.08 0.31 -0.48 -1.22 -1.76 -2.15 -2.48
NCEP CFSv2 0.97 0.50 -0.06 -0.63 -1.04 -1.33 -1.56
SINTEX-F 1.39 0.83 0.11 -0.46 -0.80 -0.88 -0.95 -0.97 -1.00
UKMO 1.09 0.59 0.06 -0.40
Average, Dynamical models 1.267 0.827 0.321 -0.145 -0.591 -0.971 -1.166 -0.969 -0.988
Statistical Models
BCC_RZDM 1.07 0.73 0.40 0.05 -0.27 -0.54 -0.76 -0.94 -1.19
CPC CA 0.97 0.60 0.18 -0.31 -0.77 -1.10 -1.30 -1.40 -1.51
CPC MRKOV 0.63 0.47 0.35 0.24 0.15 0.07 0.03 -0.01 -0.02
CSU CLIPR -0.21 -0.43 -0.65 -0.87 -0.89 -0.91 -0.93 -1.36 -1.79
IAP-NN 1.41 1.10 0.76 0.39 0.02 -0.33 -0.61 -0.80 -0.92
UCLA-TCD 1.30 0.93 0.58 0.28 0.04 -0.18 -0.37 -0.52 -0.59
UW PSL-CSLIM 1.01 0.57 0.21 -0.07 -0.30 -0.49 -0.67 -0.83 -0.96
UW PSL-LIM 1.12 0.68 0.28 -0.05 -0.33 -0.56 -0.74 -0.88 -0.96
Average, Statistical models 0.912 0.582 0.264 -0.042 -0.294 -0.505 -0.669 -0.842 -0.992
Average, All models 1.154 0.749 0.303 -0.112 -0.478 -0.764 -0.932 -0.901 -0.990

Discussion of Current Forecasts

Almost all models in the IRI ENSO-plume predict El Niño conditions that are forecasted to continue during the rest of the boreal winter and spring of 2024. ENSO-neutral is the next most-likely category, with low probabilities in boreal spring (17% in Mar-May), progressively increasing to become dominant category during Apr-Jun (72%), and May-Jul (71%). The chances of La Niña are nearzero during most of the boreal spring of 2024, increasing thereafter to become the most likely category from Jul-Sep, 2024 onwards. 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
FMA 0 0 100
MAM 0 17 83
AMJ 1 72 27
MJJ 20 71 9
JJA 49 46 5
JAS 65 32 3
ASO 71 26 3
SON 68 27 5
OND 69 24 7

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: February 19, 2023


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.