Abstract: The IPCC indicates that warming should include three types, that is, shifted mean, increased variability, and changed symmetry. However, at present, the main concern of warming is still shifted mean, which affects the overall understanding of surface warming. In this study, based on daily temperature data from 590 meteorological stations during 1961–2018, we quantified indicators of shifted mean, increased variability, and changed symmetry using mean temperature, temperature variance, and high-temperature days, respectively. Then, we revealed the spatial pattern of trends in mean temperature, temperature variance, and high-temperature days across China. Although the mean temperature exhibited a significant increasing trend over the entire study period, the trend was reversed around 1986, with a decreasing trend before 1986 and a significant warming trend after 1986. During 1961–2018, the number of stations with an advanced onset date of high temperature (63.6%) was greater than that with a delay (36.4%). Moreover, the temperature variance showed a significant decreasing trend from 1961 to 1986 but a notable increasing trend from 1986 to 2018. Overall, the variation in mean temperature, temperature variance, and high-temperature days had large spatial heterogeneity. From 1961 to 1986, the number of stations with delayed high-temperature onset date, decreasing mean temperature, and decreasing temperature variance was the largest, accounting for 23.9% of the total, and mainly distributed in the subtropical region. Meanwhile, from 1986 to 2018, the number of stations with delayed high-temperature onset dates, increasing mean temperature, and increasing temperature variance was the largest, accounting for 41.5% of the observed stations, with a more scattered spatial distribution. The regional variability in the trend changes of different temperature indicators reflects the heterogeneity of global change sensitivity in different regions. Therefore, studies that simultaneously focus on the changes in mean temperature, high-temperature days, and temperature variance can better reflect the characteristics of climate change and help predict the future climate change risk, which is of great significance to the development of mitigation and adaptation policy frameworks for climate change in China.