“…15,16,21 (1) Weight proportional to the inverse of the MAE, (2) weight proportional to the logarithm of the inverse of the MAE and (3) weight proportional to a Borda count-based ranking. 15 We consider the passive containment cooling system (PCCS) of AP1000 NPPs as case study 22 because (1) nuclear power is an energy option considered to reduce greenhouse gas emissions 23,24 and (2) it has been shown that the safety and reliability of NPPs are significantly influenced by changes of air temperature, precipitation, river flows, sea level, shoreline erosion, coastal storms, floods, heat waves and so on that affect cooling water supply. 2,8,[25][26][27] The proposed ensemble methods are used to aggregate the forecasts of the climate change models in order to assess the conditional functional failure probability (CFFP) of the PCCS by performing for an integrated probabilistic safety assessment conditional on climate projections 22,28 and to classify the temperature conditions that lead the PCCS to unexpected and dangerous scenarios.…”