Forecasting carbon-risk hotspots ahead of the extreme 2026 El Niño
Xiaomeng Du, Runda Jiang, Philippe Ciais, Pierre Friedlingstein, Stephen Sitch, Mike O'Sullivan, Jefferson Goncalves de Souza, Tim Stripp, Piyu Ke, Yi Xi, Minxuan Sun, Xiaoran Wu, Mengjie Han, Shanshan Song, Qiang Zhang, Wei Li
Abstract
A potentially super El Niño is forecasted in 2026, raising the need to anticipate land carbon-cycle risks before its impacts unfold. We develop a prospective early-warning framework that uses dynamic global vegetation models driven by an ensemble of ECMWF seasonal climate forecasts and machine-learning burned area predictions. Forecasts indicate a 0.23 0.21 PgC reduction in global net biome productivity in the second half of 2026, with hotspots of sink weakening in eastern South America and elevated fire risk in Southeast Asia.
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