The reversal of temperature anomalies from warm to cold and vice versa in the East Asian region is one of the most significant climatic phenomena during the winter season under the context of global warming. Compared to the variability of seasonal-mean winter temperature anomalies, the climate prediction uncertainty for the reversal phenomenon is greater, and its adverse impacts are more significant. Based on atmospheric reanalysis data from the winters of 1980/81 to 2022/23, this study employs seasonal empirical orthogonal decomposition and composite analysis methods to investigate the interannual variability of the East Asian winter temperature anomaly reversal mode (TARM). The results indicate that although the different processes of the East Asian winter TARM are related to intraseasonal reversals of the Siberian High, the Eurasian teleconnection and the Arctic vortex anomalies, the interannual variability of the "warm to cold" mode is significantly stronger than that of the "cold to warm" mode, suggesting a pronounced asymmetry in the interannual variability of TARM. In the "warm to cold" mode, the lower-level Siberian High strengthens over time, with the positive phase of East Atlantic-West Russia-like teleconnection in early winter shifting to a negative phase in late winter, leading to more active cold air. Conversely, in the "cold to warm" mode, the intensity of the winter Arctic vortex shifts from weak to strong, the Siberian High weakens after that, favoring the appearance of temperature anomalies that are cold in early winter and warm in late winter. Further analysis shows that North Atlantic and tropical Indian Ocean sea surface temperature anomalies with La Ni?a are important factors influencing the "warm to cold" mode, while a reduction in November Barents-Kara sea ice acts as a precursor signal for the "cold to warm" mode. Therefore, the diversity of atmospheric underlying conditions is an important reason for the asymmetry of the East Asian winter TARM. Therefore, climate prediction for the East Asian winter TARM should consider the diversity of atmospheric underlying conditions.