ENSO Forecast Navigation

Download the Quicklook PDF

ENSO Forecasts

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

2016 December Quick Look

Published: December 8, 2016

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

During early December 2016 the tropical Pacific SST anomaly was near -0.5C, the threshold for weak La Niña. Also, most of the atmospheric variables across the tropical Pacific have been consistent with weak La Niña conditions, although subseasonal atmospheric variability has temporarily weakened some of them. The upper and lower atmospheric winds have been suggestive of a strengthened Walker circulation, and the cloudiness and rainfall have also been consistent with weak La Niña conditions. The collection of ENSO prediction models indicates SSTs near the threshold of La Niña persisting through mid-winter, then weakening to cool-neutral by later winter.

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 Dec-Feb
  • Typically persist for 9-12 months, though occasionally persisting for up to 2 years
  • Typically recur every 2 to 7 years

Figure 1 is based on a consensus of CPC and IRI forecasters, in association with the official CPC/IRI ENSO Diagnostic Discussion

Figure 3 is purely objective, based on regression, using equally weighted model predictions from the plume

IRI ENSO Forecast

CPC/IRI ENSO Update

Published: December 08, 2016

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 are present, with a transition to ENSO-neutral favored during January-March 2017.

La Niña conditions persisted during November, with negative sea surface temperature (SST) anomalies present across most of the central and eastern equatorial Pacific (Fig. 1). The Niño indices remained negative during November, except for the Niño1+2 index which reflected near-average SSTs in the extreme eastern Pacific late in the month (Fig. 2). Also, the upper-ocean heat content remained below average (Fig. 3) in association with cooler temperatures at depth (Fig. 4), although this cooling lessened somewhat during the month. Atmospheric convection remained suppressed over the central tropical Pacific and enhanced over part of Indonesia (Fig. 5). The low-level easterly winds remained enhanced in the west-central tropical Pacific, and upper-level westerly winds persisted across the tropical Pacific. However, these signals were masked at times by intra-seasonal activity. Overall, the ocean and atmosphere system during November reflected a continuation of weak La Niña conditions.

The multi-model averages favor La Niña (3-month average Niño-3.4 index ≤ -0.5°C) to continue through December – February (DJF) 2016-17 (Fig. 6). Given the current conditions and the model forecasts, the forecaster consensus also favors the continuation of weak La Niña conditions through DJF 2016-17. In summary, La Niña conditions are present, with a transition to ENSO-neutral favored during January – March 2017 (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 outlook will be updated on Thursday December 15th). The current seasonal outlook for DJF 2016-17 favors above-average temperatures and below-median precipitation across much of the southern tier of the U.S., and below-average temperatures and above-median precipitation in portions of the northern tier of the U.S.

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 are also updated monthly in the Forecast Forum section of CPC’s Climate Diagnostics Bulletin. Additional perspectives and analysis are also available in an ENSO blog.

The next ENSO Diagnostics Discussion is scheduled for 12 January 2017. 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.

Climate Prediction Center
National Centers for Environmental Prediction
NOAA/National Weather Service
College Park, MD 20740

CPC/IRI Early-Month Official ENSO Forecast Probabilities

Season La Niña Neutral El Niño
NDJ 2016 62% 38% 0%
DJF 2017 51% 48% 1%
JFM 2017 42% 55% 3%
FMA 2017 33% 62% 5%
MAM 2017 24% 65% 11%
AMJ 2017 21% 63% 16%
MJJ 2017 18% 59% 23%
JJA 2017 17% 57% 26%
JAS 2017 18% 53% 29%

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: November 17, 2016

Note: The SST anomalies cited below refer to the OISSTv2 SST data set, and not ERSSTv4. OISSTv2 is often used for real-time analysis and model initialization, while ERSSTv4 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 usually shows stronger anomalies than ERSSTv4, and during very strong events the two datasets may differ by as much as 0.5 C.

Recent and Current Conditions

ENSO-neutral conditions were observed in most ENSO-related variables from May through July 2016. Then, since August, the NINO3.4 SST anomaly has been slightly cooler than -0.5 C, indicative of a weak La Niña SST condition. For October the SST anomaly was -0.72, and for Aug-Oct it was -0.62 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 anomaly in the Nino3.4 region was -0.7, at a weak La Niña level. Accompanying this ocean condition are atmospheric variables that also indicate weak La Niña. However, the lower-level trade winds have been enhanced only modestly, and mainly only near and west of the date line. Convection anomalies across the equatorial Pacific have been suggestive of La Niña, and the same is true for the Southern Oscillation Index (SOI), but with a recent lull. Overall, given the SST and the roughly consistent atmospheric variables, the diagnosis of weak La Niña is appropriate.

