Record El Niño projected to push global temperatures to 1.91°C above pre-industrial levels

Why it matters

This forecast helps separate how much of the exceptional 2026-2027 warming is due to a natural climate event versus the underlying human-caused trend, which is important for interpreting temperature records and understanding extreme years. It shows that even an unprecedented El Niño occurs on top of an already-elevated baseline from greenhouse warming, demonstrating how natural variability and anthropogenic forcing interact.

What they did

The authors developed TESR, a statistical regression model that relates the El Niño-Southern Oscillation to global mean surface temperatures using monthly data from 1940 to July 2026. They validated the model through walk-forward testing against observations and compared it to a simple trend-ENSO baseline. They then used multi-model seasonal forecasts from August 2026 to project 2026-2027 global temperatures under a scenario of unprecedented El Niño intensity.

Key findings

• Central forecast is 1.91°C above pre-industrial levels in March 2027, with 100 percent probability of exceeding the 1.5°C Paris Agreement threshold from January 2027 onward
• Model attributes approximately 19 percent of the peak warming to the El Niño event, with anthropogenic background warming accounting for 84 percent of the total
• Probability of exceeding the 2.0°C threshold reaches 23-24 percent in March 2027; accounting for historical underestimation of peak temperatures suggests 45-60 percent probability
• Model achieves 47.4 percent reduction in forecast error compared to a simple trend-ENSO model, with a Brier Skill Score of 0.798 for probabilistic forecasts

Limitations

• The projected 2026-2027 ENSO amplitude exceeds the historical calibration range, making this an extrapolation beyond tested conditions
• The model assumes linear ENSO-temperature relationships even at extreme amplitudes where nonlinear saturation might occur
• Only the Niño 3.4 index is used as a predictor; other climate modes like the Pacific Decadal Oscillation and North Atlantic variability are not explicitly represented

Glossary

• GMSTA: Global Mean Surface Temperature Anomaly, the departure of global surface temperature from a reference period
• ENSO: El Niño-Southern Oscillation, a natural cycle of temperature variations in the tropical Pacific Ocean that affects global weather
• Niño 3.4 index: A measure of sea surface temperature in a tropical Pacific region used to define ENSO phases and intensity
• Ridge regression: A statistical technique that uses regularization to reduce overfitting and improve prediction stability