Changes in the Sun’s energy output are thought to influence Earth’s climate, but confirming that influence is challenging. The signal is small, and Earth’s climate is shaped by many other processes, including internal variability and feedbacks. In this study, we use a method called Convergent Cross Mapping (CCM) to test whether solar variability had a discernible effect on temperature during the Holocene, the last ~12,000 years of relatively stable climate.

Unlike methods that rely on correlations, CCM can detect causal relationships in complex systems, in particular, nonlinear relationships or vary across timescales. We apply CCM to two independent reconstructions of solar output and three temperature records, including a single-site Greenland record and two global-scale temperature reconstructions. We also compare our results to simulations from climate models with and without solar forcing.

We find evidence that solar variability influenced temperature during the Holocene, but the strength and pattern of that influence differ across datasets. This suggests that the Sun was not the sole or dominant driver of Holocene climate variability, and that other processes played a significant role. Our study shows how causal inference tools can help clarify subtle connections in the climate system.