October Climate Briefing: La Niña Comes Knocking
Read our ENSO Essentials & Impacts pages for more about El Niño and La Niña.
In mid-October, the tropical Pacific sea-surface temperatures were well below average and into the moderate strength La Niña range. All atmospheric parameters also indicated La Niña conditions. A new set of model runs predicts moderate or possibly strong La Niña conditions through 2020 and most of winter, with a 90% probability for La Niña for winter. This outlook is similar to that of the official ENSO forecast issued September 10, which used both models and human judgement, and which carries a La Niña advisory.
Weston Anderson provides the briefing summary:
See below for tweets summarizing the current ENSO situation.
To predict ENSO conditions, computers model the SSTs in the Niño3.4 region over the next several months. The plume graph below shows the outputs of these models, some of which use equations based on our physical understanding of the system (called dynamical models), and some of which use statistics, based on the long record of historical observations.
The La Niña odds are lower in the official probabilistic forecast issued by the U.S. Climate Prediction Center (CPC) and IRI in early October than in the mid-month IRI/CPC forecast. The earlier forecast uses human judgement in addition to model output, while the mid-month forecast relies solely on model output. More on the difference between these forecasts in this IRI Medium post.
ENSO in context: Resource page on climate variability
IRI’s Global Seasonal Forecasts
Each month, IRI issues seasonal climate forecasts for the entire globe. These forecasts take into account the latest model outputs and indicate which areas are more likely to see above- or below-normal temperatures and precipitation.
All forecast maps, including temperature in addition to precipitation, and also including a description of the methodologies, are available on our seasonal forecast page. Additional forecast formats, such as our flexible forecast maproom, are available in the IRI Data Library.