Reducing uncertainty in local temperature projections.

ABSTRACT: Planning for adaptation to climate change requires accurate climate projections. Recent studies have shown that the uncertainty in global mean surface temperature projections can be considerably reduced using historical observations. However, the transposition of these new results to the local scale is not yet available. Here, we adapt an innovative statistical method that combines the latest generation of climate model simulations, global observations, and local observations to reduce uncertainty in local temperature projections. By taking advantage of the tight links between local and global temperature, we can derive the local implications of global constraints. The model uncertainty is reduced by 30% up to 70% at any location worldwide, allowing to substantially improve the quantificat

SUBMITTER: Qasmi S 

PROVIDER: S-EPMC9555774 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature