Abstract: Based on the ERA5 atmospheric reanalysis dataset and the stational surface air temperature (SAT) and precipitation data from China National Climate Centre during 1951—2022, 33 East Asian winter monsoon (EAWM) indices are selected and categorized into six types, namely the land-sea sea-level pressure (SLP) difference indices, the Siberian high indices, the East Asian trough indices, the low-level wind indices, the mid- to high-level wind indices, and the synthetic indices. Characteristics of their long-term linear trends and interannual and interdecadal variabilities are then analyzed. Their abilities to represent the spatiotemporal variability of winter SAT and precipitation in China and their relationships with major internal variabilities of the climate system such as the El Niño-Southern Oscillation (ENSO) and the Arctic Oscillation (AO) are also evaluated. The results are as follows: (1) In terms of long-term trend, although winter climate in China is characterized by an obvious warming and wetting trend, only the East Asian trough and the synthetic indices exhibit a significant weakening trend, while other indices basically show a weak strengthening trend. This result suggests that there are certain differences in the responses of different sub-members of the EAWM to current global warming. (2) On the interannual and interdecadal variability, the EAWM indices mainly show characteristics of quasi-4 a, quasi-8 a and quasi-16 a periodic oscillations. Most of the indices can well capture the interdecadal weakening of the EAWM that occurred around the mid to late 1980s. Meanwhile, the Siberian high indices, the East Asian through indices, the mid- to high-level wind indices and the land-sea SLP difference indices which consider the north-south SLP difference, show a good representation of the interdecadal strengthening of the EAWM that occurred in the mid-2000s. (3) All types of indices, except the low-level wind indices, perform well in reflecting the SAT variability in China. In particular, the indices based on the Siberian high show the best performance. The winter precipitation variability in China is best described by the low-level wind indices, while the Siberian high indices show relatively poor representation. (4) Regarding the relationship between major internal variability of the climate system and the EAWM, most of the indices show an excellent performance in reflecting the ENSO-EAWM relationship, among which the low-level wind indices show the best ability. The AO-EAWM relationship is best reflected by the Siberian high and the East Asian trough indices. In general, except for the considerable differences in the long-term trend, all types of EAWM indices can consistently reflect main characteristics of winter climate change in China. However, different categories of indices emphasize different aspects. Therefore, appropriate indices should be selected according to the purpose of the study in analyzing scientific issues related to the EAWM.