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IRI ENSO Forecast

January 2021 Quick Look

Published: January 14, 2021

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)

Use the navigation menu on the right to navigate to the different forecast sections

In mid-January, SSTs in the east-central Pacific are roughly 1.2 degree C below average, and all key atmospheric variables are consistent with La Niña conditions. A large majority of the model forecasts predict SSTs to be cooler than the threshold of La Niña SST conditions through the winter, dissipating during spring. The new official CPC/IRI outlook issued earlier this month is similar to these model forecasts, calling for a 95% chance of La Niña for the Jan-Feb-Mar season. A La Niña advisory is in effect.

Figures 1 and 3 (the official ENSO probability forecast and the objective model-based 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

IRI ENSO Forecast

CPC/IRI ENSO Update

Published: January 14, 2021

El Niño/Southern Oscillation (ENSO) Diagnostic Discussion issued jointly by the Climate Prediction Center/NCEP/NWS and the International Research Institute for Climate and Society

ENSO Alert System Status: La Niña Advisory

Synopsis: La Niña is expected to continue through the Northern Hemisphere winter 2020-21 (~95% chance during January-March), with a potential transition to ENSO-neutral during the spring 2021 (55% chance during April-June).

Below-average sea surface temperatures (SSTs) extend from the western to the eastern Pacific Ocean, and reflect the continuation of La Niña (Fig. 1). Most of the Niño indices were relatively steady throughout the month (the latest weekly Niño-3.4 index value was -1.1ºC), with negative values strengthening to -1.2ºC in the westernmost Niño-4 region (Fig. 2). The subsurface temperature anomalies on the equator (averaged from 180°-100°W) remained negative (Fig. 3), but weakened slightly in the eastern equatorial Pacific Ocean (Fig. 4). The atmospheric circulation associated with La Niña strengthened over the tropical Pacific Ocean during the month.   Low-level wind anomalies were easterly over the western to east-central tropical Pacific and upper-level wind anomalies were westerly across most of the tropical Pacific.  Tropical convection was suppressed over the western and central Pacific and enhanced around the Philippines and parts of Indonesia (Fig. 5). Both the Southern Oscillation and Equatorial Southern Oscillation strengthened during December.  Overall, the coupled ocean-atmosphere system is consistent with the ongoing La Niña.

A majority of the models in the IRI/CPC plume predict La Niña to continue through the Northern Hemisphere spring (Fig. 6). The forecaster consensus is in line with the models and suggests a transition to ENSO-neutral in the late spring 2021.  However, the forecast uncertainty increases throughout the summer and fall, which is reflected by the lower probabilities (less than ~50%) for La Niña and ENSO-neutral.  These low forecast probabilities beyond the spring are consistent with the spring predictability barrier, when model forecasts are historically less accurate than during other times of the year.  In summary, La Niña is expected to continue through the Northern Hemisphere winter 2020-21 (~95% chance for January-March), with a potential transition to ENSO-neutral during the spring 2021 (55% chance during April-June; click CPC/IRI consensus forecast for the chance of each outcome for each 3-month period).

La Niña is anticipated to affect temperature and precipitation across the United States during the upcoming months (the 3-month seasonal temperature and precipitation outlooks will be updated on Thurs. January 21st.

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 February 2021. 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.

CPC/IRI Early-Month Model-Based ENSO Forecast Probabilities

Season La Niña Neutral El Niño
DJF 2021 100% 0% 0%
JFM 2021 96% 4% 0%
FMA 2021 78% 22% 0%
MAM 2021 57% 43% 0%
AMJ 2021 43% 55% 2%
MJJ 2021 35% 58% 7%
JJA 2021 37% 52% 11%
JAS 2021 42% 45% 13%
ASO 2021 44% 41% 14%

Please refer to our licensing agreement for permission to use IRI ENSO materials. The CPC/IRI materials are not included in this licensing.

IRI ENSO Forecast

IRI Technical ENSO Update

Published: January 19, 2021

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. During ENSO events, OISSTv2 often shows stronger anomalies than ERSSTv5, and during very strong events the two datasets may differ by as much as 0.5 C. Additionally, the ERSSTv5 may tend to be cooler than OISSTv2, 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 and so, half of the time, is based on a slightly older period and does not account as much for the slow warming trend in the tropical Pacific SST.

Recent and Current Conditions

In mid-January 2021, SSTs remain below average in the NINO3.4 region, and the tropical Pacific has exhibited La Niña conditions since August. The SST anomaly for NINO3.4 during the Oct-Dec season was -1.25 C, and for the month of December it was -1.04 C, suggesting an initial weakening of the moderate La Niña conditions over the last month. The IRI’s definition of El Niño, like NOAA/Climate Prediction Center’s, requires that the 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 less. The climatological probabilities for La Niña, neutral, and El Niño conditions vary seasonally, and are shown in a table at the bottom of this page for each 3-month season. The most recent weekly anomaly in the NINO3.4 region was -1.2 C, which is higher than that of December, as there exists discernible week-to-week variability in the strength of the SST anomalies. All key atmospheric variables, such as the low-level and upper-level zonal wind anomalies and patterns of cloudiness and rainfall, indicate La Niña conditions. The traditional and equatorial Southern Oscillation Indices have been positive, and anomalously dry conditions have been observed around the date line through to the west-central part of the basin. Subsurface temperature anomalies in the central and eastern equatorial Pacific remain below average in mid-January. In summary, current conditions still indicate a moderate La Niña. A La Niña advisory is in effect.

