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IRI ENSO Forecast

2015 January Quick Look

Published: January 15, 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)

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

During December 2014 through early January 2015 the SST exceeded thresholds for weak Niño conditions, although the anomaly level has weakened recently. Meanwhile, only some of the atmospheric variables indicate an El Niño pattern. Most of the ENSO prediction models indicate weak El Niño conditions during the January-March season in progress, continuing through most or all of northern spring 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 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: January 8, 2015

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: El Niño Watch

Synopsis: There is an approximately 50-60% chance of El Niño conditions during the next two months, with ENSO-neutral favored thereafter.

During December 2014, positive sea surface temperature (SST) anomalies decreased across the central and east-central equatorial Pacific (Fig. 1). At the end of the month, the weekly Niño indices ranged from +0.8°C in the Niño-4 region, to +0.5°C in the Niño-3.4 region, to 0.0°C in the Niño-1+2 region (Fig. 2). The positive subsurface heat content anomalies (averaged between 180º-100ºW) also decreased during December (Fig. 3) in response to an upwelling equatorial oceanic Kelvin wave (Fig. 4). Although the surface and sub-surface temperature anomalies were consistent with El Niño, the overall atmospheric circulation continued to show only limited coupling with the anomalously warm water. The equatorial low-level winds were largely near average during the month, while upper-level easterly anomalies continued in the central and eastern tropical Pacific. The Southern Oscillation Index (SOI) remained slightly negative, but the Equatorial SOI remained near zero. Also, rainfall remained below-average near the Date Line and was above-average over Indonesia (Fig. 5). Overall, the combined atmospheric and oceanic state remains ENSO-neutral.

Similar to last month, most models predict the SST anomalies to remain at weak El Niño levels (3-month values of the Niño-3.4 index between 0.5°C and 0.9°C) during December-February 2014-15, and lasting into the Northern Hemisphere spring 2015 (Fig. 6). If El Niño were to emerge, the forecaster consensus favors a weak event that ends in early Northern Hemisphere spring. In summary, there is an approximately 50-60% chance of El Niño conditions during the next two months, with ENSO-neutral favored thereafter (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 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 5 February 2015. 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 Consensus ENSO Forecast Probabilities

 

Season La Niña Neutral El Niño
DJF 2014 ~0% 38% 62%
JFM 2015 1% 49% 50%
FMA 2015 1% 52% 47%
MAM 2015 2% 53% 45%
AMJ 2015 3% 53% 44%
MJJ 2015 6% 53% 41%
JJA 2015 7% 53% 40%
JAS 2015 10% 52% 38%
ASO 2015 13% 49% 38%


Figure 7. NCEP CFSv2 forecasts of sea surface temperature (SST) anomalies for the Niño 3.4 region (5°N-5°S, 120°W-170°W). Figure updated 3 November 2014.

IRI ENSO Forecast

IRI Technical ENSO Update

Published: January 15, 2015

Recent and Current Conditions

The SST anomaly in the NINO3.4 region has been at the weak El Niño level from mid-October to the end of December, and even reached the borderline of moderate El Niño for a single week at the end of November.  For December the average NINO3.4 SST anomaly was 0.78 C, indicative of weak Niño conditions, and for Oct-Dec it was 0.71 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 0.4 C, in the category of warm-neutral for SST.  This was the first week since mid-October that the SST was below 0.5 C. Accompanying this SST mainly above the El Niño threshold has been an atmospheric pattern with inadequate indication of an El Niño-like pattern–very weak westerly low-level wind anomalies and no positive anomalies of convection near the dateline. Some indicators, however, such as the Southern Oscillation Index (SOI), have been somewhat indicative of weak El Niño, and the upper level wind anomalies have also been showing El Niño-indicative enhanced easterlies.

