Abstract. It is very important to comprehend the climate variations in the vast regions of Central Plains of China. Current knowledge about climate changes of the past few hundred years in this region is primarily based on historical documents, and lack of evidences from the natural archives. However, these documents had somewhat artificially effects caused by the recorders, and not sufficient to fully understand natural climatic changes. In this paper, based on a significant correlation between the tree-ring width of Chinese Pine and observed instrumental data in the Mt. Yaoshan, China, we formulated a transfer function to reconstruct the mean minimum temperature (MMinT) from the previous December to the current June (T_{min_DJ}) for the period 1873–2011. The reconstruction explained 39.8% of the instrumental variance during the calibration period of 1958–2011. High T_{min_DJ} intervals with values greater than the 139 year average occurred in 1932–1965 and 1976–2006. The intervals 1878–1894 and 1906–1931 experienced a T_{min_DJ} lower than the 139 year average. The ten highest T_{min_DJ} years occurred after the 1950s, especially after 1996. A distinct upward trend in the T_{min_DJ} series beginning in the 1910s was apparent, and the highest value occurred around 2000. The 20th-century warming signal was captured well by the Yaoshan T_{min_DJ} temperature reconstruction, indicating that the temperature rise in the sensitive Central Plains of China region reflected the global temperature change. The T_{min_DJ} reconstruction also matched several other temperature series in China with similar warm-cold patterns. The distinct spatial correlation between both observed and reconstructed series and CRU TS3.10 grid data indicates that our results may represent T_{min_DJ} changes on a larger scale. The spatial correlation with sea surface temperature (SST) indicated that observed and reconstructed T_{min_DJ} temperatures in the Mt. Yaoshan are closely linked to the West Pacific, Indian and North Atlantic Oceans as well as El Niño-Southern Oscillation (ENSO).