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 most recent official diagnosis and outlook was issued approximately one week ago in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it states that La Niña conditions are present and are most likely to continue through boreal winter, with a 95% chance. A transition to neutral conditions during the Apr-Jun season is suggested with a 55% probability.

The latest set of model ENSO predictions from mid-January is now available in the IRI/CPC ENSO prediction plume. These are used to assess the probabilities of the three possible ENSO conditions by using the average value of the NINO3.4 SST anomaly predictions from all models on the plume, equally weighted. A standard Gaussian error is imposed over that average forecast, and its width is 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. Using this method, chances for La Niña are 89% for the Jan-Mar season, while chances for El Niño are 0%. Going forward, probabilities for La Niña decrease to 70% by Feb-Apr, near 45% for Mar-May. ENSO-neutral conditions become most likely by Apr-Jun, starting at about 70% and then dropping to climatological odds by the end of boreal summer and onward. The current set of forecasts suggests a more rapid transition to ENSO- neutral than was predicted in the last few months. El Niño probabilities are less than 10% until May-Jul, then rise to about 20% during boreal summer. A plot of the probabilities generated from this most recent IRI/CPC ENSO prediction plume using the multi-model mean and the Gaussian standard error method summarizes the model consensus out to about 10 months into the future.

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 probabilities derived from the models on the IRI/CPC plume describe a very slim chance for El Niño conditions throughout most of the forecast period, and a preference for La Niña conditions relative to neutral conditions during the next few seasons from Jan-Mar extending through Mar-May. By the Apr-Jun season, neutral becomes the more likely outcome through the remaining forecast periods, through the Aug-Oct season. This scenario has been stable over the last couple months of forecasts, though the transition from La Niña to ENSO-neutral is forecast to occur slightly earlier in the recent model predictions compared to those of the last few months.

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 IRI, and which will include some human judgment in combination with the model guidance.

Please refer to our licensing agreement for permission to use IRI ENSO materials. The CPC/IRI materials are not included in this licensing.

IRI ENSO Forecast

IRI/CPC Model-Based Probabilistic ENSO Forecast

Published: January 19, 2021

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/CPC Mid-Month Model-Based ENSO Forecast Probabilities

Season La Niña Neutral El Niño
JFM 2021 89% 11% 0%
FMA 2021 70% 30% 0%
MAM 2021 45% 55% 0%
AMJ 2021 27% 71% 2%
MJJ 2021 23% 66% 11%
JJA 2021 23% 57% 20%
JAS 2021 26% 53% 21%
ASO 2021 29% 47% 24%
SON 2021 34% 42% 24%

IRI ENSO Forecast

CPC/IRI Official Probabilistic ENSO Forecast

Published: January 14, 2021

The official CPC/IRI 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/IRI 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.



CPC/IRI Early-Month Model-Based ENSO Forecast Probabilities

Season La Niña Neutral El Niño
DJF 2021 100% 0% 0%
JFM 2021 96% 4% 0%
FMA 2021 78% 22% 0%
MAM 2021 57% 43% 0%
AMJ 2021 43% 55% 2%
MJJ 2021 35% 58% 7%
JJA 2021 37% 52% 11%
JAS 2021 42% 45% 13%
ASO 2021 44% 41% 14%

Please refer to our licensing agreement for permission to use IRI ENSO materials. The CPC/IRI materials are not included in this licensing.

IRI ENSO Forecast

IRI/CPC ENSO Predictions Plume

Published: January 19, 2021

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.


Because of occasional data corrections and late model runs following the time of ENSO product issuance, the data shown in the ENSO forecast table and the ENSO plume graph may not always match. The best source of the ENSO forecast data is http://iri.columbia.edu/~forecast/ensofcst/Data/ensofcst_ALLtoMMYY where MM is the month number and YY is the year.


