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)
During April through mid-May the observed ENSO conditions moved from warm-neutral to the borderline of a weak El Niño condition. Most of the ENSO prediction models indicate a continued warming trend, with a transition to sustained El Niño conditions by the early northern summer.
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.
El Niño/Southern Oscillation (ENSO) Diagnostic Discussion issued by the Climate Prediction Center/NCEP/NWS
Synopsis: Chance of El Niño increases during the remainder of the year, exceeding 65% during summer.
ENSO-neutral continued during April 2014, but with above-average sea surface temperatures (SST) developing over much of the eastern tropical Pacific as well as persisting near the International Date Line (Figure 1). The weekly SST indices were near to slightly above average and increasing in the Niño1+2, Niño3 and Niño3.4 regions, and above average in the Niño4 region (Figure 2). The downwelling phase of a strong oceanic Kelvin wave that began in January greatly increased the oceanic heat content during March and April (Figure 3), and produced large positive subsurface temperature anomalies across the central and eastern Pacific (Figure 4). The upper portion of these subsurface anomalies reached the sea surface, warming the waters east of 125ºW longitude. Also during April, weak low-level westerly wind anomalies were observed over the far western Pacific, while upper-level easterly anomalies occurred over much of the Pacific. Convection was enhanced over the west-central equatorial Pacific (Figure 5). These atmospheric and oceanic conditions collectively indicate a continued evolution toward El Niño.
The model predictions of ENSO for this summer and beyond are indicating an increased likelihood of El Niño compared with those from last month. Most of the models indicate that ENSO-neutral (Niño-3.4 index between -0.5°C and 0.5°C) will persist through part of the remainder of the Northern Hemisphere spring 2014 (Figure 6), most likely transitioning to El Niño during the summer. There remains uncertainty as to exactly when El Niño will develop and an even greater uncertainty as to how strong it may become. This uncertainty is related to the inherently lower forecast skill of the models for forecasts made in the spring. While ENSO-neutral is favored for Northern Hemisphere spring, the chance of El Niño increases during the remainder of the year, exceeding 65% during the summer (click CPC/IRI consensus forecast for the chance of each outcome).
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). Forecasts for the evolution of El Niño/La Niña are updated monthly in the Forecast Forum section of CPC’s Climate Diagnostics Bulletin. The next ENSO Diagnostics Discussion is scheduled for 5 June 2014. 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 |
|---|---|---|---|
| AMJ 2014 | 1% | 58% | 41% |
| MJJ 2014 | 1% | 41% | 58% |
| JJA 2014 | 1% | 32% | 67% |
| JAS 2014 | 2% | 27% | 71% |
| ASO 2014 | 2% | 24% | 74% |
| SON 2014 | 2% | 23% | 75% |
| OND 2014 | 2% | 20% | 78% |
| NDJ 2014 | 3% | 19% | 78% |
| DJF 2014 | 3% | 20% | 77% |
The SST anomaly in the Nino3.4 region in recent weeks has been in the neutral range but rising during the mid-April to mid-May period, 2014. For April the Nino3.4 SST anomaly was 0.24 C, indicative of neutral conditions, and for Feb-Apr it was -0.18 C. 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 SST anomaly in the Nino3.4 region was 0.5 C, which is warmer than the 0.24 C observed in March, and is at the borderline of an El Niño condition if it were to persist. The trend is then an upward one both for Feb-Apr to April, and from April to last week’s observation.
