We present a 1-km resolution monthly mean air temperature (Ta) dataset across the Tibetan Plateau from 2001 to 2015. It ranges from 25¡ã-45¡ãN, 70¡ã-105¡ãE, covering a total area of ~7,045,000 km2. To develop this dataset, 10 machine learning algorithms were applied to 11 environmental variables derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data and topographic index data. The best model generated by Cubist algorithm was finally selected to calculate monthly mean Ta, and achieved an overall accuracy of RMSE= 1.00 ¡ãC and MAE= 0.73 ¡ãC. To get details of this dataset, please refer to the manuscript "Mapping monthly air temperature in the Tibetan Plateau from MODIS data based on machine learning methods". This Ta dataset provides spatially continuous coverage compared with station observed data, and has much higher accuracy and spatial resolution than reanalysis datasets, making it a useful dataset for climate change and environmental studies in the Tibetan Plateau.

Xu Y., Knudby A., Shen Y., Liu Y., Mapping monthly air temperature in the Tibetan Plateau from MODIS data based on machine learning methods. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(2): 345-354. (DOI: 10.1109/jstars.2017.2787191).

The Ta dataset is provided in ENVI standard format. The coordinate system is WGS84 Geographic Coordinate System.