How the spring predictability barrier impacts La Nina, El Nino forecasts

Have you ever seen an El Niño or La Niña outlook and, several months later, heard that the world is still experiencing those climate patterns, despite forecasts predicting that the event would have ended by now? If so, you’re not alone.

Scientists have coined the term “spring predictability barrier” to describe the challenges in forecasting the rise and fall of the El Niño-Southern Oscillation (ENSO). 

These changes in the ENSO are driven by shifts in water temperature anomalies in the central and eastern Pacific, ranging from cold events, known as La Niñas, to warm cycles, known as El Niños.

This may not sound too complicated to the non-weather enthusiast, but many factors contribute to changes in the ENSO, which result in global weather impacts.

Fluctuations in trade winds, water temperatures, atmospheric pressures, ocean upwelling and even unrelated phenomena like volcanic eruptions all play a role in the status of the oscillation and the weather patterns the world sees.

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Between the two extremes of the ENSO, El Niño occurrences outnumber La Niña events by a factor of three to two, but recent cycles have gone against the norm.

In years when neither event is in control, the pattern is simply referred to as “neutral” or La Nada, with water temperatures at average typical values.

The world can remain in a neutral state for months or even years, and global computer models give forecasters a sense of where the ENSO cycle is heading, with projections that extend outwards a year or even longer.

These models give varying outputs, which can be significantly impacted during the February through May timeframe.

In some years, a model might predict the world will exit La Niña during the spring, but for various reasons, it doesn’t happen until much later in the year – much to the chagrin of weather forecasters.

The opposite can be true for El Niño as well. Models might show an El Niño event ending, but it too can drag on for several months. This is when the “spring predictability barrier” comes into focus.

The world saw an example of running into the spring predictability barrier in 2024, when models predicted a rapid collapse of El Niño, but the event officially didn’t end until later that year.

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So, why does this problem occur, and why is it important?

According to NOAA, El Niño and La Niña events typically reach their peak in the late fall and winter, but models have difficulty determining how these events will decay during the spring. 

The situation is complicated by the Sun’s movement over the Northern Hemisphere as it approaches the summer solstice. 

During this time of the year, regions across the Northern Hemisphere, particularly in the Pacific, heat up, but the exact way in which waters warm is not uniform and changes year over year. 

A lack of observations, similar to the information needed to track hurricanes, may also come into play.

If there is a lack of data from satellites or buoys in the vast stretch of ocean, forecasts become less dependable.

The accuracy of ENSO predictions is crucial because it affects both medium- and long-term weather forecasts. 

The status of ENSO plays a significant role in everything from spring severe weather outbreaks to droughts, famines, hurricanes and winter storms. 

If the ENSO status is different from what was predicted, weather forecasts around the world may not align, leading to impacts.

A La Niña event that began in late 2024 could already be showing signs of encountering the predictability barrier. Some models initially suggested it would last only a few weeks to a few months, but NOAA now indicates it could persist well into the spring before subsiding. 

This could provide yet another example of the spring predictability barrier, where models expected an end to the event before it was ready to conclude.

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NOAA researchers say they have examined possible culprits over the years for what might be behind the model discrepancies but have not been able to pinpoint any one specific reason that impacts forecasts.

“It is harder to predict the start or end of an event than to predict an event that is already occurring. There is also weaker coupling between the ocean-atmosphere in the spring due to a reduction in the average, or climatological, SST gradients in the tropical Pacific Ocean. However, for various reasons, these factors don’t fully explain why we see lower skill,” NOAA forecasters wrote in a blog on the subject.

Additionally, climate change may be playing a significant role, as there are fewer events that start at one extreme and quickly end up in another.