摘要:Global surface temperature (ST) datasets are the foundation for global climate change research. Several global ST datasets have been developed by different groups in NOAA NCEI, NASA GISS, UK Met Office Hadley Centre & UEA CRU, and Berkeley Earth. In this study, a new global ST dataset named China Merged Surface Temperature (CMST) was presented. CMST is created by merging the China-Land Surface Air Temperature (C-LSAT1.3) with sea surface temperature (SST) data from the Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5). The merge of C-LSAT and ERSSTv5 shows a high spatial coverage extended to the high latitudes and is more consistent with a reference of multi-dataset averages in the polar regions. Comparisons indicated that CMST is consistent with other existing global ST datasets in interannual and decadal variations and long-term trends at global, hemispheric, and regional scales from 1900 to 2017. The CMST dataset can be used for global climate change assessment, monitoring, and detection. The CMST dataset presented here is publicly available at https://doi.org/10.1594/PANGAEA.901295 (Li, 2019a) and has been published on the Climate Explorer website of the Royal Netherlands Meteorological Institute (KNMI) at http://climexp.knmi.nl/select.cgi?id=someone@somewhere&field=cmst (last access: 11 August 2018; Li, 2019b, c).