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
October 2021 Quick Look
Published: October 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-September, SSTs in the east-central Pacific are -0.4 degree C different from average. The evolution of key atmospheric variables is consistent with ENSO-neutral conditions. However, a La Niña Watch remains in effect for Sep 2021. A large majority of the models predict SSTs to cool further through boreal autumn and winter, and then return to ENSO-neutral levels during late spring months. Similar to, the new official CPC/IRI outlook issued earlier this month, this objective outlook calls for La Niña to emerge during Sep-Nov and persist through winter and early spring, with return to ENSO-neutral in late spring and early summer of 2022.
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: October 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 conditions have developed and are expected to continue with an 87% chance of La Niña in December 2021- February 2022.
In the past month, La Niña conditions emerged, as indicated by below-average sea surface temperatures (SSTs) across the central and east-central equatorial Pacific (Fig. 1). In the last week, the Niño-3.4 and Niño-4 index values were -0.6ºC and -0.7ºC, respectively (Fig. 2). The Niño-3 and Niño-1+2 indices were not as cool, with values at -0.3ºC and 0.1ºC. Below-average subsurface temperatures (averaged from 180-100ºW) strengthened significantly in the past month (Fig. 3), as negative anomalies were observed at depth across most of the central and eastern Pacific Ocean (Fig. 4). Low-level easterly wind anomalies and upper-level westerly wind anomalies were observed over most of the equatorial Pacific. Tropical convection was suppressed near and west of the Date Line and enhanced over Indonesia (Fig. 5), while the Southern Oscillation Index and Equatorial Southern Oscillation Index were both positive. Overall, the coupled ocean-atmosphere system was consistent with La Niña conditions.
The IRI/CPC plume average of forecasts for the Niño-3.4 SST index favors La Niña to continue through the fall and winter 2021-22 (Fig. 6). The forecaster consensus also anticipates La Niña to continue through the winter, with ENSO-neutral predicted to return during March-May 2022. Because of the recent oceanic cooling and coupling to the atmosphere, forecasters now anticipate a 57% chance of one season (November-January) reaching -1.0ºC or less in the Niño-3.4 index. Thus, at its peak, a moderate-strength La Niña is favored. In summary, La Niña conditions have developed and are expected to continue with an 87% chance of La Niña in December 2021- February 2022 (click CPC/IRI consensus forecast for the chances in 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. October 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 November 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.
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| SON | 93 | 7 | 0 |
| OND | 93 | 7 | 0 |
| NDJ | 92 | 8 | 0 |
| DJF | 87 | 13 | 0 |
| JFM | 77 | 23 | 0 |
| FMA | 63 | 36 | 1 |
| MAM | 43 | 55 | 2 |
| AMJ | 28 | 64 | 8 |
| MJJ | 23 | 63 | 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: September 20, 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. In February 2021, both datasets were updated using the 1991-2020 climatology period.
Recent and Current Conditions
In mid-September 2021, SSTs remained close to average, across much of the equatorial Pacific Ocean. The August SST anomaly in the NINO3.4 region (5S-5N; 170W-120W) was -0.44 C, and for Jun-Aug it was -0.3 C, while the most recent weekly anomaly was -0.4 C, still within the ENSO-neutral territory. The IRI’s definition of El Niño, like NOAA/Climate Prediction Center’s, requires that the SST anomaly in the NINO3.4 region exceed 0.5 C. Similarly, for La Niña, the anomaly must be -0.5 C or colder. 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 evolution of some key atmospheric variables is also consistent with ENSO-neutral conditions. The traditional and equatorial Southern Oscillation Indices that were in the near-neutral range last month, have now increased to levels outside neutral, similar to values seen during mild La Niña conditions. The Trade Winds near the surface were close to average across most of the eastern Pacific, but were stronger than average to the west of the international date line. The upper-level, westerly wind anomalies that would accompany a large-scale response to La Niña conditions were not noticeable. During August, the sub-surface SST showed cool anomalies in the eastern equatorial Pacific, while weak warm anomalies were observed to the west of the Date line.