What is the outlook for the ENSO status going forward? The most recent official diagnosis and outlook was issued earlier this month in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it called for a likelihood for neutral ENSO conditions continuing into part of the remainder of spring 2014, but with probabilities of El Niño rising to 67% by Jun-Aug 2014, and to 78% by northern autumn 2014. The latest set of model ENSO predictions, from mid-May, now available in the IRI/CPC ENSO prediction plume, is discussed below. Currently, Nino3.4 SST anomalies are at the borderline of neutral and weak El Niño. Positive anomalies are marked near the dateline and also in the far eastern part of the Pacific basin. Subsurface temperature anomalies across the eastern equatorial Pacific are well above average levels, due to a downwelling Kelvin wave triggered by two westerly wind events in the western tropical Pacific during the Jan-Mar period. These anomalies at depth have been surfacing in the far eastern part of the basin. In the atmosphere, the basin-wide sea level pressure pattern (e.g. the SOI) has been close to average recently. The low-level zonal winds have shown westerly anomalies in portions of the basin, such as somewhat east of the dateline during late April/early May, while the upper level winds have shown easterly anomalies over some longitude bands. Anomalous convection (as measured by OLR) has been positive near the dateline, and just slightly positive in some portions of the basin east of the dateline. Together, these features continue to reflect ENSO conditions near the borderline of neutral and weak El Niño. The hints toward some ocean-atmosphere coupling (westerly wind anomalies and positive SST anomalies in the central equatorial Pacific) could induce larger anomalies in both ocean and low-level atmosphere that could lead to increased coupling as the onset of El Niño conditions likely gets underway over the course of the coming month or two.
As of mid-April, none of the dynamical or statistical models models predicts La Niña SST conditions for the May-Jul 2014 season, 56% predicts El Niño conditions, and 44% indicates neutral ENSO. At lead times of 3 or more months into the future, statistical and dynamical models that incorporate information about the ocean’s observed subsurface thermal structure generally exhibit higher predictive skill than those that do not. For the Aug-Oct 2014 season, among models that do use subsurface temperature information, none predicts ENSO-neutral SSTs, 100% predicts El Niño conditions and none predicts La Niña conditions. For all model types, the probability for neutral ENSO conditions is below 50% for all forecast periods, and is highest (near 40%) for May-Jul 2014 (very beginning of period) and Jan-Mar 2015 (very end of period). Probabilities for El Niño rise to 72% for Jun-Aug and Jul-Sep 2014, and as high as 87% for Sep-Nov, falling to about 60% by Jan-Mar 2015. No model predicts La Niña conditions for any of the 3-month periods between May-Jul and Jan-Mar 2015.
Note – Only models that produce a new ENSO prediction every month are included in the above statement.
Caution is advised in interpreting the distribution of model predictions as the actual probabilities. At longer leads, the skill of the models degrades, and skill uncertainty must be convolved with the uncertainties from initial conditions and differing model physics, leading 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 from that taken verbatim from the raw model predictions.
An alternative way to assess the probabilities of the three possible ENSO conditions is more quantitatively precise and less vulnerable to sampling errors than the categorical tallying method used above. This alternative method uses the mean of the predictions of all models on the plume, equally weighted, and constructs a standard error function centered on that mean. The standard error is Gaussian in shape, and has 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. This method shows probabilities for La Niña no higher than 2% for any period between May-Jul 2014 through Jan-Mar 2015. Model probabilities for neutral ENSO conditions are near 50% for the initial period of May-Jul 2014, near 40% for the next running period of Jun-Aug, and the hover near 30% through the northern summer and fall 2014, rising again to near 35% for Dec-Feb 2013-14 and just over 40% for Jan-Mar 2015. Probabilities for El Niño are just above 50% for May-Jul 2014, rise to near 60% for Jun-Aug, nearly 65% for Jul-Sep, and rise to near 70% for Sep-Nov, Oct-Dec and Nov-Jan 2014-15. It is clear that the models collectively favor El Niño over other ENSO conditions between Jun-Aug 2014 and Dec-Feb 2014-15. 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. The same cautions mentioned above for the distributional count of model predictions apply to this Gaussian standard error method of inferring probabilities, due to differing model biases and skills. 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.
The probabilities derived from the models on the IRI/CPC plume describe, on average, a transition from neutral ENSO conditions during late northern spring to a likely development of El Niño development during May-Jul 2014, as the objective model-based probabilities for El Niño exceed those for neutral ENSO by more than a small margin between Jun-Aug 2014 and Dec-Feb 2014-15. The consensus of model predictions calls for a weak to moderate El Niño event. A caution regarding this latest set of model-based ENSO plume predictions, is that factors such as known specific model biases and recent changes that the models may have missed will be taken into account in the next official outlook to be generated and issued in early October by CPC and IRI, which will include some human judgement in combination with the model guidance.
