The article explores a new method using path signatures to understand how different factors in a system influence each other over time. By analyzing the areas under the paths, researchers can determine if one factor causes changes in another. This approach helps identify causal relationships in complex systems like climate data, even without the ability to conduct controlled experiments. The study shows that analyzing the signed areas between variables can reveal lag/lead causal connections, providing a way to test hypotheses about causal links between different factors in a system.