Hot Start, Delayed GMST Peak: Key-Window Ocean Heat and Super El Niño Shape 2026 Record Risk
Strong El Niño events are among the most influential phenomena of interannual climate variability, raising global mean surface temperature (GMST) and triggering widespread climate extremes (Hu and Fedorov 2017).Superimposed on the persistent global warming, the 2023/24 strong El Niño contributed to record-breaking GMSTs in two successive years, underscoring the capacity of strong El Niño events to push climate risks into unprecedented territory.A similar concern has emerged in 2026.Following the decay of La Niña, anomalously warm water propagated rapidly eastward in April 2026, and then El Niño conditions developed by mid-year.Recent forecasts indicate a likely exceptionally strong event during boreal autumn-winter, with some models forecasting a Niño 3.4 index greater than 3.0 °C (Lian et al. 2026; Liu et al. 2026; https://iri.columbia.edu/our-expertise/climate/forecasts/enso/current/?enso_tab=enso-sst_table).This would imply a quick recurrence of a strong El Niño only three years after the 2023/24 event.However, the associated GMST response cannot be inferred from peak Niño-3.4intensity alone, because it also depends on event evolution, persistence, ocean heat buildup and redistribution, and lagged ocean-atmosphere-land adjustments.Assessments available by mid-2026 have therefore reached different conclusions about the possible 2026 GMST outcome, ranging from a low probability of a new annual record to a substantial chance that 2026 will approach or exceed previous record levels (Liu et al., 2026;
Authors
- Tao Lian (ORCID: https://orcid.org/0000-0002-7438-4110)
- Kexin Li (ORCID: https://orcid.org/0000-0001-9330-7279)
- Fei Zheng (ORCID: https://orcid.org/0000-0001-6135-6148)
Institutions
- Chinese Academy of Sciences (CN)
- Ministry of Natural Resources (CN)
- Second Institute of Oceanography (CN)
- Institute of Atmospheric Physics (CN)
- State Key Laboratory of Satellite Ocean Environment Dynamics (CN)
Publication Details
- Journal
- Ocean-Land-Atmosphere Research
- Published
- 2026-10-27
- DOI
- https://doi.org/10.34133/olar.0186
- Primary Topic
- Climate variability and models
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China