Expected Conditions

What is the outlook for the ENSO status going forward? The most recent official diagnosis and outlook was issued one week ago in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it carries a La Niña advisory and called for a roughly 55% chance for La Niña in winter 2016-17 (i.e., for December-February 2016-17).  The latest set of model ENSO predictions, from mid-November, now available in the IRI/CPC ENSO prediction plume, is discussed below. Currently, the Nino3.4 SST anomalies are at the level of weak La Niña. Subsurface temperature anomalies across the eastern equatorial Pacific continue to be below average. Slightly enhanced easterly trade winds have been observed in the west-central tropical Pacific, suggestive of La Niña, but weakly. The pattern of sea level pressure (e.g., the SOI), the upper level winds, and the pattern of tropical convection have been more suggestive of La Niña, so that overall, the atmosphere and ocean do appear consistent with weak La Niña-like in mid-November. The SST could remain in the weak La Niña category during the rest of 2016 and into the early part of 2017.  The collection of the latest model predictions suggest that weak La Niña conditions are likely to dissipate by late winter.

As of mid-November, 64% of the dynamical or statistical models predicts La Niña conditions for the initial Nov-Jan 2016-17 season, while 36% predict 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 Feb-Apr 2017 season, among models that do use subsurface temperature information, 25% predicts La Niña conditions and 75% predicts ENSO-neutral conditions. For all model types, the probabilities for La Niña are 60-65% for Nov-Jan and Dec-Feb 2016-17, 48% for Jan-Mar 2017, then drop to 20% for Feb-Apr and drop further to about 10% or less from Apr-Jun to Jul-Sep 2017. The probability for neutral conditions is at least 50% beginning in Jan-Mar 2017, and rises to near or above 80% from Feb-Apr to May-Jul 2017, then drops somewhat for later seasons.  Probabilities for El Niño are near zero until Apr-Jun 2017, when they rise to 5%, and then up to around 20% for Jun-Aug and Jul-Sep.

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 at 63% for Nov-Jan 2016-17, decreasing to 53% for Dec-Feb, 42% for Jan-Mar, then droping more quickly and hovering between about 15 and 20% from Mar-May to Jul-Sep 2017. Probabilities for ENSO-neutral are below 50% through Dec-Feb 2016-17, 57% for Jan-Mar, and remain higher than 50% through Jun-Aug 2017. Probabilities for ENSO-neutral reach about 80% for Mar-May.  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.

In summary, the probabilities derived from the models on the IRI/CPC plume describe, on average, a likelihood for La Niña conditions near 50-65% for Nov-Jan and Dec-Feb 2016-17, dropping below 50% for subsequent seasons as the probability for ENSO-neutral rises above 50%.  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.

Climatological Probabilities

Season La Niña Neutral El Niño
DJF 36% 30% 34%
JFM 34% 38% 28%
FMA 28% 49% 23%
MAM 23% 56% 21%
AMJ 21% 58% 21%
MJJ 21% 56% 23%
JJA 23% 54% 23%
JAS 25% 51% 24%
ASO 26% 47% 27%
SON 29% 39% 32%
OND 32% 33% 35%
NDJ 35% 29% 36%

 

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: November 17, 2016



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

Season La Niña Neutral El Niño
NDJ 2016 63% 37% 0%
DJF 2017 53% 47% 0%
JFM 2017 42% 57% 1%
FMA 2017 27% 71% 2%
MAM 2017 16% 80% 4%
AMJ 2017 13% 77% 10%
MJJ 2017 16% 60% 24%
JJA 2017 18% 52% 30%
JAS 2017 20% 48% 32%

IRI ENSO Forecast

CPC/IRI Official Probabilistic ENSO Forecast

Published: December 08, 2016



CPC/IRI Early-Month Official ENSO Forecast Probabilities

Season La Niña Neutral El Niño
NDJ 2016 62% 38% 0%
DJF 2017 51% 48% 1%
JFM 2017 42% 55% 3%
FMA 2017 33% 62% 5%
MAM 2017 24% 65% 11%
AMJ 2017 21% 63% 16%
MJJ 2017 18% 59% 23%
JJA 2017 17% 57% 26%
JAS 2017 18% 53% 29%

