The co-occurrence of wind and rainfall extremes can yield larger impacts than when either hazard occurs in isolation due to their potential nonlinear interactions. In Canada, extreme precipitation events commonly co-occur with strong winds during extratropical cyclones, frontal systems, and convective storms. The compound rainfall and wind extremes can increase surface runoff and debris transport and reduce urban drainage capacity, thereby exacerbating urban flooding and causing damage to buildings and critical infrastructure. Under future climate change, these compound extremes are likely to change in frequency and/or intensity. Therefore, understanding the interdependencies and joint behavior of these hazards in both is crucial for developing effective mitigation strategies under climate change. In this study, daily precipitation and maximum near-surface wind speed derived from high-resolution regional climate simulations produced by Ouranos (CRCM5–CMIP6), evaluated against observational datasets, are used to investigate changes in the characteristics of these concurrent extreme events under 1.5°C, 2°C, 3°C, and 4°C global warming levels. To model multivariate dependence between wind and rainfall extremes and to estimate joint probabilities, a novel multivariate statistical analysis framework is developed. Moreover, the relationship between compound wind–rainfall extremes and convective parameters such as CAPE (Convective Available Potential Energy) and CIN (Convective Inhibition) is investigated. These parameters characterize atmospheric instability and help improve understanding of storm dynamics and the identification of hazardous convective environments. The results provide insights into future changes in compound wind–rainfall extremes and their implications for infrastructure risk. KEYWORDS: compound extremes, Ouranos data, Environmental factors, joint return period