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The self-calibrating Palmer Drought Severity Index (sc_PDSI) is developed within the frame of the PDSI model, but is considered to be more appropriate for global drought monitoring. The sc_PDSI can automatically calibrate itself at any location using dynamically computed values and can calculate evapotranspiration using the FAO-56 Penman Monteith (P M) equation. However, the correlation of the sc_PDSI(P-M) with some factors that drive drought, such as precipitation (P) and the reference evapotranspiration (ET0), is still unclear in China. With the aim of solving this issue, we analyzed the correlation of the detrended sc_PDSI(P-M) with the detrended P and ET on different timescales (one, three, six and 12 months) in China for the period 1951-2015. The results show that both the P and ETo are highly correlated with the sc_PDSI(P-M) on a 12-month timescale. On this timescale, the sc_PDSI(P-M) is more sensitive to P than to ET on the national scale, except for northeastern China. Thus the sc_PDSI(P-M) may effectively fit the long-term variations in these drivers of drought, especially P. These results provide guidance on the use of the sc_PDSI(P-M) to detect the impacts of climate change on drought severity under the climatic conditions found in China.