A study reveals that anthropogenic aerosols and greenhouse gases (GHGs) are the primary drivers of precipitation changes in the United States. GHGs increase mean and extreme precipitation across all seasons, while aerosols reduce precipitation on a decadal scale. Local aerosols offset GHG effects in winter and spring but enhance rainfall in summer and fall. The conflicting literature on historical precipitation trends is explained by offsetting aerosol and GHG signals. Climate models reproduce observed changes but cannot confidently determine the impact of individual anthropogenic agents. Daily precipitation, including extreme events, is crucial for the global water cycle. Understanding precipitation changes is vital for water management, agriculture, and infrastructure. Existing studies struggle to attribute local-scale precipitation trends due to reliance on climate models and uncertainty in regional attribution. The study uses a new method to attribute human influence on seasonal mean and extreme precipitation over the CONUS, decomposing the combined anthropogenic signal into contributions from GHGs and aerosols. This approach uses Pearl-causal inference and in situ records to identify Granger-causal attribution statements. The results show that the slow precipitation response to aerosols (AER-glob) and GHGs is significant across most of the CONUS, while the fast response to local aerosols (AER-local) is detectable at smaller scales. The study highlights that GHG-driven increases in precipitation are masked by aerosol effects, particularly in extreme precipitation. The results emphasize the importance of considering both century-long records and multiple anthropogenic forcing agents in regional D&A analyses. The study also shows that climate models have high uncertainty in attributing precipitation changes, and that the combined anthropogenic signal emerges later than the isolated GHG signal due to aerosol masking. The findings contribute to evidence of GHG-driven increases in flood risk, particularly in the western United States. The study provides a framework for understanding regional precipitation trends and highlights the need for further research to improve regional D&A methods.A study reveals that anthropogenic aerosols and greenhouse gases (GHGs) are the primary drivers of precipitation changes in the United States. GHGs increase mean and extreme precipitation across all seasons, while aerosols reduce precipitation on a decadal scale. Local aerosols offset GHG effects in winter and spring but enhance rainfall in summer and fall. The conflicting literature on historical precipitation trends is explained by offsetting aerosol and GHG signals. Climate models reproduce observed changes but cannot confidently determine the impact of individual anthropogenic agents. Daily precipitation, including extreme events, is crucial for the global water cycle. Understanding precipitation changes is vital for water management, agriculture, and infrastructure. Existing studies struggle to attribute local-scale precipitation trends due to reliance on climate models and uncertainty in regional attribution. The study uses a new method to attribute human influence on seasonal mean and extreme precipitation over the CONUS, decomposing the combined anthropogenic signal into contributions from GHGs and aerosols. This approach uses Pearl-causal inference and in situ records to identify Granger-causal attribution statements. The results show that the slow precipitation response to aerosols (AER-glob) and GHGs is significant across most of the CONUS, while the fast response to local aerosols (AER-local) is detectable at smaller scales. The study highlights that GHG-driven increases in precipitation are masked by aerosol effects, particularly in extreme precipitation. The results emphasize the importance of considering both century-long records and multiple anthropogenic forcing agents in regional D&A analyses. The study also shows that climate models have high uncertainty in attributing precipitation changes, and that the combined anthropogenic signal emerges later than the isolated GHG signal due to aerosol masking. The findings contribute to evidence of GHG-driven increases in flood risk, particularly in the western United States. The study provides a framework for understanding regional precipitation trends and highlights the need for further research to improve regional D&A methods.