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IRI/CPC ENSO Quick Look | Download PDF version
Technical ENSO Update16 February 2011
Recent and Current ConditionsWeak La Niña conditions emerged in early August 2011, and became weak/moderate strength during northern autumn 2011. As of mid-February 2012, SST anomalies remain in weak to moderate La Niña territory in the central and eastern equatorial Pacific. For January the SST anomaly in the NINO3.4 region was -1.08 C, indicative of weak to moderate La Niña conditions, and for the October-December season the anomaly was -1.06 C. Starting in December 2011, the IRI's definition of El Niño conditions follows that of NOAA/Climate Prediction Center, in which the SST anomaly in the NINO3.4 region (5S-5N; 170W-120W) exceeds 0.45 C. Similarly, for La Niña, the anomaly must be -0.45 C or less. The most recent weekly SST anomaly in the NINO3.4 region is -1.0 C, indicating weak to moderate La Niña conditions in the tropical Pacific; this is about the same as the -1.08 C level observed in January.Expected ConditionsWhat is the outlook for the ENSO status going forward? The official diagnosis and outlook was issued earlier this month in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI. Now, in the middle of January, a new set of model ENSO predictions is available as shown in the IRI/CPC ENSO prediction plume, discussed below. The current La Niña SSTs have continued to be below average, and below average (but now weakening) subsurface temperatures across the equatorial Pacific imply a strong likelihood of maintaining at weak to moderate La Niña conditions in the very short term. Over the coming one to two months, however, a gradual weakening is expected as the subsurface heat content anomalies continue to weaken and the SSTs, low-level winds and convection anomalies begin doing likewise due to the weakening feedbacks between ocean and atmosphere. As of mid-February, most of the dynamical and statistical models
predict La Niña conditions for the Feb-Apr season, with noticeable weakening
beginning toward the end of that period and continuing into the
subsequent seasons of northern spring 2012. For the Feb-Apr season,
69% of the models indicate La Niña conditions, and 31% indicate neutral conditions.
For Mar-May, these figures nearly reverse, to become 38% and 62%, respectively.
At lead times of 4 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. Among models that do use subsurface temperature information,
68% predict ENSO-neutral SSTs for the Jun-Aug 2012 season,
11% predict La Niña conditions, and 21% predict
El Niño conditions.
(Note
1).
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
counting 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 74% for Feb-Apr, decreasing to 42% for Mar-May,
25% for Apr-Jun, and down to 19% by May-Jul.
Model probabilities for El Niño are near
0% for Feb-Apr and Mar-May, 5% for Apr-Jun, and 20% by May-Jul.
Probabilities for ENSO-neutral
conditions are 26% for Feb-Apr, rising to 58% by Mar-May and
70% for Apr-Jun.
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 more than 20 models on the IRI/CPC plume describe a dissipation of the La Niña during the northern spring 2012, with highest liklihood of dissipation in the first half of April. Past experience has shown that some models are biased in the direction of prolonging ENSO episodes for somewhat too long a period at the end of the typical ENSO cycle. If such a bias exists in the present case, this weak to moderate La Niña may end in the February to April timeframe (with greatest likelihood in late March) rather than the March to May timeframe as indicated by the models collectively. Factors such as known model biases and recent changes that the models may have missed will be taken into account in the official outlook, that includes human judgement in combination with the model guidance, generated by IRI/CPC to be issued at the beginning of March. See also: Note 1 - Only models that produce a new ENSO prediction every month are included in the above statement.
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