Understanding extreme temperature variations is important for countries to manage risks associated with climate change. Yet, the characteristics of temperature extremes and possible climate change impacts have not been adequately investigated in Singapore. In this study, we attempted to do so by defining 14 extreme temperature indices (ETIs) for the period of 1982–2018 in Singapore, and investigating the trends of those ETIs using a pre‐whitening Man‐Kendall test coupled with the Sen's slope estimator method. The linear and nonlinear relationships between ETIs and El Niño Southern Oscillation (ENSO) were also examined using correlation, composite and wavelet analysis. Our results indicate that trends of temperature extremes varied according to station locations, ETIs and time scales. In all stations, ETIs such as the monthly mean value of the diurnal range between maximum and minimum temperatures (DTR), cool nights (TN10p) and cool days (TX10p) presented decreasing trends, while the rest of them exhibited increasing trends. The composite values varied for different ETIs—meaning that while eight no‐threshold ETIs reflected smaller values, other ETIs reflected relatively larger composite values, indicating that ENSO may have affected those ETIs more. The ETIs were mainly statistically and significantly coherent with ENSO at a 2–8 year cycle. We hope that our findings would be beneficial for climate action planning and temperature‐related disaster prevention in Singapore.