AI and the World's Hard Problems · Earth & climate science · arXiv · 2026-10-22
Forecasting carbon-risk hotspots ahead of the extreme 2026 El Ni\~no
With a potentially super El Niño forecast for 2026, an early-warning framework was developed to anticipate land carbon-cycle risks before its impacts unfold. It 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 weakening carbon sinks in eastern South America and elevated fire risk in Southeast Asia.