Abstract. 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).
Deriving a sea surface temperature record suitable for climate change research from the along-track scanning radiometers
