IRI ENSO Forecast
IRI Technical ENSO Update
Published: January 18, 2019
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 often shows stronger anomalies than ERSSTv4, and during very strong events the two datasets may differ by as much as 0.5 C. Additionally, the ERSSTv4 may tend to be cooler than OISSTv2, because ERSSTv4 is expressed relative to a base period that is updated every 5 years, while the base period of OISSTv2 is updated every 10 years and so, half of the time, is based on a slightly older period and does not account as much for the slow warming trend in the tropical Pacific SST.
Recent and Current Conditions
In mid-January 2019, weak El Niño SST conditions were observed in the NINO3.4 region. The December SST anomaly was 1.01 C, at the “bottom” of the moderate El Niño range, and for Oct-Dec it was 0.95 C, indicative of a weak El Niño. 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 0.4, indicating warm-neutral conditions. The band of warmed SST extends somewhat west of the Date Line, making the typical west-to-east SST anomaly gradient weaker than normally seen in an El Niño event. During the most recent week, the strength of the positive SST anomaly has weakened to the east of the dateline, but less so just west of the dateline. Despite the warmed SSTs, many of the key atmospheric variables, such as the lower level zonal wind anomalies, the sea level pressure pattern (e.g., the Southern Oscillation index) and the outgoing longwave radiation pattern (convection), have not suggested El Niño conditions, but rather a continuation of ENSO-neutral conditions. Thus, the coupling of the atmosphere to the oceanic conditions has been largely lacking. The subsurface temperature anomalies across the eastern equatorial Pacific remain above-average, although less strongly so over the last month. These warmed waters at depth extend to the surface, resulting in above-average temperatures, and also presaging likely continuation of above-average SST in the coming one to two months. Given the current El Niño-level SST anomalies and the subsurface profile, even with currently poor atmospheric coupling it appears likely that the SST will continue at least at weak El Niño levels through winter and possibly also through spring. This expectation assumes that the atmosphere will finally begin participating in the event more in the coming month or two.
What is the outlook for the ENSO status going forward? The most recent official diagnosis and outlook was issued approximately one week ago in the NOAA/Climate Prediction Center ENSO Diagnostic Discussion, produced jointly by CPC and IRI; it gave a 65% chance for El Niño continuing through spring. An El Niño watch remains active. The latest set of model ENSO predictions, from mid-January, now available in the IRI/CPC ENSO prediction plume, is discussed below. As of mid-January, more than 90% of the dynamical or statistical models predict El Niño conditions for the initial Jan-Mar and Feb-Apr seasons, with less than 10% showing neutral conditions. After Feb-Apr, the percentage of models forecasting El Niño decreases, dropping to 75% for Apr-Jun, 60% for Jun-Aug and to near 55% for Aug-Oct and Sep-Nov. No model predicts La Niña for any season.
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 near 0% from Jan-Mar through May-Jul, rising only to 6% by Jul-Sep and to 14% by Sep-Nov. Probabilities for neutral conditions begin at 13% for Jan-Mar, rise slowly to 29% for Apr-Jun, and to 35-40% for Jun-Aug through Sep-Nov. Probabilities for El Niño, which begin at 87% for Jan-Mar, drop through the 70-79% range for Mar-May and Apr-Jun, settling to the 50-55% range for Jul-Sep through Sep-Nov. The failure to drop below 50% by early autumn suggests a possibility for a two-year El Niño event. 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 substantial tilt of the odds toward El Niño conditions from Jan-Mar through Mar-May 2019, becoming weaker but still at least 50% through the final season of Sep-Nov. Probabilities for La Niña are close to zero through May-Jul. 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 early next month by CPC and IRI, which will include some human judgment in combination with the model guidance.