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| DJF | 37% | 28% | 35% |
| JFM | 34% | 37% | 29% |
| FMA | 30% | 48% | 22% |
| MAM | 26% | 54% | 20% |
| AMJ | 24% | 54% | 22% |
| MJJ | 25% | 51% | 24% |
| JJA | 25% | 50% | 25% |
| JAS | 27% | 46% | 27% |
| ASO | 29% | 40% | 31% |
| SON | 32% | 34% | 34% |
| OND | 34% | 31% | 35% |
| NDJ | 37% | 27% | 36% |
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| MJJ 2014 | ~0% | 50% | 50% |
| JJA 2014 | 1% | 40% | 59% |
| JAS 2014 | 2% | 36% | 62% |
| ASO 2014 | 2% | 31% | 67% |
| SON 2014 | 2% | 29% | 69% |
| OND 2014 | 1% | 29% | 70% |
| NDJ 2014 | 1% | 27% | 72% |
| DJF 2014 | 1% | 33% | 66% |
| JFM 2015 | 2% | 40% | 58% |
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 |
|---|---|---|---|
| MJJ 2014 | ~0% | 50% | 50% |
| JJA 2014 | 1% | 40% | 59% |
| JAS 2014 | 2% | 36% | 62% |
| ASO 2014 | 2% | 31% | 67% |
| SON 2014 | 2% | 29% | 69% |
| OND 2014 | 1% | 29% | 70% |
| NDJ 2014 | 1% | 27% | 72% |
| DJF 2014 | 1% | 33% | 66% |
| JFM 2015 | 2% | 40% | 58% |
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.
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| AMJ 2014 | 1% | 58% | 41% |
| MJJ 2014 | 1% | 41% | 58% |
| JJA 2014 | 1% | 32% | 67% |
| JAS 2014 | 2% | 27% | 71% |
| ASO 2014 | 2% | 24% | 74% |
| SON 2014 | 2% | 23% | 75% |
| OND 2014 | 2% | 20% | 78% |
| NDJ 2014 | 3% | 19% | 78% |
| DJF 2014 | 3% | 20% | 77% |
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.
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.
| Seasons (2014-2015) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Model | MJJ | JJA | JAS | ASO | SON | OND | NDJ | DJF | JFM |
| Dynamical models | |||||||||
| NCEP CFS version 2 | 0.6 | 0.7 | 0.8 | 1 | 1.2 | 1.3 | 1.2 | 1.1 | |
| NASA GMAO model | 0.7 | 0.9 | 1.1 | 1.3 | 1.4 | 1.5 | 1.5 | ||
| Japan Met. Agency model | 0.7 | 0.9 | 1.1 | 1.3 | 1.5 | ||||
| Scripps Inst. HCM | 0.7 | 0.9 | 1 | 1.1 | 1.1 | 1.2 | 1.2 | 1.1 | 1 |
| Lamont-Doherty model | 0.6 | 0.7 | 0.8 | 0.9 | 1 | 1 | 0.9 | 0.7 | 0.5 |
| POAMA (Austr) model | 0.7 | 0.8 | 0.8 | 0.8 | 0.8 | 0.9 | 0.8 | ||
| ECMWF model | 0.9 | 1.1 | 1.3 | 1.5 | |||||
| UKMO model | 0.5 | 0.6 | 0.7 | 0.8 | |||||
| KMA (Korea) SNU model | 0.5 | 0.7 | 0.8 | 1 | 1 | 1 | 0.9 | 0.9 | 0.8 |
| ESSIC Intermed. Coupled model | 0.7 | 0.8 | 0.8 | 0.9 | 1 | 1.1 | 1.1 | 1.1 | 0.8 |
| COLA CCSM3 model | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.5 | 0.4 |
| MÉTÉO FRANCE model | 0.4 | 0.6 | 0.7 | 0.8 | 0.8 | ||||
| CSIR-IRI 3-model MME | 0.4 | 0.5 | 0.5 | 0.5 | 0.6 | 0.8 | |||
| GFDL CM2.1 Coupled Climate model | 0.4 | 0.5 | 0.5 | 0.5 | 0.5 | 0.4 | 0.3 | 0.4 | 0.4 |
| Canadian Coupled Fcst Sys | 0.6 | 0.7 | 0.9 | 1 | 1 | 1 | 1 | 1 | 0.8 |
| GFDL CM2.5 FLOR Coupled Climate model | 0.5 | 0.7 | 0.7 | 0.8 | 0.8 | 0.9 | 0.9 | 0.9 | 0.9 |
| Average, dynamical models | 0.6 | 0.7 | 0.8 | 0.9 | 0.9 | 0.9 | 0.9 | 0.8 | 0.7 |
| Statistical models | |||||||||
| NCEP/CPC Markov model | 0.3 | 0.3 | 0.4 | 0.5 | 0.6 | 0.8 | 0.9 | 0.9 | 0.9 |
| NOAA/CDC Linear Inverse | 0.1 | 0.1 | 0 | 0 | 0 | 0 | 0.1 | 0.1 | 0.1 |
| NCEP/CPC Constructed Analog | 0.3 | 0.4 | 0.4 | 0.4 | 0.5 | 0.7 | 0.7 | 0.6 | 0.5 |
