The Three Gorges Reservoir Area and its Surrounding Region (TGRASR) play a crucial role in the Yangtze River Basin. Over the past years, there has been growing concern about the effects of extreme weather events in this area, mainly attributed to climate change. To effectively address the implications of climate change, a thorough understanding of the temporal and spatial variability of these events is necessary. However, some of the previous studies have been limited to analyzing trend changes in events and have not sufficiently considered the connection with atmospheric circulation indices. In this study, we analyzed the spatio-temporal variations of extreme weather events using the Mann-Kendall and Sen's slope trend methods. Then, the correlation between extreme weather events and climate factors is explored using the Mantel test, Geo-Detector method (GDM), and Partial wavelet coherency (PWC) in terms of linear, hierarchical heterogeneity, and nonlinear, respectively. Finally, we investigated the potential climate factors that affect the temporal and spatial variability of extreme weather occurrences. The results showed that(1) among the 12 extreme indices analyzed in the TGRASR region from 1960 to 2020, there was a decreasing trend observed in Consecutive dry days (CDD), Consecutive wet days (CWD), and Annual count of days when precipitation is ≥10 mm (R10), while the remaining indices exhibited an increasing trend. Subsequent analysis employing the M-K mutation revealed that the mutation point for CWD occurred around 1975, resulting in a significant decrease in its trend. Additionally, the Simple daily intensity index (SDII), Annual count of days when the daily maximum temperature (TX) is >25 °C (SU25), and R10 displayed a decreasing trend. Mutations in the trends SU25, Annual count of days when the daily minimum temperature (TN) is >20 °C (TR20), and Annual count of days with at least 6 consecutive days when TX > 90th percentile (WSDI) were observed in 1997, 1999, 2003, and 2005, respectively. Following these mutations, all four indices displayed a substantial increase. (2) CDD, CWD, and R10 exhibit a decreasing trend across most stations, whereas the remaining indices demonstrate an increasing trend. Regarding spatial distribution, indices characterizing precipitation frequency and intensity exhibit higher mean values in the southeastern part of the TGRASR. (3) Mantel test: North Pacific pattern (NP), North Tropical Atlantic (NTA), and Global Mean Land/Ocean Temperature (GMLOT) have significant linear correlations with extreme precipitation and extreme temperature events; GDM: GMLOT and NTA are the main contributors to extreme precipitation and extreme temperature; PWC: 12 extreme indices have some nonlinear associations with all five climate factors. The study's findings can assist decision-makers in formulating sustainable water resource management strategies and measures for mitigating drought and flood risks. Additionally, the study contributes to uncovering climatic factors that influence changes in extreme weather events.