In summary, the equatorial Pacific region currently remains in ENSO-neutral conditions. CPC announced a La Niña Watch in July 2021, and this Watch is still in effect for Sep 2021.
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 on 09 September 2021 in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it states that La Niña is favored during the coming Northern Hemisphere winter and into the early spring.
The latest set of model ENSO predictions from mid-September 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. Currently, however, the NASA-GEOS model is not factored into the probabilistic update, even though it appears on the plume-of-models graphic. 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 transitioning from current ENSO-neutral to La Niña is 60% for the Sep-Nov season, while chances for ENSO-neutral are 40%. During the Northern Hemisphere winter, the majority of models, as well as multi-model mean, suggest that tropical Pacific temperatures may cool to La Niña levels. Both dynamical and statistical models agree well this time on the likelihood of a second La Niña. ENSO-neutral again becomes the most likely outcome in 2022, with probabilities exceeding 50% from Feb-Apr onward. El Niño probabilities start at 1% in Nov-Jan and slowly rise to around 20% by the late spring of 2022. 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 indicate that La Niña is the most likely outcome through boreal winter – possibly extending into the spring of 2022. The likelihood for El Niño development remains very low during the entire forecast period.
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.
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| SON | 60 | 40 | 0 |
| OND | 66 | 34 | 0 |
| NDJ | 67 | 32 | 1 |
| DJF | 61 | 37 | 2 |
| JFM | 49 | 48 | 3 |
| FMA | 36 | 60 | 4 |
| MAM | 25 | 70 | 5 |
| AMJ | 16 | 72 | 12 |
| MJJ | 16 | 63 | 21 |
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: September 20, 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.
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| SON | 60 | 40 | 0 |
| OND | 66 | 34 | 0 |
| NDJ | 67 | 32 | 1 |
| DJF | 61 | 37 | 2 |
| JFM | 49 | 48 | 3 |
| FMA | 36 | 60 | 4 |
| MAM | 25 | 70 | 5 |
| AMJ | 16 | 72 | 12 |
| MJJ | 16 | 63 | 21 |
IRI ENSO Forecast
CPC/IRI Official Probabilistic ENSO Forecast
Published: October 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.
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| SON | 93 | 7 | 0 |
| OND | 93 | 7 | 0 |
| NDJ | 92 | 8 | 0 |
| DJF | 87 | 13 | 0 |
| JFM | 77 | 23 | 0 |
| FMA | 63 | 36 | 1 |
| MAM | 43 | 55 | 2 |
| AMJ | 28 | 64 | 8 |
| MJJ | 23 | 63 | 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: September 20, 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 – 2022) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Model | SON | OND | NDJ | DJF | JFM | FMA | MAM | AMJ | MJJ |
| Dynamical Models | |||||||||
| NASA GMAO | -1.49 | -1.96 | -2.10 | -1.80 | -1.39 | -0.97 | -0.65 | ||
| NCEP CFSv2 | -0.67 | -1.04 | -1.32 | -1.39 | -1.27 | -1.05 | -0.71 | ||
| JMA | -0.51 | -0.54 | -0.57 | -0.49 | -0.30 | ||||
| SAUDI-KAU | -0.50 | -0.28 | -0.05 | 0.18 | 0.28 | 0.33 | 0.34 | 0.37 | 0.39 |
| LDEO | -0.13 | -0.13 | -0.11 | 0.02 | 0.17 | 0.25 | 0.26 | 0.23 | 0.25 |
| AUS-ACCESS | -0.87 | -1.07 | -1.13 | -0.97 | |||||