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 a 50-60% likelihood for El Niño conditions during January and February, followed by a greater than 50% chance for ENSO-neutral beginning in March.  The latest set of model ENSO predictions, from mid-January, now available in the IRI/CPC ENSO prediction plume, is discussed below. Currently, Nino3.4 SST anomalies are near the borderline of warm-neutral and weak El Niño conditions. Subsurface temperature anomalies across the eastern equatorial Pacific have remained above average, but have weakened considerably during December and the first half of January. In the atmosphere, the basin-wide sea level pressure pattern (e.g. the SOI) has been weakly negative (in neighborhood of -0.5) over the last month, suggestive of borderline El Niño conditions at best.  Also, other atmospheric parameters continue to reflect neutral ENSO conditions: Weak anomalous low-level westerlies have only appeared at times during the last month or two, but interestingly have recently appeared in the western tropical Pacific and could potentially induce a weak downwelling Kelvin wave that might reinforce some warming at the surface in the coming few months. Upper level anomalous easterly anomalies have been observed over part of the equatorial Pacific, indicative of El Niño, but have been less clear in recent weeks. But perhaps more importantly, anomalous convection (as measured by OLR) has been near average, or even below average, near and eastward of the dateline.  Together, the oceanic and atmospheric features reflect a warmish but neutral ENSO condition, despite the clearly weak El Niño status of the SST (except for the very latest week) during the last nearly three months.

As of mid-January, none of the dynamical or statistical models models predicts La Niña SST conditions for the initial Jan-Mar 2015 season, 74% predicts El Niño conditions, and 26% 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 Apr-Jun 2015 season, among models that do use subsurface temperature information, 72% predicts El Niño SST conditions, 28% predicts ENSO-neutral conditions and none predicts La Niña conditions. For all model types, the probabilities for El Niño are 61% for Feb-Apr, between 50% and 60% between Mar-May and May-Jul, and drop to below 50% from Jun-Aug until the final forecast season of Sep-Nov. No model predicts La Niña conditions for any of the 3-month periods between Jan-Mar and Aug-Oct 2015, but 6% of the models (i.e., one model) predicts La Niña conditions for Sep-Nov.

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 near 0% from Mar-May 2015 through Apr-Jun, rising to 6% by Jun-Aug and up to 20% by Sep-Nov.  Model probabilities for neutral ENSO conditions are 36% for the initial period of Mar-May 2015, 42% for the next running period of Feb-Apr 2015, between 44% and 47% between Mar-May and Jul-Sep and near 40% for Aug-Oct and Sep-Nov. Probabilities for El Niño are 64% for Jan-Mar 2015, 58% for Feb-Apr, and slowly decrease from 55% to 50% from Mar-May to Jun-Aug. After Jun-Aug, probabilities for El Niño drop through the 41% to 47% interval through the final season of Sep-Nov. The models collectively favor El Niño over other ENSO conditions by a large margin only for Jan-Mar 2015.  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, El Niño conditions for the Jan-Mar 2015 season currently in progress, likely enduring well into northern spring season of 2015. The consensus of model predictions calls for a weak El Niño event, as already seen in the SST anomalies over the last two to three months. 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 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

IRI/CPC Plume-Based Probabilistic ENSO Forecast

Published: January 15, 2015



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

Season La Niña Neutral El Niño
JFM 2015 ~0% 36% 64%
FMA 2015 ~0% 42% 58%
MAM 2015 ~0% 45% 55%
AMJ 2015 ~0% 47% 53%
MJJ 2015 3% 45% 52%
JJA 2015 6% 44% 50%
JAS 2015 9% 44% 47%
ASO 2015 13% 41% 46%
SON 2015 20% 39% 41%

IRI ENSO Forecast

CPC/IRI Consensus Probabilistic ENSO Forecast

Published: January 8, 2015



CPC/IRI Early-Month Consensus ENSO Forecast Probabilities

 

Season La Niña Neutral El Niño
DJF 2014 ~0% 38% 62%
JFM 2015 1% 49% 50%
FMA 2015 1% 52% 47%
MAM 2015 2% 53% 45%
AMJ 2015 3% 53% 44%
MJJ 2015 6% 53% 41%
JJA 2015 7% 53% 40%
JAS 2015 10% 52% 38%
ASO 2015 13% 49% 38%

IRI ENSO Forecast

IRI/CPC ENSO Predictions Plume

Published: January 15, 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.