Seasons (2021 – 2021)
Model JFM FMA MAM AMJ MJJ JJA JAS ASO SON
Dynamical Models
NASA GMAO -2.12 -2.34 -2.20 -1.85 -1.43 -1.06 -0.79
NCEP CFSv2 -1.12 -1.01 -0.79 -0.63 -0.55 -0.55 -0.55
JMA -0.67 -0.50 -0.37 -0.23 -0.10
BCC_CSM11m -0.60 -0.15 0.36 0.91 1.39 1.69 1.75 1.66 1.51
SAUDI-KAU -0.81 -0.53 -0.25 -0.09 -0.05 -0.09 -0.17 -0.25 -0.31
LDEO -0.21 0.09 0.40 0.66 0.74 0.47 -0.02 -0.38 -0.60
AUS-ACCESS -0.67 -0.60 -0.43 -0.23
ECMWF -0.77 -0.61 -0.46 -0.30 -0.20
UKMO -0.88 -0.82 -0.73 -0.58
KMA SNU -0.47 -0.33 -0.20 -0.05 0.12 0.31 0.47 0.62 0.72
IOCAS ICM -0.83 -0.75 -0.58 -0.44 -0.29 -0.17 -0.13 -0.20 -0.33
COLA CCSM4 -1.08 -1.09 -1.03 -0.98 -1.01 -1.15 -1.34 -1.56 -1.75
MetFRANCE -1.22 -1.22 -0.85 -0.78 -0.81 -0.45 -0.28
SINTEX-F -0.47 -0.43 -0.34 -0.26 -0.14 -0.03 0.00 -0.00 -0.01
CS-IRI-MM -0.54 -0.32 -0.15 0.04 0.22 0.38
GFDL CM2.1 -0.38 -0.01 0.31 0.58 0.67 0.56 0.24 -0.14 -0.35
GFDL FLOR -0.55 -0.32 -0.09 0.18 0.48 0.78 0.95 0.95 0.85
CMC CANSIP -0.84 -0.70 -0.62 -0.56 -0.48 -0.43 -0.48 -0.61 -0.75
Average, Dynamical models -0.79 -0.65 -0.45 -0.26 -0.09 0.02 -0.03 0.01 -0.10
Statistical Models
NTU CODA -1.19 -0.93 -0.65 -0.55 -0.33 -0.11 -0.26 -0.60 -0.77
BCC_RZDM -0.99 -0.73 -0.50 -0.27 -0.11 -0.01 -0.02 -0.05 -0.04
CPC MRKOV -0.91 -0.76 -0.61 -0.47 -0.34 -0.25 -0.14 -0.02 0.11
CPC CA -0.79 -0.48 -0.15 0.08 0.23 0.22 0.15 0.18 0.31
CSU CLIPR -0.75 -0.62 -0.50 -0.37 -0.42 -0.48 -0.53 -0.60 -0.66
IAP-NN -0.93 -0.77 -0.59 -0.39 -0.20 -0.06 0.02 0.07 0.12
FSU REGR -0.86 -0.70 -0.57 -0.42 -0.29 -0.19 -0.17 -0.17 -0.18
UCLA-TCD -0.73 -0.50 -0.28 -0.10 0.00 0.04 0.03 -0.01 -0.05
Average, Statistical models -0.89 -0.69 -0.48 -0.31 -0.18 -0.10 -0.11 -0.15 -0.15
Average, All models -0.82 -0.66 -0.46 -0.27 -0.12 -0.03 -0.06 -0.06 -0.12

Discussion of Current Forecasts

Most of the models in the set of dynamical and statistical model predictions issued during mid-December 2020 show moderate La Niña SST conditions for the remainder of 2020, with most dwindling to weak La Niña conditions by late boreal winter, and neutral during spring.  In the most recent week, the SST anomaly in the NINO3.4 region was -1.2 C, indicative of moderate La Niña strength, and -1.3 C for the month of November. As of mid-December the subsurface water temperatures in the eastern equatorial Pacific remain below-average, having been reinforced by the action of the easterly wind anomalies.

All of the dynamical and statistical models predict at least weak La Niña conditions for the Dec-Feb season, decreasing to about 50% by Mar-May and below 50% thereafter. Objective model-based La Niña probabilities are 98% for Dec-Feb, dropping to about 30% by Apr-Jun. Thereafter, neutral conditions become the most likely at 66% confidence in Apr-Jun, and then decaying towards climatological odds,according to this suite of models. Based on the multi-model mean prediction, and the expected skill of the models by start time and lead time, the probabilities (X100) for La Niña, neutral and El Niño conditions (using -0.5C and 0.5C thresholds) over the coming 9 seasons are:

IRI/CPC Mid-Month Model-Based ENSO Forecast Probabilities

Season La Niña Neutral El Niño
JFM 2021 89% 11% 0%
FMA 2021 70% 30% 0%
MAM 2021 45% 55% 0%
AMJ 2021 27% 71% 2%
MJJ 2021 23% 66% 11%
JJA 2021 23% 57% 20%
JAS 2021 26% 53% 21%
ASO 2021 29% 47% 24%
SON 2021 34% 42% 24%

Summary of forecasts issued over last 22 months

The following plots show 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 also 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. The first plot shows forecasts for dynamical models, the second for statistical models, and the third for all models. For less difficult readability, forecasts are shown to a maximum of only the first five lead times. Below the third plot, we provide a mechanism for highlighting the forecasts of one model at a time against a background of more lightly colored lines for all other models.


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.

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 1971-2000 period as the base period, or a period not very different from it.

Please refer to our licensing agreement for permission to use IRI ENSO materials. The CPC/IRI materials are not included in this licensing.

IRI ENSO Forecast

Forecast Probability Distribution Based on the IRI/CPC ENSO Prediction Plume

Published: Jan 19, 2021


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


  • <

    Figure 1

    Figure 1 shows the ensemble mean predictions of each dynamical model, along with the statistical predictions. This plot provides some idea of the disagreement among the individual models, as well as the difference between the mean of the forecasts of dynamical versus statistical models.

  • Figure 2

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

  • Figure 3

    Figure 3, 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.