| ECMWF | -0.41 | -0.52 | -0.57 | -0.55 | -0.43 | ||||
| UKMO | -0.81 | -0.91 | -0.88 | -0.73 | |||||
| KMA | -0.81 | -1.03 | -1.03 | -0.91 | -0.82 | ||||
| IOCAS ICM | -0.47 | -0.56 | -0.74 | -0.84 | -0.85 | -0.78 | -0.68 | -0.62 | -0.58 |
| COLA CCSM4 | -0.68 | -1.02 | -1.28 | -1.29 | -1.09 | -0.78 | -0.46 | -0.22 | -0.03 |
| MetFRANCE | -0.60 | -0.71 | -0.81 | -0.81 | -0.56 | -0.51 | -0.32 | ||
| SINTEX-F | -0.60 | -0.54 | -0.41 | -0.23 | -0.07 | 0.07 | 0.16 | 0.30 | 0.46 |
| CS-IRI-MM | -0.49 | -0.65 | -0.75 | -0.69 | -0.48 | -0.21 | |||
| GFDL SPEAR | -0.49 | -0.66 | -0.75 | -0.65 | -0.42 | -0.17 | 0.03 | 0.19 | 0.33 |
| CMC CANSIP | -0.62 | -0.86 | -0.97 | -0.92 | -0.73 | -0.52 | -0.36 | -0.19 | 0.02 |
| Average, Dynamical models | -0.63 | -0.78 | -0.84 | -0.75 | -0.57 | -0.39 | -0.24 | 0.01 | 0.12 |
| Statistical Models | |||||||||
| NTU CODA | -0.67 | -0.69 | -0.76 | -0.83 | -0.79 | -0.60 | -0.37 | -0.18 | 0.01 |
| CPC MRKOV | -0.77 | -0.71 | -0.58 | -0.43 | -0.29 | -0.21 | -0.11 | -0.02 | 0.06 |
| CPC CA | -0.22 | -0.22 | -0.23 | -0.16 | -0.12 | 0.04 | 0.05 | 0.05 | -0.03 |
| CSU CLIPR | -0.52 | -0.41 | -0.30 | -0.19 | -0.13 | -0.06 | 0.00 | -0.01 | -0.01 |
| IAP-NN | -0.72 | -0.80 | -0.82 | -0.78 | -0.68 | -0.52 | -0.35 | -0.19 | -0.06 |
| UCLA-TCD | -0.82 | -0.96 | -1.00 | -0.94 | -0.79 | -0.60 | -0.42 | -0.29 | -0.22 |
| Average, Statistical models | -0.62 | -0.63 | -0.62 | -0.55 | -0.47 | -0.33 | -0.20 | -0.11 | -0.04 |
| Average, All models | -0.63 | -0.74 | -0.78 | -0.70 | -0.54 | -0.37 | -0.22 | -0.04 | 0.04 |
Discussion of Current Forecasts
Most of the models in the set of dynamical and statistical model predictions issued during mid-September 2021 show below-average SST conditions likely to cool further in coming months. During the Sep-Nov through Dec-Feb seasons, La Niña conditions are favored over ENSO-neutral. For Jan-Mar, the odds are more equal. This re-emergence of La Niña is predicted to potentially persist long enough to constitute a La Niña event. In 2022 late spring ENSO-neutral is again predicted as the most likely outcome (60-70%). In the most recent week, the SST anomaly in the NINO3.4 region was -0.4 C, indicative of ENSO-neutral, and -0.44 C for the month of August. As of mid-September, the subsurface water temperatures in the eastern equatorial Pacific are below-average, while above-average temperatures exist to the west; in both cases the temperature anomalies are relatively weak.
Dynamical and statistical models show coherent La Niña conditions with 60% likelihood for the Sep-Nov season, increasing to nearly 70% at the end of the year, and then decreasing again in early 2022. La Niña conditions is more likely than ENSO-neutral during rest of boreal autumn and winter months. 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 -0.5 C and 0.5 C thresholds) over the coming 9 seasons are:
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| SON | 60 | 40 | 0 |
| OND | 66 | 34 | 0 |
| NDJ | 67 | 32 | 1 |
| DJF | 61 | 37 | 2 |
| JFM | 49 | 48 | 3 |
| FMA | 36 | 60 | 4 |
| MAM | 25 | 70 | 5 |
| AMJ | 16 | 72 | 12 |
| MJJ | 16 | 63 | 21 |
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: September 20, 2021
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.
-
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.
-
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.