Strong El Niño events are mostly a mix of eastern and central Pacific warming

Why it matters

Strong El Niño events have large global climate effects. Knowing that most of them are a mix of two patterns, not purely eastern or central, changes how researchers should classify and study them. The projected rise in strong mixed events may help guide work on ENSO under climate change.

What they did

The authors split Pacific sea surface temperature into an eastern (E) and a central (C) component. They used a regression on E- and C-indices, with 12-year running windows, and applied it to observations since 1940. They then applied it to 45 CMIP6 climate models under the SSP585 high-emission scenario. They compared the 20th and 21st centuries and tested the changes by bootstrap resampling.

Key findings

• Four of the five strong El Niño events (1972–73, 1982–83, 1997–98, 2015–16, 2023–24) were mixed-type.
• The E-component supplies 6.4% of moderate events but 46.8% on average in strong events. The C-component supplies 85.8% in moderate events and 52.0% in strong ones.
• The C-component develops from subtropical signals up to 9 months ahead. The E-component builds quickly from equatorial winds and thermocline changes, with no such early signal.
• In the models, strong mixed-type events rise by 33.5%, from 3.11 to 4.16 per century. Strong El Niño events overall rise by about 43.6%.
• Strong EP events grow fastest in relative terms, by 110.9%. Mixed-type events still make the largest share of the increase in strong events, about 47.8%.

Limitations

• Only five strong events exist in the observed record, so the shares for strong events have wide uncertainty.
• CMIP6 models do not capture the observed La Niña-like cooling and decadal variability such as the PDO, so the projection needs further study.
• Of 45 models, only 24 project more strong mixed-type events, and the choice of 80% significance and a 12-year window affects the method.

Glossary

• Mixed-type El Niño: An El Niño with warming in both the central and eastern Pacific.
• BCLR: Binary combined linear regression, the authors’ method for splitting SST into E-component, C-component and non-ENSO parts.
• CMIP6: A coordinated set of climate model experiments used to project future climate.
• Thermocline: The ocean layer where temperature drops quickly with depth.