The precipitation pattern is an indicator of climate change. Under the background of climatic warming, many research results on the change in precipitation patterns in different regions have been accumulated. However, there has been insufficient comparison of the sensitivity of rainfall and snowfall to climatic warming. On the basis of temperature and precipitation observational data from 58 meteorological stations in northeast China (Heilongjiang Province) acquired from 1961 to 2016, in this study, we perform a detailed analysis of the spatiotemporal changes in the precipitation pattern and the sensitivity of the pattern to climate change by using statistical methods such as trend, abrupt change, and correlation analyses. According to the results, no significant changes in the patterns of the precipitation amount and frequency were observed in the high latitudes of northeast China from 1961 to 2016. Nevertheless, the ratio of the changes in annual snowfall and precipitation amounts increased significantly in the eastern part of the region. No significant changes were observed in the rainfall amount or frequency patterns at different intensities. However, significant changes were observed in the snowfall amount and frequency patterns at different intensities. The amount and frequency of heavy and moderate snow showed a significant upward trend. The proportion of heavy and moderate snow frequencies increased significantly. In addition, the proportion of light snow frequency decreased significantly. A comprehensive analysis showed that snowfall is sensitive to temperature changes, whereas rainfall is not. The snowfall frequency and the proportion of snowfall frequency are most sensitive to temperature; an increase in temperature mainly affects the frequencies of light, heavy, and moderate snow and the proportion of light snow frequency. The major contribution of this study is that it clarifies the sensitivity differences between rainfall and snowfall to increases in temperature and demonstrates that snowfall frequencies and proportions at different blizzard intensities are the most sensitive indicators to changes in temperature.