IRI ENSO Forecast
IRI/CPC ENSO Predictions Plume
Published: April 19, 2022
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.
Forecast SST Anomalies (deg C) in the Nino 3.4 Region
|
Seasons (2022 – 2023) |
Model |
AMJ |
MJJ |
JJA |
JAS |
ASO |
SON |
OND |
NDJ |
DJF |
Dynamical Models |
NASA GMAO |
-0.77 |
-1.01 |
-1.14 |
-1.13 |
-1.22 |
-1.35 |
-1.44 |
|
|
NCEP CFSv2 |
-1.08 |
-1.19 |
-1.21 |
-1.10 |
-1.01 |
-1.03 |
-1.05 |
|
|
JMA |
-0.79 |
-0.69 |
-0.58 |
-0.50 |
-0.50 |
|
|
|
|
BCC_CSM11m |
-0.36 |
0.12 |
0.54 |
0.76 |
0.83 |
0.86 |
0.94 |
1.11 |
1.30 |
SAUDI-KAU |
-0.86 |
-0.72 |
-0.61 |
-0.60 |
-0.58 |
-0.55 |
-0.45 |
-0.25 |
0.05 |
LDEO |
-0.65 |
-0.46 |
-0.25 |
-0.13 |
-0.13 |
-0.17 |
-0.18 |
-0.29 |
-0.46 |
AUS-ACCESS |
-0.58 |
-0.40 |
-0.23 |
-0.17 |
|
|
|
|
|
ECMWF |
-0.70 |
-0.54 |
-0.36 |
-0.28 |
-0.31 |
|
|
|
|
UKMO |
-0.71 |
-0.59 |
-0.49 |
-0.47 |
|
|
|
|
|
KMA |
-0.25 |
-0.15 |
-0.06 |
-0.11 |
-0.02 |
|
|
|
|
IOCAS ICM |
-0.92 |
-0.96 |
-1.02 |
-1.12 |
-1.29 |
-1.54 |
-1.79 |
-2.01 |
-2.16 |
COLA CCSM4 |
-0.82 |
-0.90 |
-1.04 |
-1.17 |
-1.30 |
-1.41 |
-1.46 |
-1.34 |
-1.01 |
MetFRANCE |
-1.16 |
-1.14 |
-0.87 |
-0.61 |
-0.48 |
-0.55 |
-0.66 |
|
|
SINTEX-F |
-0.42 |
-0.31 |
-0.11 |
0.02 |
0.07 |
0.12 |
0.19 |
0.29 |
0.41 |
CS-IRI-MM |
-0.48 |
-0.35 |
-0.23 |
-0.24 |
-0.30 |
-0.46 |
|
|
|
GFDL SPEAR |
-0.54 |
-0.35 |
-0.21 |
-0.20 |
-0.32 |
-0.46 |
-0.52 |
-0.40 |
-0.14 |
CMC CANSIP |
-0.80 |
-0.61 |
-0.40 |
-0.30 |
-0.35 |
-0.49 |
-0.59 |
-0.60 |
-0.50 |
Average, Dynamical models |
-0.699 |
-0.603 |
-0.486 |
-0.432 |
-0.460 |
-0.586 |
-0.638 |
-0.436 |
-0.314 |
Statistical Models |
NTU CODA |
-0.59 |
-0.40 |
-0.18 |
-0.12 |
-0.24 |
-0.41 |
-0.23 |
-0.23 |
-0.25 |
BCC_RZDM |
-0.95 |
-0.84 |
-0.80 |
-0.88 |
-1.08 |
-1.27 |
-1.48 |
-1.61 |
-1.57 |
CPC MRKOV |
-0.91 |
-0.75 |
-0.65 |
-0.56 |
-0.46 |
-0.37 |
-0.24 |
-0.06 |
0.11 |
CPC CA |
-0.56 |
-0.46 |
-0.36 |
-0.36 |
-0.33 |
-0.32 |
-0.27 |
-0.20 |
-0.02 |
CSU CLIPR |
-0.65 |
-0.64 |
-0.62 |
-0.61 |
-0.59 |
-0.57 |
-0.55 |
-0.50 |
-0.45 |
IAP-NN |
-0.78 |
-0.62 |
-0.46 |
-0.30 |
-0.13 |
0.04 |
0.17 |
0.24 |
0.26 |
UCLA-TCD |
-0.59 |
-0.48 |
-0.49 |
-0.59 |
-0.75 |
-0.89 |
-0.97 |
-0.95 |
-0.83 |
Average, Statistical models |
-0.718 |
-0.599 |
-0.509 |
-0.489 |
-0.511 |
-0.542 |
-0.510 |
-0.473 |
-0.392 |
Average, All models |
-0.705 |
-0.601 |
-0.493 |
-0.449 |
-0.476 |
-0.569 |
-0.588 |
-0.453 |
-0.351 |
Discussion of Current Forecasts
The majority of both dynamical and statistical model forecasts issued in mid-April 2022 indicate a below-normal SST anomalies in the equatorial Pacific and a continuation of current La Niña event until May-Jul of 2022. The odds are near-equal for a continuation of the weak La Niña or transition to ENSO-neutral afterwards, indicative of large uncertainty in current forecast. 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, ENSO-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 |
AMJ |
80 |
20 |
0 |
MJJ |
61 |
39 |
0 |
JJA |
49 |
49 |
2 |
JAS |
47 |
48 |
5 |
ASO |
49 |
44 |
7 |
SON |
54 |
38 |
8 |
OND |
54 |
36 |
10 |
NDJ |
48 |
38 |
14 |
DJF |
43 |
42 |
15 |
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.