Significant increases in both heatwaves and heavy precipitation were reported under global warming, leading to detrimental social, economic, and environmental impacts. However, future variations of such compound heatwave and heavy precipitation events (CHWHPs) were barely analyzed in Guangdong. Therefore, a downscaled compound heatwave-precipitation analysis approach (DCHP) was developed to explore the spatio-temporal variations of CHWHPs in Guangdong under two shared socioeconomic pathways (i.e., SSPs). Potential changes in four parameters (i.e., the occurrence frequency, the average duration, the total intensity, and the longest duration) of projected CHWHPs for the future (i.e., 2025-2054 and 2066-2095) and historical (i.e., 1985-2014) periods were analyzed based on the multi-model ensemble of 15 global climate models (GCMs) from the Coupled Model Intercomparison Projected Phase 6 (CMIP6). Additionally, the effects of multiple impact factors (GCM, SSP, and their interactions) on the compound events were investigated through a multilevel factorial analysis approach. The results showed that the majority of Guangdong would undergo a significant increasing trend in the projected temperature and precipitation (e.g., 0.43-0.61 degrees C per decade and - 7.79 to 43.02 mm per decade under SSP5-8.5). Spatial changes and interannual trends suggested that Guangdong would suffer more CHWHP events in the future, especially for 2066-2095 under SSP5-8.5. The variations of four parameters are projected to increase by 13.86 events, 2.27 days per event, 55.32 degrees C, and 7.13 days during 2066-2095 under SSP5-8.5, respectively; the MK test of four parameters are statistically significant and the Sen's slopes are 0.0125%, 0.0027%, 0.1946%, and 0.0097% per decade, respectively. The higher increases in such parameters are expected to be concentrated in western, northwestern, and northeastern Guangdong. The factorial analysis results indicate that the GCM choice is a major impacting factor on the projected CHWHP parameters in two future periods; the contribution of such factor would decrease slightly from 2025-2054 to 2066-2095. The results can help support informed decision-making to mitigate and adapt to potential risks from compound events in multiple sectors under climate change, such as human health and agriculture.