Seasons (2015-2015)
Model JFM FMA MAM AMJ MJJ JJA JAS ASO SON
Dynamical models
NCEP CFS version 2 0.4 0.5 0.6 0.8 1 1.4 1.6 1.9
NASA GMAO model 0.7 0.7 0.7 0.7 0.7 0.7 0.5
Japan Met. Agency model 0.5 0.4 0.4 0.4 0.4
Scripps Inst. HCM 0.9 0.8 0.6 0.5 0.5 0.5 0.6 0.6 0.7
Lamont-Doherty model 0.8 0.8 0.8 1 1.2 1.2 1.2 1.1 1.1
POAMA (Austr) model 0.4 0.4 0.5 0.6 0.6 0.7 0.7
ECMWF model 0.8 0.7 0.7 0.9
UKMO model 0.3 0 -0.2 -0.1
KMA (Korea) SNU model 0.7 0.7 0.6 0.6 0.6 0.5 0.5 0.4 0.4
ESSIC Intermed. Coupled model 0.6 0.6 0.6 0.5 0.5 0.4 0.3 0.3 0.2
COLA CCSM3 model 1.1 1.2 1.2 0.9 0.6 0.3 0 -0.2 -0.5
MÉTÉO FRANCE model 0.6 0.6 0.7 0.7 0.8
CSIR-IRI 3-model MME 0.5 0.4 0.3 0.3 0.2 0.2
GFDL CM2.1 Coupled Climate model 0.6 0.8 0.9 1 1 0.9 0.6 0.4 0.2
Canadian Coupled Fcst Sys 0.5 0.5 0.6 0.6 0.7 0.8 0.7 0.6 0.6
GFDL CM2.5 FLOR Coupled Climate model 0.7 0.8 0.9 0.9 0.9 0.8 0.6 0.5 0.4
Average, dynamical models 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.6 0.4
Statistical models
NCEP/CPC Markov model 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.4 0.5
NOAA/CDC Linear Inverse 0.5 0.4 0.2 0.1 0 -0.1 -0.1 -0.1 -0.1
NCEP/CPC Constructed Analog 0.5 0.3 0.2 0.2 0.2 0.1 0.1 0.1 0.2
NCEP/CPC Can Cor Anal 0.5 0.4 0.4 0.4 0.3 0.4 0.4 0.4 0.4
Landsea/Knaff CLIPER 0.5 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2
Univ. BC Neural Network 0.7 0.6 0.6 0.5 0.4 0.4 0.4 0.4 0.4
FSU Regression 0.6 0.5 0.4 0.4 0.3 0.2 0.2 0.2 0.2
TCD – UCLA 0.7 0.6 0.4 0.2 0 -0.1 -0.2 -0.2 -0.3
Average, statistical models 0.6 0.4 0.3 0.3 0.2 0.2 0.2 0.2 0.2
Average, all models 0.6 0.6 0.5 0.5 0.5 0.5 0.5 0.4 0.3

Discussion of Current Forecasts

Most of the set of dynamical and statistical model predictions issued during late December 2014 and early January 2015 predict weak El Niño conditions through the rest of northern winter 2014-15 and continuing through much or all of spring 2015. Existence of El Niño conditions appears approximately 60-65% likely for the Jan-Mar 2015 season, about 55% likely for the Feb-Apr and Mar-May 2015 seasons, and drops to 50-55% for Apr-Jun and May-Jul. In the most recent week, the SST anomaly in the Nino3.4 region was 0.4 C, reflecting warm-neutral to borderline El Niño conditions. Some atmospheric variables do not reflect El Niño, however. The monthly anomalous SSTs in the Niño3.4 region were 0.85 and 0.78 C for November and December, 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
JFM 2015 ~0% 36% 64%
FMA 2015 ~0% 42% 58%
MAM 2015 ~0% 45% 55%
AMJ 2015 ~0% 47% 53%
MJJ 2015 3% 45% 52%
JJA 2015 6% 44% 50%
JAS 2015 9% 44% 47%
ASO 2015 13% 41% 46%
SON 2015 20% 39% 41%

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.