A new method uses a differentiable simple climate model to optimize training scenarios, enhancing emulator generalization. Training on one optimized scenario outperforms six standard ScenarioMIP pathways, and such scenarios yield more skillful emulators when used with intermediate-complexity models, despite smaller dataset sizes.