The first quarter of 2026 ranked as the fourth-warmest on record globally, despite the presence of a weak La Niña that typically cools the planet. Arctic sea ice cover also reached record lows for the period, underscoring the accelerating pace of climate change. Now, scientists warn that a powerful El Niño event expected to arrive by early autumn could push 2026 into the history books as the second-warmest year ever measured.
According to an analysis by Carbon Brief, which draws on temperature datasets from five independent research groups, there is a 19 percent chance that 2026 will surpass 2024 as the warmest year on record. The analysis is virtually certain that 2026 will rank among the four warmest years, with the most likely outcome being second place.
What Makes This El Niño Different?
El Niño, the warming phase of the El Niño-Southern Oscillation (ENSO) in the tropical Pacific, influences weather patterns across the globe, often triggering droughts, floods, and marine heatwaves. The standard measure is the temperature anomaly in the Niño3.4 region of the equatorial Pacific. Sustained sea surface temperatures above 0.5°C indicate an El Niño; above 1.5°C, a strong event; and above 2°C, what scientists call a “super” El Niño.
Carbon Brief reports that the latest climate models yield a median estimate of 2.2°C warming by September 2026, firmly in super El Niño territory. Warming is expected to intensify after September, as El Niño conditions typically peak between November and January. Should a super event materialize, it would substantially increase the chance that 2027 becomes the warmest year on record, according to the analysis.
A New Forecasting Tool
Historically, predicting El Niño strength more than a few months ahead has been challenging. Most forecast systems rely on computationally expensive dynamical climate models, statistical models built on decades of ENSO research, or AI approaches that require vast training data and are often hard to interpret physically.
Researchers at the University of Hawai'i at Mānoa have published a study in Geophysical Research Letters that offers a simpler, data-driven alternative. Lead author Yuxin Wang explains that the model uses two core “climate memories” discovered decades ago: sea level changes in the tropical Pacific, which reveal heat build-up, and global sea surface temperature anomalies outside the tropical Pacific. By feeding historic data into a computer model, the team tested whether it could have accurately predicted the Niño3.4 index over the past six decades. “We found that it can predict El Niño and La Niña surprisingly well, with useful skill up to about 15 months ahead,” Wang said.
The model currently forecasts a strong El Niño, more than 2°C warmer than normal over the equatorial eastern Pacific, toward the end of 2026. “Accurately predicting ENSO more than a year in advance is important because it can provide early warning, allowing communities, governments, and resource managers to take actions and make adaptations to reduce the potential impacts from El Niño and La Niña,” Wang added.
European Implications
For Europe, a super El Niño carries distinct risks. While the continent is not directly in the tropical Pacific, ENSO events can disrupt atmospheric circulation, altering rainfall patterns and temperatures across the Mediterranean, the Balkans, and northern Europe. Warmer winters and increased storm activity in some regions, coupled with drought risks in others, could strain water resources and agriculture. The early warning provided by the new model could help national meteorological services in countries like France, Germany, and Italy prepare contingency plans.
The broader context is that 2026 is unfolding against a backdrop of record global warmth. The weak La Niña at the start of the year did little to offset the long-term warming trend, and the projected super El Niño threatens to amplify it. As European policymakers debate climate adaptation strategies, the prospect of back-to-back record-warm years underscores the urgency of both mitigation and preparedness.
