Climate models rely on uncertain adjustable parameters. We tested millions of combinations of these inputs to see how well the model matches real-world data. We found that no single set of inputs can match several observations at the same time, which suggests that the issue lies in the model itself. We developed a method to detect these conflicts and trace them back trace them to their source. The aim is to help modellers target improvements that reduce uncertainty in climate projections.