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: November 17, 2016

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 (2016-2017)
Model  NDJ DJF  JFM  FMA  MAM  AMJ  MJJ  JJA  JAS
Dynamical models
NASA GMAO model -1.1 -0.9 -0.5 -0.2 0 0.2 0.5
NCEP CFS version 2 -0.6 -0.6 -0.6 -0.4 -0.1 0.1 0.2 0.3
Japan Met. Agency model -0.9 -1 -0.9 -0.6 -0.4
Scripps Inst. HCM -1.1 -1.1 -1.1 -1 -0.9 -0.7 -0.5 -0.3 -0.2
Lamont-Doherty model -0.4 -0.2 0.1 0.3 0.4 0.4 0.3 0.1 -0.2
POAMA (Austr) model -0.7 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2
ECMWF model -0.4 -0.2 0 0.1 0.2
UKMO model -0.6 -0.4 0 0.2
KMA (Korea) SNU model -0.5 -0.4 -0.4 -0.5 -0.5 -0.5 -0.6 -0.6 -0.5
IOCAS (China) Intermed. Coupled model -0.8 -0.7 -0.6 -0.5 -0.4 -0.4 -0.4 -0.5 -0.6
COLA CCSM4 model -0.6 -0.5 -0.4 -0.3 -0.1 0 0.1 0.1 0
MÉTÉO FRANCE model -0.8 -0.6 -0.5 -0.4 -0.3
Japan Frontier Coupled model -0.6 -0.5 -0.5 -0.4 -0.4 -0.3 -0.2 -0.1 0
CSIR-IRI 3-model MME -0.3 -0.6 -0.7 -0.7 -0.6 -0.5
GFDL CM2.1 Coupled Climate model -0.7 -0.6 -0.3 0 0.3 0.6 0.8 1 1.2
Canadian Coupled Fcst Sys -0.4 -0.2 -0.2 -0.1 0 0.3 0.5 0.6 0.7
GFDL CM2.5 FLOR Coupled Climate model -0.8 -0.7 -0.5 -0.3 -0.1 0.2 0.5 0.8 1
Average, dynamical models -0.7 -0.6 -0.5 -0.3 -0.2 -0.1 0.1 0.1 0.2
Statistical models
NCEP/CPC Markov model -0.7 -0.6 -0.5 -0.5 -0.4 -0.4 -0.3 -0.3 -0.3
NOAA/CDC Linear Inverse -0.2 -0.1 0 0.2 0.2 0.2 0.3 0.2 0.2
NCEP/CPC Constructed Analog -0.4 -0.3 -0.2 0 0.1 0.2 0 -0.1 -0.1
NCEP/CPC Can Cor Anal -0.3 -0.3 -0.3 -0.1 0 0.2 0.2 0.2 0.2
Landsea/Knaff CLIPER -0.8 -0.7 -0.6 -0.4 -0.3 -0.2 -0.1 -0.1 0
Univ. BC Neural Network -0.4 -0.2 0 0.1 0.3 0.4 0.4 0.5 0.5
FSU Regression -0.9 -0.9 -0.9 -0.7 -0.4 -0.2 0.1 0.3 0.4
TCD – UCLA -0.6 -0.4 -0.3 -0.1 0 0 0.1 0.1 0.1
Average, statistical models -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.1 0.1
Average, all models -0.6 -0.5 -0.4 -0.3 -0.2 0 0.1 0.1 0.1

Discussion of Current Forecasts

The set of dynamical and statistical model predictions issued during late October and early November 2016 predicts either cool-neutral or weak to weak/moderate La Niña conditions during the November-January period. More models suggest weak La Niña than the other possibilities, and this forecast continues through the northern mid-winter season of DJF. Early in 2017, weakening to cool-neutral ENSO conditions is suggested. In the most recent week, the SST anomaly in the Nino3.4 region was -0.7 C, at a weak La Niña level, and -0.72 C for the month of October, indicating a weak La Niña SST condition. The atmospheric variables also reflect mainly weak La Niña. The trade winds have only been weakly enhanced, while the Southern Oscillation index has been changeable month to month but has averaged somewhat positive. The pattern of convection across the tropical Pacific indicates La Niña. 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 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
NDJ 2016 63% 37% 0%
DJF 2017 53% 47% 0%
JFM 2017 42% 57% 1%
FMA 2017 27% 71% 2%
MAM 2017 16% 80% 4%
AMJ 2017 13% 77% 10%
MJJ 2017 16% 60% 24%
JJA 2017 18% 52% 30%
JAS 2017 20% 48% 32%

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

IRI/CPC ENSO Prediction Plumes Based on the North American Multi-model Ensemble (NMME) + Other Comprehensive Dynamical Models

NMME+ Models not available yet for Dec, 2016