IRI ENSO Forecast
IRI Technical ENSO Update
Published: June 19, 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-May 2019, weak El Niño SST conditions were observed in the NINO3.4 region. The May SST anomaly was 0.71 C, in the weak El Niño range, and for Mar-May it was 0.85 C, also 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 0.7 C, indicating weak El Niño conditions. Since late January some important atmospheric variables became El Niño-like, including on-and-off westerly low-level zonal wind anomalies and above-average convection near the dateline. In the latest month anomalous westerly wind anomalies took place in the western tropical Pacific, while the convection near the dateline has somewhat subsided. The subsurface temperature anomalies across the eastern equatorial Pacific weakened markedly to just slightly above average in the last month, but in the last week or two have risen again slightly in response to the anomalous westerly wind event which has now ended.
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 66% chance for El Niño for this northern summer season, dropping to 50-55% for lasting through winter season. An El Niño advisory is in effect. The latest set of model ENSO predictions, from mid-June, now available in the IRI/CPC ENSO prediction plume, is next discussed: As of mid-June, 81% of the dynamical or statistical models predict El Niño conditions for the Jun-Aug as well as the Jul-Sep seasons. After Jul-Sep, the percentage of models forecasting El Niño slightly decreases, maintaining levels between 72% and 78% all the way through to Feb-Apr 2020. No model predicts La Niña, except for Nov-Jan and Dec-Feb, when one model (5% of total) does so. Probabilities for neutral conditions hover in the 19-28% range throughout the forecast period.
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 below 10% for all forecast seasons, peaking at 7% for Oct-Dec. Probabilities for neutral conditions begin at 35% for Jun-Aug, rise to 40-42% for Jul-Sep and Aug-Oct, and then settle in the 32-37% range for the remainder of the forecast period to Feb-Apr 2020. Probabilities for El Niño begin at 65% for Jun-Aug, decline to the 56-59% range from Jul-Sep to Oct-Dec, and then rise again to 60-65% for Nov-Jan through the final season of Feb-Apr. 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 tilt of the odds toward El Niño conditions from Jun-Aug through Feb-Apr 2020, with slightly weaker tilts from Jul-Sep to Sep-Nov. Probabilities for La Niña are no higher than 7% through Jul-Sep. 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.
IRI/CPC Mid-Month Model-Based ENSO Forecast Probabilities