Evaluating the Reliability of GLENS Stratospheric Aerosol Injection Ensemble Simulations over Southeast Asia

Stratospheric Aerosol Injection (SAI) has been investigated as a climate intervention strategy to offset global warming, and regional impacts studies rely on simulations from the Geoengineering Large Ensemble (GLENS). The probabilistic behavior of the GLENS ensemble has not been systematically characterized for Southeast Asia. Because GLENS is a counterfactual experiment combining the Representative Concentration Pathway 8.5 (RCP8.5) forcing with active SAI, comparison with observations cannot validate the SAI response itself. In the early protocol years, the SAI forcing is small, so the early window provides a diagnostic of statistical consistency between the ensemble and the observed climate and of ensemble spread reliability. We compare the 21-member GLENS ensemble for 2020–2025 with ERA5 for daily precipitation and mean and maximum temperature using empirical coverage of the 95% prediction interval, rank histograms with the Jolliffe–Primo decomposition, the Continuous Ranked Probability Score, and the Brier Score for rainfall occurrence. Coverage is well below nominal for all variables, and rank histograms show pronounced U-shapes dominated by the dispersion error component, indicating systematic underdispersion. Because the underlying mechanisms are properties of the ensemble system rather than of the SAI forcing, this underdispersion is expected to persist in the future record, motivating statistical post-processing of GLENS before its use in SAI impact assessments.