Dataset of daily near-surface air temperature in China from 1979 to 2018

Abstract. Near-surface air temperature (Ta) is an important physical parameter that reflects climate change. Many methods are used to obtain the daily maximum (Tmax?), minimum (Tmin?), and average (Tavg) temperature, but affected by multiple factors. To Ta data (Tmax?, Tmin?, Tavg) with high spatio-temporal resolution in China, we fully analyzed advantages disadvantages of various existing data. Different reconstruction models were constructed for different weather conditions, accuracy was improved building correction equations regions. Finally, a dataset China from 1979 2018 obtained spatial 0.1?. For Tmax?, validation using situ shows root mean square error (RMSE) ranges 0.86 1.78?, absolute (MAE) varies 0.63 1.40?, Pearson coefficient (R2) 0.96 0.99. RMSE 0.78 2.09?, MAE 0.58 1.61?, R2 0.95 Tavg, 0.35 1.00?, 0.27 0.68 ?, 0.99 1.00. Furthermore, evaluation indicators analyze temporal variation trends Ta, Tavg increase more than 0.03 ?C yr?1, which consistent general global warming trend. In summary, this has accuracy, compensates values previously missing at provides key parameters study change, especially high-temperature drought low-temperature chilling damage. The publicly available https://doi.org/10.5281/zenodo.5502275 (Fang et al., 2021a).