The use of emergent constraints to quantify uncertainty for policyrelevant quantities such as equilibrium climate sensitivity (ECS) has become increasingly widespread in recent years. Many researchers ...

A new technique enables huge machine-learning models to efficiently generate more accurate quantifications of their uncertainty about certain predictions. This could help practitioners determine ...

Quantifying uncertainty in carbon accounting is essential at scales ranging from individual projects to country-level compensation for reducing emissions from deforestation and forest degradation.