Detecting Changes in Global Extremes Under the GLENS‐SAI Climate Intervention Strategy

As anthropogenic activities continue to drive increases in extreme events, the fundamental solution of reducing greenhouse gas emissions remains elusive. Thus, there is growing interest stratospheric aerosol injection (SAI) offset some most dangerous consequences climate change. Although global SAI deployment would likely be easy detect by metrics, detectability on events might more difficult. We examine this question model simulations SAI; specifically, Stratospheric Aerosol Geoengineering Large Ensemble (GLENS-SAI) scenario. train a logistic regression predict whether map extremes came from with or without SAI. The timing accurate predictions quantification time required impacts. find that regional changes temperature and precipitation under GLENS are robustly detected within 1 15 years initial injection, respectively.