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ENSO Forecast

2015 April Quick Look

Published: April 16, 2015

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 March through early-April 2015 the SST met the threshold for weak Niño conditions. Most of the atmospheric variables now indicate an El Niño pattern, including weakened trade winds, low Southern Oscillation Index and excess rainfall in the vicinity of the dateline. The consensus of ENSO prediction models indicate weak El Niño conditions during the April-June 2015 season in progress, likely strengthening during summer and lasting through 2015.

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

IRI Technical ENSO Update

Published: April 16, 2015

Recent and Current Conditions

The SST anomaly in the NINO3.4 region has been mostly at a weak El Niño level from mid-October through mid-April 2015.  For March the average NINO3.4 SST anomaly was 0.58 C, indicative of weak Niño conditions, and for Jan-Mar it was 0.56 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 0.7 C, in the category of weak El Niño.  Accompanying this SST has been an atmospheric pattern with supporting indications of an El Niño condition, including westerly low-level wind anomalies and positive anomalies of convection in the vicinity of the dateline. The Southern Oscillation Index (SOI) and the equatorial SOI have also been indicative of weak El Niño, with values of roughly -1.0.

Expected Conditions

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 an approximately 70% likelihood for El Niño conditions continuing through summer 2015. The latest set of model ENSO predictions, from mid-April, now available in the IRI/CPC ENSO prediction plume, is discussed below. Currently, Nino3.4 SST anomalies are in the weak El Niño cagtegory. Subsurface temperature anomalies across the eastern equatorial Pacific have increased to well above average levels during the past two months as the downwelling phase of a Kelvin wave has been moving eastward at depth in response to westerly low-level wind anomalies during the last 2 to 3 months.  The positive heat content anomaly may portend increases in SST over the coming few months, and has already been doing so to some degree. In the atmosphere, the basin-wide sea level pressure anomaly pattern (e.g. the SOI) has been at weak El Niño levels, and anomalous convection (as measured by OLR) has been above average near the dateline.  Together, the oceanic and atmospheric features reflect a weak El Niño condition during late March and through mid-April; the ENSO status for the SST alone has been that of weak El Niño for an even longer time period–i.e., over the last five months.

As of mid-April, none of the dynamical or statistical models models predicts La Niña SST conditions for the initial Apr-Jun 2015 season, 75% predicts El Niño conditions, and 25% 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 Jul-Sep 2015 season, among models that do use subsurface temperature information, 95% predicts El Niño SST conditions, 5% predicts ENSO-neutral conditions and none predicts La Niña conditions. For all model types, the probabilities for El Niño are 79% for May-Jul, 83% for Jun-Aug, and 80-89% from Jul-Sep through the end of 2015. No models predict La Niña conditions for any forecast period during 2014. The season having highest probability for El Niño SST conditions is Oct-Dec, when the probability is 89%.

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 less than 2% from Apr-Jun through Aug-Oct 2015, rising to near 5% by Nov-Jan and Dec-Feb 2015-16.  Model probabilities for neutral ENSO conditions are approximately 20% through Nov-Jan 2015-16, rising to 24% for Dec-Feb. Probabilities for El Niño are 80-81% for Apr-Jun through Aug-Oct 2015, dropping to 70-75% from Sep-Nov through Dec-Feb 2015-16. The models collectively favor El Niño over other ENSO conditions by the largest margin during from Apr-Jun through Aug-Oct 2014.  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, weak El Niño conditions for the Apr-Jun and May-Jul seasons, with strengthening El Niño conditions suggested through northern autumn season, reaching moderate strength.  However, model spread is still noteworthy, reflecting the presence of the northern spring ENSO predictability barrier. 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 March 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 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%

 


IRI ENSO Forecast Histogram Image

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

Season La Niña Neutral El Niño
AMJ 2015 ~0% 19% 81%
MJJ 2015 ~0% 20% 80%
JJA 2015 ~0% 19% 81%
JAS 2015 1% 19% 80%
ASO 2015 1% 19% 80%
SON 2015 4% 22% 74%
OND 2015 4% 21% 75%
NDJ 2015 5% 22% 73%
DJF 2015 4% 24% 72%

ENSO Forecast

IRI Model-Based Probabilistic ENSO Forecast

Published: April 16, 2015

A purely objective ENSO probability forecast, based on regression, using as input the model predictions from the plume of dynamical and statistical forecasts shown in the ENSO Predictions Plume. Each of the forecasts is weighted equally. It is updated near or just after the middle of the month, using forecasts from the plume models that are run in the first half of the month. It does not use any human interpretation or judgment. This is updated on the third Thursday of the month.


IRI ENSO Forecast Histogram Image


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

Season La Niña Neutral El Niño
AMJ 2015 ~0% 19% 81%
MJJ 2015 ~0% 20% 80%
JJA 2015 ~0% 19% 81%
JAS 2015 1% 19% 80%
ASO 2015 1% 19% 80%
SON 2015 4% 22% 74%
OND 2015 4% 21% 75%
NDJ 2015 5% 22% 73%
DJF 2015 4% 24% 72%

ENSO Forecast

IRI ENSO Predictions Plume

Published: April 16, 2015

Note on interpreting model forecasts

The following graph and table show forecasts made by dynamical and statistical models for SST in the Nino 3.4 region for nine overlapping 3-month periods. Note that the expected skills of the models, based on historical performance, are not equal to one another. The skills also generally decrease as the lead time increases. Thirdly, forecasts made at some times of the year generally have higher skill than forecasts made at other times of the year--namely, they are better when made between June and December than when they are made between February and May. Differences among the forecasts of the models reflect both differences in model design, and actual uncertainty in the forecast of the possible future SST scenario.

Interactive Chart

You can highlight a specific model by hovering over it either on the chart or the legend. Selecting An item on the legend will toggle the visibility of the model on the page. You can also select DYN MODELS or STAT MODELS to toggle them all at once. Clicking on the "burger" menu above the legend will give you options to download the image or expand to full screen. If you have any feedback on this new feature, please let us know at webmaster@iri.columbia.edu.


List of Models Used


Forecast SST Anomalies (deg C) in the Nino 3.4 Region

Seasons (2015-2015)
Model AMJ MJJ JJA JAS ASO SON OND NDJ DJF
Dynamical models
NCEP CFS version 2 1 1.4 1.7 1.8 2 2.2 2.2 1.8
NASA GMAO model 0.8 1.1 1.4 1.7 1.8 1.8 1.9
Japan Met. Agency model 0.8 1.1 1.3 1.6 1.9
Scripps Inst. HCM 0.5 0.5 0.6 0.6 0.6 0.7 0.7 0.8 0.7
Lamont-Doherty model 0.3 0.3 0.3 0.1 0.1 0.2 0.5 0.7 0.8
POAMA (Austr) model 1 1.1 1.3 1.4 1.4 1.4 1.4
ECMWF model 1 1.3 1.6 1.8 2
UKMO model 1 1 0.9 0.9
KMA (Korea) SNU model 0.5 0.5 0.5 0.5 0.6 0.7 0.6 0.6 0.6
ESSIC Intermed. Coupled model 0.7 0.8 0.7 0.7 0.6 0.6 0.7 0.7 0.6
COLA CCSM3 model 0.8 1.2 1.5 1.6 1.6 1.5 1.5 1.6 1.6
MÉTÉO FRANCE model 0.8 1.1 1.4 1.7 1.8
CSIR-IRI 3-model MME 0.5 0.6 0.8 0.8 0.9 1
GFDL CM2.1 Coupled Climate model 1 1.5 1.8 1.9 1.9 1.8 1.8 1.8 1.7
Canadian Coupled Fcst Sys 0.8 1 1.2 1.3 1.4 1.4 1.5 1.5 1.5
0.9 1.2 1.5 1.7 1.8 1.9 1.9 1.9 1.7
Average, dynamical models 0.8 1 1.2 1.3 1.4 1.3 1.3 1.3 1.1
Statistical models
NCEP/CPC Markov model 0.8 0.8 0.9 1 1.2 1.4 1.6 1.7 1.7
NOAA/CDC Linear Inverse 0.3 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1
NCEP/CPC Constructed Analog 0.3 0.4 0.3 0.2 0.2 0.4 0.6 0.6 0.6
NCEP/CPC Can Cor Anal 0.7 0.8 0.8 0.8 0.8 0.9 1 1 0.8
Landsea/Knaff CLIPER 0 -0.1 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2 -0.2
Univ. BC Neural Network 0.5 0.4 0.6 0.7 0.8 0.9 1.1 1.2 1.2
FSU Regression 0.8 0.8 0.9 0.9 0.9 1 1.2 1.3 1.2
TCD – UCLA 0.9 1 1.1 1.1 1.3 1.4 1.6 1.8 1.9
Average, statistical models 0.5 0.5 0.6 0.6 0.6 0.7 0.9 0.9 0.9
Average, all models 0.7 0.8 1 1 1.1 1.1 1.1 1.1 1