| NCEP/CPC Can Cor Anal | 0.4 | 0.6 | 0.6 | 0.7 | 0.8 | 1 | 0.9 | 0.8 | 0.6 |
| Landsea/Knaff CLIPER | 0.3 | 0.4 | 0.5 | 0.6 | 0.6 | 0.5 | 0.4 | 0.3 | 0.3 |
| Univ. BC Neural Network | 0.2 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.8 |
| FSU Regression | 0.6 | 0.7 | 0.7 | 0.8 | 1 | 1.2 | 1.2 | 1.1 | 0.9 |
| TCD – UCLA | 0.6 | 0.5 | 0.5 | 0.4 | 0.4 | 0.3 | 0.2 | 0.1 | -0.1 |
| Average, statistical models | 0.3 | 0.4 | 0.4 | 0.5 | 0.6 | 0.6 | 0.6 | 0.6 | 0.5 |
| Average, all models | 0.5 | 0.6 | 0.7 | 0.8 | 0.8 | 0.8 | 0.8 | 0.7 | 0.6 |
Most of the set of dynamical and statistical model predictions issued during late April and early May 2014 predict a transition from neutral ENSO conditions to weak El Nino conditions during the last portion of this northern spring 2014 into summer, with a steady warming predicted through summer and into fall 2014. Development of El Nino conditions appears approximately 60% likely by the Jun-Aug season of 2014, and rises to at least 70% by Oct-Dec and Nov-Jan seasons. In the most recent week, the SST anomaly in the Nino3.4 region was 0.5C, reflecting borderline neutral/El Nino conditions. Based on the multi-model mean predictions, and the expected skill of the models by start time and lead time, the probabilities (X100) for La Nina, neutral and El Nino conditions (using -0.5C and 0.5C thresholds) over the coming 9 seasons are:
| Season | La Niña | Neutral | El Niño |
|---|---|---|---|
| MJJ 2014 | ~0% | 50% | 50% |
| JJA 2014 | 1% | 40% | 59% |
| JAS 2014 | 2% | 36% | 62% |
| ASO 2014 | 2% | 31% | 67% |
| SON 2014 | 2% | 29% | 69% |
| OND 2014 | 1% | 29% | 70% |
| NDJ 2014 | 1% | 27% | 72% |
| DJF 2014 | 1% | 33% | 66% |
| JFM 2015 | 2% | 40% | 58% |
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.
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:
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.
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.
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 Fig. 3 relies solely on model output. Figure 1 is updated on this page on the second Thursday of every month.
NOAA/CPC ENSO Forecast Graphic, courtesy of NOAA/CPC
×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 Fig. 4. 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. Figure 3 is updated on the third Thursday of every month.
×Plume of forecasts of the Nino3.4 SST anomaly from dynamical and statistical models that are run during the first half of the month. A probability forecast is generated using all the models in Fig. 4, and is shown in Fig. 3. The average of the forecasts of the dynamical models is shown by the thick yellow line, and of the statistical models by the thick green line. The average of the four models run at the NOAA Climate Prediction center (CPC) is shown by the thick pink line. This figure is updated on the third Thursday of every month. Because forecasts from some models of Fig. 4 are not yet available when the official CPC ENSO probability forecast (Fig. 1) is made, the official forecast uses the previous month's Fig. 4 as one of its inputs, which is shown in the CPC ENSO Diagnostic Discussion.
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