Detection and attribution studies generally examine individual climate variables such as temperature and precipitation. Thus, we lack a strong understanding of climate change impacts on correlated climate extremes and compound events, which have become more common in recent years. Here we present a monthly-scale compound warm and dry attribution study, examining CMIP6 climate models with and without the influence of anthropogenic forcing. We show that most regions have experienced large increases in concurrent warm and dry months in historical simulations with human emissions, while no coherent change has occurred in historical natural-only simulations without human emissions. At the global scale, the likelihood of compound warm-dry months has increased 2.7 times due to anthropogenic emissions. With this multivariate perspective, we highlight that anthropogenic emissions have not only impacted individual extremes but also compound extremes. Due to amplified risks from multivariate extremes, our results can provide important insights on the risks of associated climate impacts.