Discussion of Current Forecasts

Most of the set of dynamical and statistical model predictions issued during late March and early April 2015 predict weak El Niño SST conditions continuing through spring 2015. Continuation of El Niño conditions appears approximately 80% likely from the current Apr-Jun 2015 season through to the Jul-Sep seasons, as the average of all models predicts El Niño amplification. Some decrease in the probability of El Niño is predicted after northern summer, but remaining at least 70% through to winter 2015-16.  There is still substantial spread among the individual model predictions, and dynamical models are showing  stronger El Niño predictions than statistical ones. In the most recent week, the SST anomaly in the Nino3.4 region was 0.7 C, reflecting weak El Niño conditions. Most of the atmospheric variables also reflect weak El Niño, including lower and upper level wind anomalies, Southern Oscillation Index and the pattern of anomalous convection. The monthly anomalous SSTs in the Niño3.4 region were 0.56 and 0.58 C for February and March, respectively. 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 Plume-Based ENSO Forecast Probabilities

Season La Niña Neutral El Niño
AMJ 2015 ~0% 19% 81%
MJJ 2015 ~0% 20% 80%
JJA 2015 ~0% 19% 81%
JAS 2015 1% 19% 80%
ASO 2015 1% 19% 80%
SON 2015 4% 22% 74%
OND 2015 4% 21% 75%
NDJ 2015 5% 22% 73%
DJF 2015 4% 24% 72%

Summary of forecasts issued over last 22 months

The following interactive plot shows the model forecasts issued not only from the current month (as in the plot above), but also from the 21 months previous to this month. The observations are shown up to the most recently completed 3-month period. The plots allow comparison of plumes from the previous start times, or examination of the forecast behavior of a given model over time.
Hovering over any single model will highlight that particular model in the chart.
Clicking a particular model will hide/show that model in the chart.
At the bottom of the plot, you can select which models to show in the chart: all the models, the dynamical models only, or the statistical models only.


Notes on the data 

Only models producing forecasts on a monthly basis are included. This means that some models whose forecasts appear in the Experimental Long-Lead Forecast Bulletin (produced by COLA) do not appear in the table.

Once an IRI ENSO probability forecast has been published, the results stand even if a model reports an error and changes their data. When this happens we will update the plume with the model's correct values even though our forecast hasn't changed. What this means is that our forecast is always the same, but the underlying data may be different from what we based our forecast on.

The SST anomaly forecasts are for the 3-month periods shown, and are for the Nino 3.4 region (120-170W, 5N-5S). Often, the anomalies are provided directly in a graph or a table by the respective forecasting centers for the Nino 3.4 region. In some cases, however, they are given for 1-month periods, for 3-month periods that skip some of the periods in the above table, and/or only for a region (or regions) other than Nino 3.4. In these cases, the following means are used to obtain the needed anomalies for the table:

  • Temporal averaging
  • Linear temporal interpolation
  • Visual averaging of values on a contoured map

The anomalies shown are those with respect to the base period used to define the normals, which vary among the groups producing model forecasts. They have not been adjusted to anomalies with respect to a common base period. Discrepancies among the climatological SST resulting from differing base periods may be as high as a quarter of a degree C in the worst cases. Forecasters are encouraged to use the standard 1991-2020 period as the base period, or a period not very different from it.

Historical SST Anomalies Image

New Article

Real-time ENSO forecast skill evaluated over the last two decades, with focus on the onset of ENSO events. Ehsan, M.A., L’Heureux, M.L., Tippett, M.K., Robertson, A.W, Turmelle, J.P., npj Clim Atmos Sci, 2024.

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.

Forecast and model data used in our probabilistic forecast can be accessed by submitting a Request to Access IRI ENSO Data.

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.