Based on the four typical global monthly surface temperature datasets, namely the climate research dataset of the University of East Anglia (CRUTEM3), the dataset of the U.S. National Climatic Data Center (GHCN-V3), the dataset of the U.S. National Aeronautics and Space Administration (GISSTMP), and the Berkeley Earth surface temperature dataset, this paper analyzes the status of existing resources through extensive research and international cooperation. Then, China's first global land monthly temperature dataset was developed by integrating the four global monthly surface temperature datasets and some regional datasets from the major countries or regions. This dataset contains 9519 stations from all over the world with the length no less than 20 years for monthly average temperature, 7073 for monthly maximum, and 6587 for monthly minimum temperature. Compared with CRUTEM3 and GHCN-V3, the station density of this dataset is much higher, especially in South America, Africa and Asia; besides, there are much more stations after the 1990s, which can dramatically reduce the uncertainty of the estimated global temperature trend since 1990.